From 67f9fc82b0316cd33d815f5b17e3c1b0a38eac56 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 26 Dec 2025 13:49:50 -0500 Subject: [PATCH 01/67] Add integration test --- .github/workflows/ci_on_ubuntu.yml | 10 +- ci/test_integration_espnet3.sh | 29 ++++ egs3/TEMPLATE/__init__.py | 0 egs3/TEMPLATE/asr/__init__.py | 0 egs3/TEMPLATE/asr/conf/infer.yaml | 61 +++++++ egs3/TEMPLATE/asr/conf/measure.yaml | 24 +++ egs3/TEMPLATE/asr/conf/train.yaml | 126 ++++++++++++++ egs3/TEMPLATE/asr/readme.md | 33 ++++ egs3/TEMPLATE/asr/run.py | 210 ++++++++++++++++++++++++ egs3/__init__.py | 0 egs3/mini_an4/__init__.py | 1 + egs3/mini_an4/asr/__init__.py | 1 + egs3/mini_an4/asr/conf/infer.yaml | 37 +++++ egs3/mini_an4/asr/conf/measure.yaml | 26 +++ egs3/mini_an4/asr/conf/train.yaml | 159 ++++++++++++++++++ egs3/mini_an4/asr/path.sh | 6 + egs3/mini_an4/asr/run.py | 20 +++ egs3/mini_an4/asr/run.sh | 15 ++ egs3/mini_an4/asr/src/__init__.py | 1 + egs3/mini_an4/asr/src/create_dataset.py | 152 +++++++++++++++++ egs3/mini_an4/asr/src/dataset.py | 57 +++++++ egs3/mini_an4/asr/src/tokenizer.py | 25 +++ 22 files changed, 988 insertions(+), 5 deletions(-) create mode 100644 ci/test_integration_espnet3.sh create mode 100644 egs3/TEMPLATE/__init__.py create mode 100644 egs3/TEMPLATE/asr/__init__.py create mode 100644 egs3/TEMPLATE/asr/conf/infer.yaml create mode 100644 egs3/TEMPLATE/asr/conf/measure.yaml create mode 100644 egs3/TEMPLATE/asr/conf/train.yaml create mode 100644 egs3/TEMPLATE/asr/readme.md create mode 100644 egs3/TEMPLATE/asr/run.py create mode 100644 egs3/__init__.py create mode 100644 egs3/mini_an4/__init__.py create mode 100644 egs3/mini_an4/asr/__init__.py create mode 100644 egs3/mini_an4/asr/conf/infer.yaml create mode 100644 egs3/mini_an4/asr/conf/measure.yaml create mode 100644 egs3/mini_an4/asr/conf/train.yaml create mode 100644 egs3/mini_an4/asr/path.sh create mode 100644 egs3/mini_an4/asr/run.py create mode 100644 egs3/mini_an4/asr/run.sh create mode 100644 egs3/mini_an4/asr/src/__init__.py create mode 100644 egs3/mini_an4/asr/src/create_dataset.py create mode 100644 egs3/mini_an4/asr/src/dataset.py create mode 100644 egs3/mini_an4/asr/src/tokenizer.py diff --git a/.github/workflows/ci_on_ubuntu.yml b/.github/workflows/ci_on_ubuntu.yml index ca10f1367e2e..be959564d90e 100644 --- a/.github/workflows/ci_on_ubuntu.yml +++ b/.github/workflows/ci_on_ubuntu.yml @@ -160,11 +160,11 @@ jobs: source tools/activate_python.sh coverage erase - # - name: test espnet3 integration - # run: ./ci/test_integration_espnet3.sh - # - uses: codecov/codecov-action@v2 - # with: - # flags: test_integration_espnet3 + - name: test espnet3 integration + run: ./ci/test_integration_espnet3.sh + - uses: codecov/codecov-action@v5 + with: + flags: test_integration_espnet3 test_configuration_espnet2: runs-on: ${{ matrix.os }} diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh new file mode 100644 index 000000000000..7c34d954be49 --- /dev/null +++ b/ci/test_integration_espnet3.sh @@ -0,0 +1,29 @@ +#!/usr/bin/env bash + +set -euo pipefail + +. tools/activate_python.sh +. tools/extra_path.sh + +python="coverage run --append" +cwd=$(pwd) + +gen_dummy_coverage(){ + touch empty.py + ${python} empty.py +} + +python3 -m pip install -e '.[asr]' + +cd ./egs3/mini_an4/asr +gen_dummy_coverage +echo "==== [ESPnet3] ASR ====" +source ./path.sh +${python} run.py \ + --stages create_dataset train_tokenizer collect_stats train infer measure \ + --train_config conf/train.yaml \ + --infer_config conf/infer.yaml \ + --measure_config conf/measure.yaml + +rm -rf exp data +cd "${cwd}" diff --git a/egs3/TEMPLATE/__init__.py b/egs3/TEMPLATE/__init__.py new file mode 100644 index 000000000000..e69de29bb2d1 diff --git a/egs3/TEMPLATE/asr/__init__.py b/egs3/TEMPLATE/asr/__init__.py new file mode 100644 index 000000000000..e69de29bb2d1 diff --git a/egs3/TEMPLATE/asr/conf/infer.yaml b/egs3/TEMPLATE/asr/conf/infer.yaml new file mode 100644 index 000000000000..42714a973b6d --- /dev/null +++ b/egs3/TEMPLATE/asr/conf/infer.yaml @@ -0,0 +1,61 @@ +# Inference/decoding configuration template for ESPnet3 ASR. +# Mirrors the training paths but keeps only inference-relevant knobs. + +# Minimal runtime scaffold; fill in task in derived configs if needed. +num_device: 1 +num_nodes: 1 + +# Path scaffold relative to the recipe root. +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: asr_template_eval +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode + +# Dataset definition for test splits only. +dataset: + _target_: espnet3.components.data_organizer.DataOrganizer + test: + - name: test-clean + dataset: + _target_: src.dataset.LibriSpeechDataset + data_dir: ${dataset_dir} + split: test-clean + +# Parallel execution used during data loading / scoring (defaults to local). +parallel: + env: local + n_workers: 1 + +# DataLoader defaults; keep small batch settings for lightweight decoding. +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + batches: + type: numel + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 4 + batch_bins: 4000000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} diff --git a/egs3/TEMPLATE/asr/conf/measure.yaml b/egs3/TEMPLATE/asr/conf/measure.yaml new file mode 100644 index 000000000000..38df1c4f63f4 --- /dev/null +++ b/egs3/TEMPLATE/asr/conf/measure.yaml @@ -0,0 +1,24 @@ +# Metric/scoring configuration template for ESPnet3 ASR. +# Consumes decode outputs under decode_dir and reports metrics. + +# Path scaffold relative to the recipe root; keep aligned with infer.yaml. +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: asr_template_eval +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: /path/to/your/dataset + +# Dataset definition for test splits only (used to enumerate test names). +dataset: + _target_: espnet3.components.data_organizer.DataOrganizer + test: + - name: test-clean + dataset: + _target_: src.dataset.LibriSpeechDataset + data_dir: ${dataset_dir} + split: test-clean + +# Metrics block intentionally empty in template; fill with WER/CER, etc. +metrics: diff --git a/egs3/TEMPLATE/asr/conf/train.yaml b/egs3/TEMPLATE/asr/conf/train.yaml new file mode 100644 index 000000000000..2dc73bbd066f --- /dev/null +++ b/egs3/TEMPLATE/asr/conf/train.yaml @@ -0,0 +1,126 @@ +# Main training config template for ESPnet3 ASR. +# This file is intentionally verbose to document how each field is used in the +# default recipe skeleton. Copy and trim it for your own recipe. + +# Number of devices/nodes; kept minimal for the template. +num_device: 1 +num_nodes: 1 +task: # Hydra target of the training task (fill in per-recipe if needed). + +# Path scaffold relative to the recipe root. +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: asr_template_train +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: /path/to/your/dataset +# Dataset creation function (downloads into dataset_dir cache). +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + +# Dataset definition for training/validation splits. +dataset: + _target_: espnet3.components.data_organizer.DataOrganizer + train: + - name: train-split + dataset: + _target_: src.dataset.LibriSpeechDataset + data_dir: ${dataset_dir} + split: train + valid: + - name: valid-split + dataset: + _target_: src.dataset.LibriSpeechDataset + data_dir: ${dataset_dir} + split: dev + + # Optional global preprocessor; can also be omitted + preprocessor: + +tokenizer: + # Recipe should provide a text_builder that returns tokenizer text + # (list[str] or path). + text_builder: + func: src.tokenizer.gather_training_text + dataset_dir: ${dataset_dir} + split: train + +# Parallel execution settings used by espnet3.parallel (defaults to local). +parallel: + env: local + n_workers: 1 + + +# DataLoader common collate and iterator setup. +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + batches: + type: numel + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 4 + batch_bins: 4000000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + + +# Optimizer and scheduler are intentionally lightweight defaults. +optim: + _target_: torch.optim.Adam + lr: 0.002 + weight_decay: 0.000001 + + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 15000 + + +best_model_criterion: + - - valid/loss + - 3 + - min + + +# Trainer settings map to Lightning Trainer; override per-recipe as needed. +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 100 + max_epochs: 10 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +fit: {} diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md new file mode 100644 index 000000000000..843e40d97ddf --- /dev/null +++ b/egs3/TEMPLATE/asr/readme.md @@ -0,0 +1,33 @@ +# LibriSpeech 100h ESPnet3 recipe + +This recipe follows the [lightning-hydra-template]( +https://github.com/ashleve/lightning-hydra-template +) layout and uses the latest `espnet3` package utilities. + +## Quick start + +```bash +# 0) Edit configs to set paths (e.g., conf/train.yaml: dataset_dir, create_dataset.func) + +# 1) Convert LibriSpeech to Hugging Face format (run once) +python run.py --stages create_dataset --train_config conf/train.yaml + +# 2) Train with the default Branchformer configuration +python run.py --stages train --train_tokenizer --collect_stats \ + --train_config conf/train.yaml + +# 3) Decode +python run.py --stages infer --infer_config conf/infer.yaml + +# 4) Score +python run.py --stages measure --measure_config conf/measure.yaml +``` + +All hyper-parameters are stored in `configs/` and can be overridden using +Hydra syntax. For example: + +```bash +python run.py --stages train \ + --train_overrides trainer.max_epochs=10 runtime.device=cuda \ + --train_config conf/train.yaml +``` diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py new file mode 100644 index 000000000000..1ec052b8071f --- /dev/null +++ b/egs3/TEMPLATE/asr/run.py @@ -0,0 +1,210 @@ +#!/usr/bin/env python3 +"""Generic runner template for System-based experiments.""" + +from __future__ import annotations + +import argparse +import sys +from pathlib import Path +from typing import Any, Callable, List, Optional, Sequence, Tuple, Type + +from omegaconf import OmegaConf + +from espnet3.utils.config import load_config_with_defaults +from espnet3.utils.logging import configure_logging, log_env_metadata, log_run_metadata +from espnet3.utils.stages import resolve_stages, run_stages + +# Default stage list (can be extended/overridden by callers) +DEFAULT_STAGES: List[str] = [ + "create_dataset", + "train_tokenizer", + "collect_stats", + "train", + "infer", + "measure", + "publish", +] + +# Type alias for a System class +SystemCls = Type[Any] +AddArgsFn = Callable[[argparse.ArgumentParser], None] + + +def build_parser( + stages: Sequence[str], + add_arguments: Optional[AddArgsFn] = None, +) -> argparse.ArgumentParser: + """Build base ArgumentParser and let caller extend it.""" + parser = argparse.ArgumentParser() + + parser.add_argument( + "--stages", + choices=list(stages) + ["all"], + nargs="+", + default=["all"], + help="Which stages to run. Multiple values allowed.", + ) + parser.add_argument( + "--train_config", + default=None, + type=Path, + help=( + "Hydra config for training (passed to load_config_with_defaults). " + "Required for create_dataset/train_tokenizer/collect_stats/train stages." + ), + ) + parser.add_argument( + "--infer_config", + default=None, + type=Path, + help="Hydra config for inference/decoding stage.", + ) + parser.add_argument( + "--measure_config", + default=None, + type=Path, + help="Hydra config for measure/scoring stage.", + ) + parser.add_argument( + "--dry_run", + action="store_true", + help="Print what would be executed without actually running stages.", + ) + + # Stage-specific arguments can be added here if needed + parser.add_argument( + "--train.dataset_dir", + default=None, + type=Path, + help="dataset directory for training (used in some stages).", + ) + + # Let caller add custom CLI arguments + if add_arguments is not None: + add_arguments(parser) + + return parser + + +def parse_cli_and_stage_args( + parser: argparse.ArgumentParser, + *, + stages: Sequence[str], +) -> Tuple[argparse.Namespace, List[str]]: + args = parser.parse_args() + stages_to_run = resolve_stages(args.stages, stages) + + return args, stages_to_run + + +def main( + args, + system_cls: SystemCls, + *, + stages: Sequence[str] = DEFAULT_STAGES, +) -> None: + stages_to_run = resolve_stages(args.stages, stages) + + # ----------------------------------------- + # Load configs + # ----------------------------------------- + train_config = ( + None + if args.train_config is None + else load_config_with_defaults(args.train_config) + ) + infer_config = ( + None + if args.infer_config is None + else load_config_with_defaults(args.infer_config) + ) + measure_config = ( + None + if args.measure_config is None + else load_config_with_defaults(args.measure_config) + ) + + log_dir = getattr(train_config, "exp_dir", None) + logger = configure_logging(log_dir=Path(log_dir) if log_dir else None) + log_run_metadata( + logger, + argv=sys.argv, + configs={ + "train": Path(args.train_config) if args.train_config else None, + "infer": Path(args.infer_config) if args.infer_config else None, + "measure": Path(args.measure_config) if args.measure_config else None, + }, + ) + log_env_metadata(logger) + if train_config is not None: + logger.info( + "Train config content:\n%s", OmegaConf.to_yaml(train_config, resolve=True) + ) + if infer_config is not None: + logger.info( + "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) + ) + if measure_config is not None: + logger.info( + "Measure config content:\n%s", + OmegaConf.to_yaml(measure_config, resolve=True), + ) + + # ----------------------------------------- + # Instantiate system + # ----------------------------------------- + system = system_cls( + train_config=train_config, + infer_config=infer_config, + measure_config=measure_config, + ) + + # ----------------------------------------- + # Resolve stages and run + # ----------------------------------------- + logger.info("System: %s", system_cls.__name__) + logger.info("Requested stages: %s", args.stages) + logger.info("Resolved stages: %s", stages_to_run) + + # Guardrail: ensure required configs exist for requested stages + pretrain_stages = { + "create_dataset", + "train_tokenizer", + "collect_stats", + "train", + } + required_configs = {} + required_configs.update({stage: train_config for stage in pretrain_stages}) + required_configs.update({"infer": infer_config, "measure": measure_config}) + missing = [ + s + for s in stages_to_run + if s in required_configs and required_configs[s] is None + ] + if missing: + missing_str = ", ".join(missing) + raise ValueError( + f"Config not provided for stage(s): {missing_str}. " + "Use --train_config/--infer_config/--measure_config." + ) + run_stages( + system=system, + stages_to_run=stages_to_run, + dry_run=args.dry_run, + log=logger, + ) + + +if __name__ == "__main__": + parser = build_parser(stages=DEFAULT_STAGES) + args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) + + # Here you should replace `YourSystemClass` with the actual system class + # you want to use for your experiment. + from espnet3.systems.asr.system import ASRSystem # Example import + + main( + args=args, + system_cls=ASRSystem, + stages=DEFAULT_STAGES, + ) diff --git a/egs3/__init__.py b/egs3/__init__.py new file mode 100644 index 000000000000..e69de29bb2d1 diff --git a/egs3/mini_an4/__init__.py b/egs3/mini_an4/__init__.py new file mode 100644 index 000000000000..8b137891791f --- /dev/null +++ b/egs3/mini_an4/__init__.py @@ -0,0 +1 @@ + diff --git a/egs3/mini_an4/asr/__init__.py b/egs3/mini_an4/asr/__init__.py new file mode 100644 index 000000000000..8b137891791f --- /dev/null +++ b/egs3/mini_an4/asr/__init__.py @@ -0,0 +1 @@ + diff --git a/egs3/mini_an4/asr/conf/infer.yaml b/egs3/mini_an4/asr/conf/infer.yaml new file mode 100644 index 000000000000..93338319cf44 --- /dev/null +++ b/egs3/mini_an4/asr/conf/infer.yaml @@ -0,0 +1,37 @@ +# Mini AN4 ASR inference config for ESPnet3 integration tests. + +num_device: 1 +num_nodes: 1 + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: mini_an4_asr_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + test: + - name: test + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/test.tsv + +parallel: + env: local + n_workers: 1 + +model: + _target_: espnet2.bin.asr_inference.Speech2Text + asr_train_config: ${exp_dir}/config.yaml + asr_model_file: ${exp_dir}/last.ckpt + beam_size: 1 + ctc_weight: 0.3 + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/measure.yaml new file mode 100644 index 000000000000..395c01c1fbac --- /dev/null +++ b/egs3/mini_an4/asr/conf/measure.yaml @@ -0,0 +1,26 @@ +# Mini AN4 ASR scoring config for ESPnet3 integration tests. + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: mini_an4_asr_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + test: + - name: test + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/test.tsv + +metrics: + - metric: + _target_: espnet3.systems.asr.metrics.wer.WER + clean_types: + + - metric: + _target_: espnet3.systems.asr.metrics.cer.CER + clean_types: diff --git a/egs3/mini_an4/asr/conf/train.yaml b/egs3/mini_an4/asr/conf/train.yaml new file mode 100644 index 000000000000..d774ee7c2088 --- /dev/null +++ b/egs3/mini_an4/asr/conf/train.yaml @@ -0,0 +1,159 @@ +# Mini AN4 ASR training config for ESPnet3 integration tests. + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: mini_an4_asr_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 2 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.001 + weight_decay: 0.0 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 100 + +best_model_criterion: + - - valid/loss + - 1 + - min + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: transformer + encoder_conf: + output_size: 256 + attention_heads: 4 + linear_units: 2048 + num_blocks: 12 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + attention_dropout_rate: 0.0 + input_layer: conv2d + normalize_before: true + + decoder: transformer + decoder_conf: + attention_heads: 4 + linear_units: 2048 + num_blocks: 6 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + self_attention_dropout_rate: 0.0 + src_attention_dropout_rate: 0.0 + + normalize: utterance_mvn + normalize_conf: {} + + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/path.sh b/egs3/mini_an4/asr/path.sh new file mode 100644 index 000000000000..1456ecff938d --- /dev/null +++ b/egs3/mini_an4/asr/path.sh @@ -0,0 +1,6 @@ +#!/bin/bash + +export PYTHONPATH=../../../:../../TEMPLATE/asr:$(pwd):${PYTHONPATH} + +source ../../../tools/activate_python.sh +source ../../../tools/extra_path.sh diff --git a/egs3/mini_an4/asr/run.py b/egs3/mini_an4/asr/run.py new file mode 100644 index 000000000000..8a38549eda45 --- /dev/null +++ b/egs3/mini_an4/asr/run.py @@ -0,0 +1,20 @@ +from egs3.TEMPLATE.asr.run import ( + DEFAULT_STAGES, + build_parser, + main, + parse_cli_and_stage_args, +) +from espnet3.systems.asr.system import ASRSystem + +if __name__ == "__main__": + parser = build_parser( + stages=DEFAULT_STAGES, + add_arguments=None, + ) + args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) + + main( + args=args, + system_cls=ASRSystem, + stages=stages_to_run, + ) diff --git a/egs3/mini_an4/asr/run.sh b/egs3/mini_an4/asr/run.sh new file mode 100644 index 000000000000..254efce433cf --- /dev/null +++ b/egs3/mini_an4/asr/run.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +set -euo pipefail + +python=python3 + +. ./path.sh +. ../../../utils/parse_options.sh + +${python} run.py \ + --stages all \ + --train_config conf/train.yaml \ + --infer_config conf/infer.yaml \ + --measure_config conf/measure.yaml \ + "$@" diff --git a/egs3/mini_an4/asr/src/__init__.py b/egs3/mini_an4/asr/src/__init__.py new file mode 100644 index 000000000000..8b137891791f --- /dev/null +++ b/egs3/mini_an4/asr/src/__init__.py @@ -0,0 +1 @@ + diff --git a/egs3/mini_an4/asr/src/create_dataset.py b/egs3/mini_an4/asr/src/create_dataset.py new file mode 100644 index 000000000000..4d672b003aeb --- /dev/null +++ b/egs3/mini_an4/asr/src/create_dataset.py @@ -0,0 +1,152 @@ +"""Prepare the Mini AN4 dataset for ESPnet3 ASR recipes (simplified).""" + +from __future__ import annotations + +import argparse +import logging +import re +import shutil +import subprocess +from dataclasses import dataclass +from pathlib import Path +from typing import Iterable + +from espnet3.utils.download import extract_targz, setup_logger + +LOGGER = logging.getLogger(__name__) + +SPH_DIRS = {"train": "an4_clstk", "test": "an4test_clstk"} +TRANSCRIPTS = {"train": "an4_train.transcription", "test": "an4_test.transcription"} + +# " WORDS (a-b-c)" を想定 +LINE_RE = re.compile(r"^(?P.+?)\s+\((?P[^)]+)\)\s*$") + + +@dataclass(frozen=True) +class Entry: + utt_id: str + wav_path: Path + text: str + + +def is_gzip(path: Path) -> bool: + return path.is_file() and path.read_bytes()[:2] == b"\x1f\x8b" + + +def ensure_extracted(archive: Path, dataset_dir: Path, *, logger: logging.Logger) -> Path: + downloads_dir = dataset_dir / "downloads" + an4_root = downloads_dir / "an4" + if an4_root.exists(): + logger.info("Found existing downloads: %s", an4_root) + return an4_root + + if not archive.is_file(): + raise FileNotFoundError(f"Archive not found: {archive}") + if not is_gzip(archive): + raise RuntimeError(f"Archive is not gzip: {archive}") + + dataset_dir.mkdir(parents=True, exist_ok=True) + extract_targz(archive, dataset_dir, logger=logger) + + if not an4_root.exists(): + raise RuntimeError(f"AN4 root not found after extract: {an4_root}") + return an4_root + + +def parse_line(line: str) -> tuple[str, str, str]: + m = LINE_RE.match(line) + if not m: + raise ValueError(f"Malformed transcript line: {line}") + + words = m.group("words") + # transcript の を雑に剥がす（現状仕様踏襲） + if words.startswith(" "): + words = words[4:] + if words.endswith(" "): + words = words[:-5] + + src = m.group("src") # 例: abc-def-ghi + pre, mid, last = src.split("-") + utt_id = f"{mid}-{pre}-{last}" + return utt_id, src, words + + +def load_entries(an4_root: Path, split: str) -> list[tuple[str, str, str]]: + path = an4_root / "etc" / TRANSCRIPTS[split] + if not path.is_file(): + raise FileNotFoundError(f"Transcript not found: {path}") + + entries: list[tuple[str, str, str]] = [] + for line in path.read_text(encoding="utf-8").splitlines(): + line = line.strip() + if line: + entries.append(parse_line(line)) + + entries.sort(key=lambda x: x[0]) + return entries + + +def sph_to_wav(sph2pipe: str, sph: Path, wav: Path) -> None: + if wav.exists(): + return + wav.parent.mkdir(parents=True, exist_ok=True) + cmd = [sph2pipe, "-f", "wav", "-p", "-c", "1", str(sph)] + with wav.open("wb") as f: + subprocess.run(cmd, stdout=f, check=True) + + +def prepare_split(an4_root: Path, dataset_dir: Path, split: str, sph2pipe: str) -> list[Entry]: + wav_dir = dataset_dir / "wav" / split + sph_dir = an4_root / "wav" / SPH_DIRS[split] + + out: list[Entry] = [] + for utt_id, src, text in load_entries(an4_root, split): + mid = src.split("-")[1] + sph = sph_dir / mid / f"{src}.sph" + if not sph.is_file(): + raise FileNotFoundError(f"Missing sph file: {sph}") + + wav = (wav_dir / f"{utt_id}.wav").resolve() + sph_to_wav(sph2pipe, sph, wav) + out.append(Entry(utt_id=utt_id, wav_path=wav, text=text)) + return out + + +def write_manifest(path: Path, entries: Iterable[Entry]) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with path.open("w", encoding="utf-8") as f: + for e in entries: + f.write(f"{e.utt_id}\t{e.wav_path}\t{e.text}\n") + + +def create_dataset(dataset_dir: Path, *, archive_path: Path | None = None) -> None: + dataset_dir = Path(dataset_dir) + logger = setup_logger(name="mini_an4.create_dataset") + + archive = Path("../../../egs2/mini_an4/asr1/downloads.tar.gz") + an4_root = ensure_extracted(archive, dataset_dir, logger=logger) + + sph2pipe = shutil.which("sph2pipe") + if not sph2pipe: + raise RuntimeError("sph2pipe not found in PATH. Please install it.") + + train = prepare_split(an4_root, dataset_dir, "train", sph2pipe) + test = prepare_split(an4_root, dataset_dir, "test", sph2pipe) + + if len(train) < 2: + raise RuntimeError("Training data is too small (need >= 2 for dev+nodev).") + + manifest_dir = dataset_dir / "manifest" + write_manifest(manifest_dir / "train_dev.tsv", train[:1]) + write_manifest(manifest_dir / "train_nodev.tsv", train[1:]) + write_manifest(manifest_dir / "test.tsv", test) + + LOGGER.info("Prepared Mini AN4 manifests under %s", manifest_dir) + + +if __name__ == "__main__": + p = argparse.ArgumentParser(description="Prepare Mini AN4 dataset") + p.add_argument("--dataset_dir", type=Path, required=True) + p.add_argument("--archive_path", type=Path, default=None) + a = p.parse_args() + create_dataset(a.dataset_dir, archive_path=a.archive_path) diff --git a/egs3/mini_an4/asr/src/dataset.py b/egs3/mini_an4/asr/src/dataset.py new file mode 100644 index 000000000000..ed022deca65f --- /dev/null +++ b/egs3/mini_an4/asr/src/dataset.py @@ -0,0 +1,57 @@ +"""Dataset loader for Mini AN4 manifests.""" + +from __future__ import annotations + +from dataclasses import dataclass +from pathlib import Path +from typing import List + +import numpy as np +import soundfile as sf +from torch.utils.data import Dataset as TorchDataset + + +@dataclass(frozen=True) +class ManifestEntry: + utt_id: str + wav_path: Path + text: str + + +def _read_manifest(manifest_path: Path) -> List[ManifestEntry]: + entries: List[ManifestEntry] = [] + with manifest_path.open("r", encoding="utf-8") as f: + for line in f: + line = line.strip() + if not line: + continue + utt_id, wav_path, text = line.split("\t", maxsplit=2) + entries.append( + ManifestEntry( + utt_id=utt_id, + wav_path=Path(wav_path), + text=text, + ) + ) + if not entries: + raise RuntimeError(f"Manifest is empty: {manifest_path}") + return entries + + +class MiniAN4Dataset(TorchDataset): + def __init__(self, manifest_path: str | Path) -> None: + manifest_path = Path(manifest_path) + if not manifest_path.is_file(): + raise FileNotFoundError(f"Manifest not found: {manifest_path}") + self._entries = _read_manifest(manifest_path) + + def __len__(self) -> int: + return len(self._entries) + + def __getitem__(self, idx: int): + entry = self._entries[int(idx)] + array, _sr = sf.read(str(entry.wav_path)) + return { + "speech": np.asarray(array, dtype=np.float32), + "text": entry.text, + } diff --git a/egs3/mini_an4/asr/src/tokenizer.py b/egs3/mini_an4/asr/src/tokenizer.py new file mode 100644 index 000000000000..9f7306852966 --- /dev/null +++ b/egs3/mini_an4/asr/src/tokenizer.py @@ -0,0 +1,25 @@ +from __future__ import annotations + +from pathlib import Path +from typing import List + + +def gather_training_text(manifest_path: Path) -> List[str]: + manifest_path = Path(manifest_path) + if not manifest_path.is_file(): + raise FileNotFoundError(f"Manifest not found: {manifest_path}") + + texts: list[str] = [] + with manifest_path.open("r", encoding="utf-8") as f: + for line in f: + line = line.strip() + if not line: + continue + parts = line.split("\t", maxsplit=2) + if len(parts) != 3: + raise ValueError(f"Invalid manifest line: {line}") + texts.append(parts[2]) + + if not texts: + raise RuntimeError(f"No text found in manifest: {manifest_path}") + return texts From 374c10dca3c8c0d209b2a394ea7ff206115d6c3d Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 26 Dec 2025 14:09:48 -0500 Subject: [PATCH 02/67] Added jiwer for scoring stage --- pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/pyproject.toml b/pyproject.toml index c261c7f3a844..e79980244286 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -78,6 +78,7 @@ asr = [ "ctc-segmentation @ git+https://github.com/espnet/ctc-segmentation.git@9b9ea1d", "editdistance", "opt_einsum", + "jiwer", ] tts = [ From b205eb65ffdb68dba6c27f82757f90d3f2abd0de Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 26 Dec 2025 14:13:42 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zW**rJD9@qZmkH(oRP>@V3REQ)%v=fisBapezYB@lojQXVvx1lw`JNrI$mO^?y29yVass3zQlRhVnQ%N_jeEC6oQ_L z>9N^Y7Si81@JG?Ln%P6mp}z7Kqy3;N0{z*WdJ1;*p(6tG`^(hGVtyWvZtQi8`bJdgVgEe=-9IRcvT1?lIqVUJYA75+vp#w+GqQ*n>Cbnt`lBN{>WF?pPrCho z3MOMI8i9#*g3f~S2m7v6E246Mj_dvT_68jx_$%4;pz{KZvXbsy>I}3dRQ>s%$5F>H znvU$T#U9VpnnimCtp2endc3kVGvy#w#NQ;m-+9**`%RR zo*ubmyRhlUL}ca+=I2W&P1we$XJBW5f?D7CPn;HA|EM!jJ{H82h!J*P$Nx*+zkkTZ zXRU(yIWtFzD#^}Tn9|VE&gNn2H$l;#l%s0{m35(N7X6N#zie60mqx}G`Z$>-lJSp; zGekdH9$U4h_p-Cdz9InaUn-yIyB@M3C2BQ!P5-JaA(xst=ugh+|Az}%4>o(U#SWWR zghu2YsBy^t@2bf0G0+CuKpSWSZJ-Ubfi} Date: Fri, 26 Dec 2025 19:25:02 +0000 Subject: [PATCH 04/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- egs3/mini_an4/__init__.py | 1 - egs3/mini_an4/asr/__init__.py | 1 - egs3/mini_an4/asr/src/__init__.py | 1 - egs3/mini_an4/asr/src/create_dataset.py | 8 ++++++-- 4 files changed, 6 insertions(+), 5 deletions(-) diff --git a/egs3/mini_an4/__init__.py b/egs3/mini_an4/__init__.py index 8b137891791f..e69de29bb2d1 100644 --- a/egs3/mini_an4/__init__.py +++ b/egs3/mini_an4/__init__.py @@ -1 +0,0 @@ - diff --git a/egs3/mini_an4/asr/__init__.py b/egs3/mini_an4/asr/__init__.py index 8b137891791f..e69de29bb2d1 100644 --- a/egs3/mini_an4/asr/__init__.py +++ b/egs3/mini_an4/asr/__init__.py @@ -1 +0,0 @@ - diff --git a/egs3/mini_an4/asr/src/__init__.py b/egs3/mini_an4/asr/src/__init__.py index 8b137891791f..e69de29bb2d1 100644 --- a/egs3/mini_an4/asr/src/__init__.py +++ b/egs3/mini_an4/asr/src/__init__.py @@ -1 +0,0 @@ - diff --git a/egs3/mini_an4/asr/src/create_dataset.py b/egs3/mini_an4/asr/src/create_dataset.py index 4d672b003aeb..386c5688a658 100644 --- a/egs3/mini_an4/asr/src/create_dataset.py +++ b/egs3/mini_an4/asr/src/create_dataset.py @@ -33,7 +33,9 @@ def is_gzip(path: Path) -> bool: return path.is_file() and path.read_bytes()[:2] == b"\x1f\x8b" -def ensure_extracted(archive: Path, dataset_dir: Path, *, logger: logging.Logger) -> Path: +def ensure_extracted( + archive: Path, dataset_dir: Path, *, logger: logging.Logger +) -> Path: downloads_dir = dataset_dir / "downloads" an4_root = downloads_dir / "an4" if an4_root.exists(): @@ -95,7 +97,9 @@ def sph_to_wav(sph2pipe: str, sph: Path, wav: Path) -> None: subprocess.run(cmd, stdout=f, check=True) -def prepare_split(an4_root: Path, dataset_dir: Path, split: str, sph2pipe: str) -> list[Entry]: +def prepare_split( + an4_root: Path, dataset_dir: Path, split: str, sph2pipe: str +) -> list[Entry]: wav_dir = dataset_dir / "wav" / split sph_dir = an4_root / "wav" / SPH_DIRS[split] From d42994af127660dd147661c9fdb2c4603b64c2d1 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 8 Jan 2026 17:18:59 -0500 Subject: [PATCH 05/67] Bug fix - Assume hypothesis to be "" when hypothesis is blank --- espnet3/utils/scp_utils.py | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/espnet3/utils/scp_utils.py b/espnet3/utils/scp_utils.py index df0ea03a3930..b1b50ba238b4 100644 --- a/espnet3/utils/scp_utils.py +++ b/espnet3/utils/scp_utils.py @@ -8,10 +8,15 @@ def read_scp(scp_file): """Read an SCP file into a key/value dictionary.""" with open(scp_file, "r") as f: lines = [line.strip() for line in f.readlines()] - return { - line.split(maxsplit=1)[0].strip(): line.split(maxsplit=1)[1].strip() - for line in lines - } + parsed = {} + for line in lines: + if not line: + continue + parts = line.split(maxsplit=1) + key = parts[0].strip() + value = parts[1].strip() if len(parts) > 1 else "" + parsed[key] = value + return parsed def get_class_path(obj) -> str: From e649581628c3a7d875d2e1ee9c795b7595d4fcb7 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 8 Jan 2026 17:20:09 -0500 Subject: [PATCH 06/67] Add validation-based lr scheduler such as ReduceOnPlateau - Previously we asked developer to create a user-defined modle, but I supported as a default. - Userd can set `val_scheduler_criterion` as espnet2 to use this function. --- espnet3/components/modeling/model.py | 27 ++++++- .../test_model_with_optim_scheduler.py | 79 ++++++++----------- 2 files changed, 58 insertions(+), 48 deletions(-) diff --git a/espnet3/components/modeling/model.py b/espnet3/components/modeling/model.py index 1ffdce77850e..1ae3d1f42a39 100644 --- a/espnet3/components/modeling/model.py +++ b/espnet3/components/modeling/model.py @@ -242,6 +242,14 @@ def configure_optimizers(self): AssertionError: If configuration rules are violated. ValueError: If neither optimizer configuration is provided. """ + def _get_val_scheduler_monitor(): + criterion = getattr(self.config, "val_scheduler_criterion", None) + if criterion is None: + return None + if not isinstance(criterion, str): + raise ValueError("val_scheduler_criterion must be a string like 'valid/loss'") + return criterion + if getattr(self.config, "optim", None) and getattr( self.config, "scheduler", None ): @@ -344,12 +352,23 @@ def configure_optimizers(self): "Must specify either `optim` or `optims` and `scheduler` or" "`schedulers`" ) + + def _build_lr_scheduler_config(sch): + config = {"scheduler": sch, "interval": "step"} + monitor = _get_val_scheduler_monitor() + if monitor is not None: + config["interval"] = "epoch" + config["monitor"] = monitor + return config + + if isinstance(scheduler, list): + lr_scheduler = [_build_lr_scheduler_config(sch) for sch in scheduler] + else: + lr_scheduler = _build_lr_scheduler_config(scheduler) + return { "optimizer": optimizer, - "lr_scheduler": { - "scheduler": scheduler, - "interval": "step", # assuming lr scheduler is updated per step - }, + "lr_scheduler": lr_scheduler, } def train_dataloader(self): diff --git a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py index 4d9ea545a2e1..35ede5cb1dbb 100644 --- a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py +++ b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py @@ -16,6 +16,8 @@ # | test_multiple_optims_and_schedulers| Validates multiple optimizers and schedulers with param-based mapping | # noqa: E501 # | test_custom_scheduler_interval | Ensures scheduler interval is correctly set to "step" | # noqa: E501 # | test_reduce_on_plateau_with_config_adam | Tests ReduceLROnPlateau scheduler integration with manual stepping | # noqa: E501 +# | test_reduce_on_plateau_monitor_from_config | Ensures ReduceLROnPlateau gets monitor key from config | # noqa: E501 +# | test_val_scheduler_criterion_sets_epoch | Ensures val_scheduler_criterion switches to epoch | # noqa: E501 # # Invalid Configuration Tests # | Test Name | Description | # noqa: E501 @@ -38,33 +40,6 @@ def __init__(self): self.linear2 = nn.Linear(10, 5) -class ReduceLROnPlateauModel(LitESPnetModel): - def __init__(self, model, config): - super().__init__(model, config) - self.favorite_metric = 1.0 - - def configure_optimizers(self): - optimizer = torch.optim.Adam(self.parameters(), lr=0.01) - self.scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau( - optimizer, patience=2, factor=0.5 - ) - return optimizer - - def optimizer_step( - self, - epoch_nb, - batch_nb, - optimizer, - ): - if batch_nb == 0: - self.scheduler.step(self.favorite_metric) - print( - f"metric: {self.favorite_metric}, best: {self.scheduler.best}, " - f"num_bad_epochs: {self.scheduler.num_bad_epochs}" - ) - optimizer.step() - optimizer.zero_grad() - # ========== VALID CASES ========== @@ -131,7 +106,8 @@ def test_multiple_optims_and_schedulers(): model = LitESPnetModel(DummyModel(), config) out = model.configure_optimizers() assert hasattr(out["optimizer"], "optimizers") # HybridOptim - assert isinstance(out["lr_scheduler"]["scheduler"], list) + assert isinstance(out["lr_scheduler"], list) + assert all("scheduler" in item for item in out["lr_scheduler"]) def test_custom_scheduler_interval(): @@ -156,7 +132,7 @@ def test_custom_scheduler_interval(): assert out["lr_scheduler"]["interval"] == "step" -def test_reduce_on_plateau_with_config_adam(): +def test_reduce_on_plateau_monitor_from_config(): config = OmegaConf.create( { "optim": {"_target_": "torch.optim.Adam", "lr": 0.01}, @@ -165,6 +141,7 @@ def test_reduce_on_plateau_with_config_adam(): "patience": 1, "factor": 0.5, }, + "val_scheduler_criterion": "valid/loss", "dataset": { "_target_": "espnet3.components.data.data_organizer.DataOrganizer", "train": [], @@ -175,21 +152,35 @@ def test_reduce_on_plateau_with_config_adam(): } ) - model = DummyModel() - lit_model = ReduceLROnPlateauModel(model, config) - optimizer = lit_model.configure_optimizers() - - # mimic training loop - for epoch in range(3): - for batch in range(1): # we step scheduler at batch 0 - lit_model.favorite_metric = ( - 1.0 - 0.1 * epoch - ) # simulate val_loss decreasing - lit_model.optimizer_step( - epoch_nb=epoch, - batch_nb=batch, - optimizer=optimizer, - ) + model = LitESPnetModel(DummyModel(), config) + out = model.configure_optimizers() + assert out["lr_scheduler"]["interval"] == "epoch" + assert out["lr_scheduler"]["monitor"] == "valid/loss" + + +def test_val_scheduler_criterion_sets_epoch(): + config = OmegaConf.create( + { + "optim": {"_target_": "torch.optim.Adam", "lr": 0.01}, + "scheduler": { + "_target_": "torch.optim.lr_scheduler.StepLR", + "step_size": 5, + }, + "val_scheduler_criterion": "valid/acc", + "dataset": { + "_target_": "espnet3.components.data.data_organizer.DataOrganizer", + "train": [], + "valid": [], + }, + "dataloader": {"train": {}, "valid": {}}, + "num_device": 1, + } + ) + + model = LitESPnetModel(DummyModel(), config) + out = model.configure_optimizers() + assert out["lr_scheduler"]["interval"] == "epoch" + assert out["lr_scheduler"]["monitor"] == "valid/acc" # ========== INVALID CASES ========== From 7fae474de17d0a228f7ebb269ada1103e8014e6c Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 8 Jan 2026 18:53:32 -0500 Subject: [PATCH 07/67] Skip bulding tokenizer when exists --- espnet3/systems/asr/system.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index e9afb5e6aa89..7dc8aa8de930 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -86,16 +86,19 @@ def train(self, *args, **kwargs): raise RuntimeError("train_config.dataset_dir must be set for training.") # Train tokenizer if not trained previously - tokenizer_path = ( - Path(self.train_config.tokenizer.save_path) - / f"{self.train_config.tokenizer.model_type}.model" - ) - if not tokenizer_path.exists(): + if not self._tokenizer_exists(): self.train_tokenizer() # Proceed with standard training return super().train() + def _tokenizer_exists(self) -> bool: + tokenizer_cfg = self.train_config.tokenizer + output_path = Path(tokenizer_cfg.save_path) + model = output_path / f"{tokenizer_cfg.model_type}.model" + vocab = output_path / f"{tokenizer_cfg.model_type}.vocab" + return model.exists() and vocab.exists() + def train_tokenizer(self, *args, **kwargs): """Train a SentencePiece tokenizer based on configured text. @@ -107,6 +110,10 @@ def train_tokenizer(self, *args, **kwargs): RuntimeError: If required tokenizer config is missing or invalid. """ self._reject_stage_args("train_tokenizer", args, kwargs) + + if self._tokenizer_exists(): + logger.info("Tokenizer already exists. Skipping train_tokenizer().") + return start = time.perf_counter() output_path = Path(self.train_config.tokenizer.save_path) output_path.mkdir(parents=True, exist_ok=True) From eb8762db0d24ce4b31e0a2daf9f02d50a1975541 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:07:43 -0500 Subject: [PATCH 08/67] Some bug fix for config loading - supported train/valid switching for preprocessor - Add new default resolver to load external config file --- espnet3/components/modeling/model.py | 6 ++++ espnet3/utils/config.py | 44 ++++++++++++++++++++++++++++ espnet3/utils/task.py | 13 +++++--- 3 files changed, 59 insertions(+), 4 deletions(-) diff --git a/espnet3/components/modeling/model.py b/espnet3/components/modeling/model.py index 1ae3d1f42a39..ca4b1766a867 100644 --- a/espnet3/components/modeling/model.py +++ b/espnet3/components/modeling/model.py @@ -435,6 +435,12 @@ def collect_stats(self): ) for mode in ["train", "valid"]: + print(dataset_config) + if mode == "train": + dataset_config.preprocessor.train = True + else: + dataset_config.preprocessor.train = False + collect_stats( model_config=OmegaConf.to_container(self.config.model, resolve=True), dataset_config=dataset_config, diff --git a/espnet3/utils/config.py b/espnet3/utils/config.py index 3723a8a887ac..c7a0b70444c1 100644 --- a/espnet3/utils/config.py +++ b/espnet3/utils/config.py @@ -32,8 +32,40 @@ def load_line(path): raise +def load_yaml(path, key=None): + """Load a YAML file and optionally return a nested key. + + This resolver is intended for pulling a single value from another config, + e.g., `${load_yaml:conf/train.yaml,exp_tag}`. + + Args: + path (str or Path): Path to the YAML file. + key (str, optional): Dot-delimited key to select. + + Returns: + Any: The selected value or the full config if key is None. + """ + try: + cfg = OmegaConf.load(path) + except FileNotFoundError: + logging.error(f"File not found: {path}") + raise + except PermissionError: + logging.error(f"Permission denied when accessing file: {path}") + raise + + if key is None or str(key).strip() == "": + return cfg + + value = OmegaConf.select(cfg, str(key), default=None) + if value is None: + raise KeyError(f"Key not found in YAML: {key}") + return value + + OMEGACONF_ESPNET3_RESOLVER = { "load_line": load_line, + "load_yaml": load_yaml, } for name, resolver in OMEGACONF_ESPNET3_RESOLVER.items(): OmegaConf.register_new_resolver(name, resolver) @@ -121,9 +153,21 @@ def load_config_with_defaults(path: str) -> OmegaConf: if "defaults" in final_cfg: del final_cfg["defaults"] + _ensure_target_convert_all(final_cfg) return final_cfg +def _ensure_target_convert_all(cfg) -> None: + if isinstance(cfg, DictConfig): + if "_target_" in cfg: + cfg["_convert_"] = "all" + for value in cfg.values(): + _ensure_target_convert_all(value) + elif isinstance(cfg, ListConfig): + for value in cfg: + _ensure_target_convert_all(value) + + def _build_config_path(base_path: Path, entry: str) -> Path: entry_path = Path(entry) if entry_path.suffix and entry_path.suffix != ".yaml": diff --git a/espnet3/utils/task.py b/espnet3/utils/task.py index d2cef2e1351d..4bc22e4c478f 100644 --- a/espnet3/utils/task.py +++ b/espnet3/utils/task.py @@ -35,7 +35,7 @@ def get_espnet_model(task: str, config: Union[Dict, DictConfig]) -> AbsESPnetMod finally: sys.argv = original_argv - if isinstance(config, OmegaConf): + if OmegaConf.is_config(config): default_config.update(OmegaConf.to_container(config, resolve=True)) else: default_config.update(config) @@ -56,7 +56,11 @@ def save_espnet_config( default_config = ez_task.get_default_config() sys.argv = original_argv - resolved_config = OmegaConf.to_container(config, resolve=True) + resolved_config = ( + OmegaConf.to_container(config, resolve=True) + if OmegaConf.is_config(config) + else config + ) # set model config at the root level model_config = resolved_config.pop("model") @@ -65,8 +69,9 @@ def save_espnet_config( default_config.update(model_config) # set the preprocessor config at the root level - if config.dataset is not None and "preprocessor" in config.dataset: - preprocess_config = resolved_config["dataset"].pop("preprocessor") + dataset_config = resolved_config.get("dataset") + if dataset_config is not None and "preprocessor" in dataset_config: + preprocess_config = dataset_config.pop("preprocessor") if "_target_" in preprocess_config: preprocess_config.pop("_target_") default_config.update(preprocess_config) From 4d12f16c3fa792755360d646928f3d3cd43b5009 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:09:28 -0500 Subject: [PATCH 09/67] Add transducer system, task, and inference runner --- espnet3/systems/asr/inference.py | 37 ++ espnet3/systems/asr/transducer_system.py | 90 +++++ espnet3/systems/asr/transducer_task.py | 431 +++++++++++++++++++++++ 3 files changed, 558 insertions(+) create mode 100644 espnet3/systems/asr/transducer_system.py create mode 100644 espnet3/systems/asr/transducer_task.py diff --git a/espnet3/systems/asr/inference.py b/espnet3/systems/asr/inference.py index e08a86a168cb..ad92bd76967f 100644 --- a/espnet3/systems/asr/inference.py +++ b/espnet3/systems/asr/inference.py @@ -108,3 +108,40 @@ def forward(idx, dataset=None, model=None, **kwargs): hyp = model(speech)[0][0] ref = data["text"] return {"idx": idx, "hyp": hyp, "ref": ref} + + + +class TransducerInferenceRunner(AbsInferenceRunner): + """Inference runner that produces hypotheses and references. + + This runner expects dataset items to contain ``speech`` and ``text`` + fields and returns decoded hypotheses alongside references. + + It is designed around ``espnet3.systems.asr.task.ASRTask`` outputs; when + using a custom model outside that task, implement your own inference + runner and decoding logic. + """ + + @staticmethod + def forward(idx, dataset=None, model=None, **kwargs): + """Run inference for one dataset item and return hypothesis/ref. + + Args: + idx: Integer index into the dataset. + dataset: Dataset providing speech/text entries. + model: ASR inference model callable on speech input. + **kwargs: Unused keyword arguments reserved for compatibility. + + Returns: + Dict with index, hypothesis string, and reference string. + + Raises: + AssertionError: If required fields are missing from dataset items. + """ + data = dataset[idx] + assert "speech" in data, "ASR inference requires 'speech' in dataset item." + assert "text" in data, "ASR inference requires 'text' in dataset item." + speech = data["speech"] + hyp = model(speech)[0] + ref = data["text"] + return {"idx": idx, "hyp": hyp, "ref": ref} diff --git a/espnet3/systems/asr/transducer_system.py b/espnet3/systems/asr/transducer_system.py new file mode 100644 index 000000000000..7d7dadd525ab --- /dev/null +++ b/espnet3/systems/asr/transducer_system.py @@ -0,0 +1,90 @@ +"""ASR system implementation and tokenizer training helpers. + +This module adds ASR-specific stages on top of the base system, including +tokenizer training and dataset creation hooks. +""" + +import logging +import time +from pathlib import Path + +from omegaconf import DictConfig +from espnet3.parallel.parallel import set_parallel +from espnet3.systems.asr.inference import InferenceProvider, TransducerInferenceRunner +from espnet3.systems.asr.system import ASRSystem +from espnet3.systems.base.inference import (_collect_scp_lines, _flatten_results) +from espnet3.systems.base.inference_runner import AbsInferenceRunner + +logger = logging.getLogger(__name__) + + +class ASRTransducerSystem(ASRSystem): + """ASR Transducer-specific system. + + This system adds: + - Tokenizer training inside train() + """ + def infer(self, *args, **kwargs): + """Run inference on the configured datasets.""" + self._reject_stage_args("infer", args, kwargs) + logger.info( + "Inference start | decode_dir=%s", + getattr(self.infer_config, "decode_dir", None), + ) + return inference(self.infer_config) + + +def inference(config: DictConfig): + """Run inference over all configured test sets and write SCP outputs. + + Args: + config: Hydra/omegaconf configuration with dataset and decode settings. + """ + start = time.perf_counter() + set_parallel(config.parallel) + + test_sets = [test_set.name for test_set in config.dataset.test] + assert len(test_sets) > 0, "No test set found in dataset" + assert len(test_sets) == len(set(test_sets)), "Duplicate test key found." + + logger.info( + "Starting inference | decode_dir=%s test_sets=%s", + getattr(config, "decode_dir", None), + test_sets, + ) + + for test_name in test_sets: + logger.info("===> Processing test set: %s", test_name) + config.test_set = test_name + provider = InferenceProvider(config) + runner = TransducerInferenceRunner(provider=provider, async_mode=False) + if not isinstance(runner, AbsInferenceRunner): + raise TypeError( + f"{type(runner).__name__} must inherit from AbsInferenceRunner" + ) + dataset_length = len(provider.build_dataset(config)) + logger.info("===> Processing %d samples..", dataset_length) + out = runner(list(range(dataset_length))) + if out is None: + raise RuntimeError("Async inference is not supported in this entrypoint.") + results = _flatten_results(out) + scp_lines = _collect_scp_lines( + results, + idx_key=runner.idx_key, + hyp_keys=runner.hyp_key, + ref_keys=runner.ref_key, + ) + + # create scp files + output_dir = Path(config.decode_dir) / test_name + output_dir.mkdir(parents=True, exist_ok=True) + for key, lines in scp_lines.items(): + with open(output_dir / f"{key}.scp", "w", encoding="utf-8") as f: + f.write("\n".join(lines)) + logger.info( + "Finished test set %s | outputs=%s", + test_name, + output_dir, + ) + + logger.info("Inference finished in %.2fs", time.perf_counter() - start) diff --git a/espnet3/systems/asr/transducer_task.py b/espnet3/systems/asr/transducer_task.py new file mode 100644 index 000000000000..017fcd5ef58f --- /dev/null +++ b/espnet3/systems/asr/transducer_task.py @@ -0,0 +1,431 @@ +"""ASR Transducer Task.""" + +import argparse +import logging +from typing import Callable, Collection, Dict, List, Optional, Tuple + +import numpy as np +import torch +from typeguard import typechecked + +from espnet2.asr.frontend.abs_frontend import AbsFrontend +from espnet2.asr.frontend.default import DefaultFrontend +from espnet2.asr.frontend.windowing import SlidingWindow +from espnet2.asr.specaug.abs_specaug import AbsSpecAug +from espnet2.asr.specaug.specaug import SpecAug +from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder +from espnet2.asr_transducer.decoder.mega_decoder import MEGADecoder +from espnet2.asr_transducer.decoder.rnn_decoder import RNNDecoder +from espnet2.asr_transducer.decoder.rwkv_decoder import RWKVDecoder +from espnet2.asr_transducer.decoder.stateless_decoder import StatelessDecoder +from espnet2.asr_transducer.encoder.encoder import Encoder +from espnet2.asr_transducer.espnet_transducer_model import ESPnetASRTransducerModel +from espnet2.asr_transducer.joint_network import JointNetwork +from espnet2.layers.abs_normalize import AbsNormalize +from espnet2.layers.global_mvn import GlobalMVN +from espnet2.layers.utterance_mvn import UtteranceMVN +from espnet2.tasks.abs_task import AbsTask +from espnet2.text.phoneme_tokenizer import g2p_choices +from espnet2.train.class_choices import ClassChoices +from espnet2.train.collate_fn import CommonCollateFn +from espnet2.train.preprocessor import CommonPreprocessor +from espnet2.train.trainer import Trainer +from espnet2.utils.get_default_kwargs import get_default_kwargs +from espnet2.utils.nested_dict_action import NestedDictAction +from espnet2.utils.types import float_or_none, int_or_none, str2bool, str_or_none + +frontend_choices = ClassChoices( + name="frontend", + classes=dict( + default=DefaultFrontend, + sliding_window=SlidingWindow, + ), + type_check=AbsFrontend, + default="default", +) +specaug_choices = ClassChoices( + "specaug", + classes=dict( + specaug=SpecAug, + ), + type_check=AbsSpecAug, + default=None, + optional=True, +) +normalize_choices = ClassChoices( + "normalize", + classes=dict( + global_mvn=GlobalMVN, + utterance_mvn=UtteranceMVN, + ), + type_check=AbsNormalize, + default="utterance_mvn", + optional=True, +) +decoder_choices = ClassChoices( + "decoder", + classes=dict( + mega=MEGADecoder, + rnn=RNNDecoder, + rwkv=RWKVDecoder, + stateless=StatelessDecoder, + ), + type_check=AbsDecoder, + default="rnn", +) + + +class ASRTransducerTask(AbsTask): + """ASR Transducer Task definition.""" + + num_optimizers: int = 1 + + class_choices_list = [ + frontend_choices, + specaug_choices, + normalize_choices, + decoder_choices, + ] + + trainer = Trainer + + @classmethod + def add_task_arguments(cls, parser: argparse.ArgumentParser): + """Add Transducer task arguments. + + Args: + cls: ASRTransducerTask object. + parser: Transducer arguments parser. + + """ + group = parser.add_argument_group(description="Task related.") + + required = parser.get_default("required") + required += ["token_list"] + + group.add_argument( + "--token_list", + type=str_or_none, + default=None, + help="Integer-string mapper for tokens.", + ) + group.add_argument( + "--input_size", + type=int_or_none, + default=None, + help="The number of dimensions for input features.", + ) + group.add_argument( + "--init", + type=str_or_none, + default=None, + help="Type of model initialization to use.", + ) + group.add_argument( + "--model_conf", + action=NestedDictAction, + default=get_default_kwargs(ESPnetASRTransducerModel), + help="The keyword arguments for the model class.", + ) + group.add_argument( + "--encoder_conf", + action=NestedDictAction, + default={}, + help="The keyword arguments for the encoder class.", + ) + group.add_argument( + "--joint_network_conf", + action=NestedDictAction, + default={}, + help="The keyword arguments for the joint network class.", + ) + + group = parser.add_argument_group(description="Preprocess related.") + + group.add_argument( + "--use_preprocessor", + type=str2bool, + default=True, + help="Whether to apply preprocessing to input data.", + ) + group.add_argument( + "--token_type", + type=str, + default="bpe", + choices=["bpe", "char", "word", "phn"], + help="The type of tokens to use during tokenization.", + ) + group.add_argument( + "--bpemodel", + type=str_or_none, + default=None, + help="The path of the sentencepiece model.", + ) + group.add_argument( + "--non_linguistic_symbols", + type=str_or_none, + help="The 'non_linguistic_symbols' file path.", + ) + group.add_argument( + "--cleaner", + type=str_or_none, + choices=[None, "tacotron", "jaconv", "vietnamese"], + default=None, + help="Text cleaner to use.", + ) + group.add_argument( + "--g2p", + type=str_or_none, + choices=g2p_choices, + default=None, + help="g2p method to use if --token_type=phn.", + ) + group.add_argument( + "--speech_volume_normalize", + type=float_or_none, + default=None, + help="Normalization value for maximum amplitude scaling.", + ) + group.add_argument( + "--rir_scp", + type=str_or_none, + default=None, + help="The RIR SCP file path.", + ) + group.add_argument( + "--rir_apply_prob", + type=float, + default=1.0, + help="The probability of the applied RIR convolution.", + ) + group.add_argument( + "--noise_scp", + type=str_or_none, + default=None, + help="The path of noise SCP file.", + ) + group.add_argument( + "--noise_apply_prob", + type=float, + default=1.0, + help="The probability of the applied noise addition.", + ) + group.add_argument( + "--noise_db_range", + type=str, + default="13_15", + help="The range of the noise decibel level.", + ) + + for class_choices in cls.class_choices_list: + # Append -- and --_conf. + # e.g. --decoder and --decoder_conf + class_choices.add_arguments(group) + + @classmethod + @typechecked + def build_collate_fn(cls, args: argparse.Namespace, train: bool) -> Callable[ + [Collection[Tuple[str, Dict[str, np.ndarray]]]], + Tuple[List[str], Dict[str, torch.Tensor]], + ]: + """Build collate function. + + Args: + cls: ASRTransducerTask object. + args: Task arguments. + train: Training mode. + + Return: + : Callable collate function. + + """ + + return CommonCollateFn(float_pad_value=0.0, int_pad_value=-1) + + @classmethod + @typechecked + def build_preprocess_fn( + cls, args: argparse.Namespace, train: bool + ) -> Optional[Callable[[str, Dict[str, np.array]], Dict[str, np.ndarray]]]: + """Build pre-processing function. + + Args: + cls: ASRTransducerTask object. + args: Task arguments. + train: Training mode. + + Return: + : Callable pre-processing function. + + """ + + if args.use_preprocessor: + retval = CommonPreprocessor( + train=train, + token_type=args.token_type, + token_list=args.token_list, + bpemodel=args.bpemodel, + non_linguistic_symbols=args.non_linguistic_symbols, + text_cleaner=args.cleaner, + g2p_type=args.g2p, + rir_scp=args.rir_scp if hasattr(args, "rir_scp") else None, + rir_apply_prob=( + args.rir_apply_prob if hasattr(args, "rir_apply_prob") else 1.0 + ), + noise_scp=args.noise_scp if hasattr(args, "noise_scp") else None, + noise_apply_prob=( + args.noise_apply_prob if hasattr(args, "noise_apply_prob") else 1.0 + ), + noise_db_range=( + args.noise_db_range if hasattr(args, "noise_db_range") else "13_15" + ), + speech_volume_normalize=( + args.speech_volume_normalize if hasattr(args, "rir_scp") else None + ), + ) + else: + retval = None + + return retval + + @classmethod + def required_data_names( + cls, train: bool = True, inference: bool = False + ) -> Tuple[str, ...]: + """Required data depending on task mode. + + Args: + cls: ASRTransducerTask object. + train: Training mode. + inference: Inference mode. + + Return: + retval: Required task data. + + """ + if not inference: + retval = ("speech", "text") + else: + retval = ("speech",) + + return retval + + @classmethod + def optional_data_names( + cls, train: bool = True, inference: bool = False + ) -> Tuple[str, ...]: + """Optional data depending on task mode. + + Args: + cls: ASRTransducerTask object. + train: Training mode. + inference: Inference mode. + + Return: + retval: Optional task data. + + """ + retval = () + + return retval + + @classmethod + @typechecked + def build_model(cls, args: argparse.Namespace) -> ESPnetASRTransducerModel: + """Required data depending on task mode. + + Args: + cls: ASRTransducerTask object. + args: Task arguments. + + Return: + model: ASR Transducer model. + + """ + + if isinstance(args.token_list, str): + with open(args.token_list, encoding="utf-8") as f: + token_list = [line.rstrip() for line in f] + + # Overwriting token_list to keep it as "portable". + args.token_list = list(token_list) + elif isinstance(args.token_list, (tuple, list)): + token_list = list(args.token_list) + else: + raise RuntimeError("token_list must be str or list") + vocab_size = len(token_list) + + if hasattr(args, "scheduler_conf"): + args.model_conf["warmup_steps"] = args.scheduler_conf.get( + "warmup_steps", 25000 + ) + + logging.info(f"Vocabulary size: {vocab_size}") + + # 1. frontend + if args.input_size is None: + # Extract features in the model + frontend_class = frontend_choices.get_class(args.frontend) + frontend = frontend_class(**args.frontend_conf) + input_size = frontend.output_size() + else: + # Give features from data-loader + frontend = None + input_size = args.input_size + + # 2. Data augmentation for spectrogram + if args.specaug is not None: + specaug_class = specaug_choices.get_class(args.specaug) + specaug = specaug_class(**args.specaug_conf) + else: + specaug = None + + # 3. Normalization layer + if args.normalize is not None: + normalize_class = normalize_choices.get_class(args.normalize) + normalize = normalize_class(**args.normalize_conf) + else: + normalize = None + + # 4. Encoder + encoder = Encoder(input_size, **args.encoder_conf) + encoder_output_size = encoder.output_size + + # 5. Decoder + decoder_class = decoder_choices.get_class(args.decoder) + + decoder = decoder_class( + vocab_size, + **args.decoder_conf, + ) + decoder_output_size = decoder.output_size + + # 6. Joint Network + joint_network = JointNetwork( + vocab_size, + encoder_output_size, + decoder_output_size, + **args.joint_network_conf, + ) + + # 7. Build model + model = ESPnetASRTransducerModel( + vocab_size=vocab_size, + token_list=token_list, + frontend=frontend, + specaug=specaug, + normalize=normalize, + encoder=encoder, + decoder=decoder, + joint_network=joint_network, + **args.model_conf, + ) + + # 8. Initialize model + if args.init is not None: + raise NotImplementedError( + "Currently not supported.", + "Initialization part will be reworked in a short future.", + ) + + return model From e8d0d974fda2378c38c680f991ce1dfe56c856b6 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:12:12 -0500 Subject: [PATCH 10/67] Add configs for integration test --- egs3/mini_an4/asr/conf/infer.yaml | 2 +- egs3/mini_an4/asr/conf/infer_transducer.yaml | 36 ++++ egs3/mini_an4/asr/conf/measure.yaml | 2 +- .../conf/train_asr_rnn_data_aug_debug.yaml | 166 ++++++++++++++++++ .../asr/conf/train_asr_rnn_debug.yaml | 166 ++++++++++++++++++ ...in.yaml => train_asr_streaming_debug.yaml} | 42 ++--- .../asr/conf/train_asr_transducer_debug.yaml | 164 +++++++++++++++++ .../asr/conf/train_asr_transformer.yaml | 160 +++++++++++++++++ .../asr/conf/train_asr_transformer_debug.yaml | 160 +++++++++++++++++ .../mini_an4/asr/conf/train_lm_rnn_debug.yaml | 142 +++++++++++++++ ...n_transducer_asr_conformer_rnnt_debug.yaml | 139 +++++++++++++++ 11 files changed, 1156 insertions(+), 23 deletions(-) create mode 100644 egs3/mini_an4/asr/conf/infer_transducer.yaml create mode 100644 egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml create mode 100644 egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml rename egs3/mini_an4/asr/conf/{train.yaml => train_asr_streaming_debug.yaml} (85%) create mode 100644 egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml create mode 100644 egs3/mini_an4/asr/conf/train_asr_transformer.yaml create mode 100644 egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml create mode 100644 egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml create mode 100644 egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml diff --git a/egs3/mini_an4/asr/conf/infer.yaml b/egs3/mini_an4/asr/conf/infer.yaml index 93338319cf44..7c9ff3576a1e 100644 --- a/egs3/mini_an4/asr/conf/infer.yaml +++ b/egs3/mini_an4/asr/conf/infer.yaml @@ -5,7 +5,7 @@ num_nodes: 1 recipe_dir: . data_dir: ${recipe_dir}/data -exp_tag: mini_an4_asr_debug +exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode diff --git a/egs3/mini_an4/asr/conf/infer_transducer.yaml b/egs3/mini_an4/asr/conf/infer_transducer.yaml new file mode 100644 index 000000000000..d26efa9f92bd --- /dev/null +++ b/egs3/mini_an4/asr/conf/infer_transducer.yaml @@ -0,0 +1,36 @@ +# Mini AN4 ASR inference config for ESPnet3 integration tests. + +num_device: 1 +num_nodes: 1 + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: ${load_yaml:conf/train.yaml,exp_tag} +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + test: + - name: test + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/test.tsv + +parallel: + env: local + n_workers: 1 + +model: + _target_: espnet2.bin.asr_transducer_inference.Speech2Text + asr_train_config: ${exp_dir}/config.yaml + asr_model_file: ${exp_dir}/last.ckpt + beam_size: 1 + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/measure.yaml index 395c01c1fbac..d650f9577243 100644 --- a/egs3/mini_an4/asr/conf/measure.yaml +++ b/egs3/mini_an4/asr/conf/measure.yaml @@ -2,7 +2,7 @@ recipe_dir: . data_dir: ${recipe_dir}/data -exp_tag: mini_an4_asr_debug +exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml new file mode 100644 index 000000000000..425c665a8946 --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml @@ -0,0 +1,166 @@ +# This is a debug config for CI +# Mini AN4 ASR training config for ESPnet3 integration tests. + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_asr_rnn_data_aug_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + _convert_: all + fs: 16000 + train: true + data_aug_effects: # no need to set the "sample_rate" argument for each effect here + - [0.1, "contrast", {"enhancement_amount": 75.0}] + - [0.1, "highpass", {"cutoff_freq": 5000, "Q": 0.707}] + - [0.1, "equalization", {"center_freq": 1000, "gain": 0, "Q": 0.707}] + - - 0.1 + - - [0.3, "speed_perturb", {"factor": 0.9}] + - [0.3, "speed_perturb", {"factor": 1.1}] + - [0.3, "speed_perturb", {"factor": 1.3}] + data_aug_num: [1, 4] + data_aug_prob: 1.0 + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 2 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + + + +optim: + _target_: torch.optim.Adam + lr: 0.001 + weight_decay: 0.0 + +scheduler: + _target_: torch.optim.lr_scheduler.ReduceLROnPlateau + mode: min + factor: 0.5 + patience: 1 + +val_scheduler_criterion: valid/loss + +best_model_criterion: + - - valid/acc + - 1 + - max + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: vgg_rnn + encoder_conf: + num_layers: 1 + hidden_size: 2 + output_size: 2 + + decoder: rnn + decoder_conf: + hidden_size: 2 + + normalize: utterance_mvn + normalize_conf: {} + + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml new file mode 100644 index 000000000000..31adfa9cff24 --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml @@ -0,0 +1,166 @@ +# This is a debug config for CI +# Mini AN4 ASR training config for ESPnet3 integration tests. + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_asr_rnn_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + _convert_: all + fs: 16000 + train: true + data_aug_effects: # no need to set the "sample_rate" argument for each effect here + - [0.1, "contrast", {"enhancement_amount": 75.0}] + - [0.1, "highpass", {"cutoff_freq": 5000, "Q": 0.707}] + - [0.1, "equalization", {"center_freq": 1000, "gain": 0, "Q": 0.707}] + - - 0.1 + - - [0.3, "speed_perturb", {"factor": 0.9}] + - [0.3, "speed_perturb", {"factor": 1.1}] + - [0.3, "speed_perturb", {"factor": 1.3}] + data_aug_num: [1, 4] + data_aug_prob: 1.0 + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 2 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + + + +optim: + _target_: torch.optim.Adam + lr: 0.001 + weight_decay: 0.0 + +scheduler: + _target_: torch.optim.lr_scheduler.ReduceLROnPlateau + mode: min + factor: 0.5 + patience: 1 + +val_scheduler_criterion: valid/loss + +best_model_criterion: + - - valid/loss + - 1 + - min + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: vgg_rnn + encoder_conf: + num_layers: 1 + hidden_size: 2 + output_size: 2 + + decoder: rnn + decoder_conf: + hidden_size: 2 + + normalize: utterance_mvn + normalize_conf: {} + + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train.yaml b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml similarity index 85% rename from egs3/mini_an4/asr/conf/train.yaml rename to egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml index d774ee7c2088..4e28805078d6 100644 --- a/egs3/mini_an4/asr/conf/train.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml @@ -1,12 +1,17 @@ +# This is a debug config for CI # Mini AN4 ASR training config for ESPnet3 integration tests. + +init: xavier_uniform + + num_device: 1 num_nodes: 1 task: espnet3.systems.asr.task.ASRTask recipe_dir: . data_dir: ${recipe_dir}/data -exp_tag: mini_an4_asr_debug +exp_tag: train_asr_streaming_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode @@ -54,7 +59,7 @@ dataloader: collate_fn: ${dataloader.collate_fn} num_workers: 0 batches: - type: sorted + type: unsorted shape_files: - ${stats_dir}/train/feats_shape batch_size: 2 @@ -75,8 +80,7 @@ dataloader: optim: _target_: torch.optim.Adam - lr: 0.001 - weight_decay: 0.0 + lr: 0.005 scheduler: _target_: espnet2.schedulers.warmup_lr.WarmupLR @@ -122,35 +126,31 @@ model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt - encoder: transformer + encoder: contextual_block_transformer encoder_conf: - output_size: 256 - attention_heads: 4 - linear_units: 2048 - num_blocks: 12 - dropout_rate: 0.1 - positional_dropout_rate: 0.1 - attention_dropout_rate: 0.0 - input_layer: conv2d - normalize_before: true + block_size: 40 + hop_size: 16 + look_ahead: 16 + output_size: 2 + attention_heads: 2 + linear_units: 2 + num_blocks: 1 decoder: transformer decoder_conf: - attention_heads: 4 - linear_units: 2048 - num_blocks: 6 - dropout_rate: 0.1 - positional_dropout_rate: 0.1 - self_attention_dropout_rate: 0.0 - src_attention_dropout_rate: 0.0 + attention_heads: 2 + linear_units: 2 + num_blocks: 1 normalize: utterance_mvn normalize_conf: {} + model: espnet model_conf: ctc_weight: 0.3 lsm_weight: 0.1 length_normalized_loss: false + extract_feats_in_collect_stats: false frontend: default frontend_conf: diff --git a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml new file mode 100644 index 000000000000..9e8138be848f --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml @@ -0,0 +1,164 @@ +# This is a debug config for CI +# Mini AN4 ASR training config for ESPnet3 integration tests. + +init: xavier_uniform + + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_asr_transducer_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: unsorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 2 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.005 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 100 + +best_model_criterion: + - - valid/loss + - 1 + - min + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: transformer + encoder_conf: + output_size: 2 + attention_heads: 2 + linear_units: 2 + num_blocks: 2 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + attention_dropout_rate: 0.0 + input_layer: conv1d2 + normalize_before: true + + decoder: transducer + decoder_conf: + rnn_type: lstm + num_layers: 1 # Decoder Layers + hidden_size: 4 # Decoder dim + dropout: 0.1 + dropout_embed: 0.2 + + joint_net_conf: + joint_space_size: 4 + + normalize: utterance_mvn + normalize_conf: {} + + model: espnet + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml new file mode 100644 index 000000000000..ee90be82c1fc --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml @@ -0,0 +1,160 @@ +# This is a debug config for CI +init: xavier_uniform + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_asr_transformer +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 32 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.005 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 30000 + +best_model_criterion: + - - valid/acc + - 10 + - max + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 100 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: transformer + encoder_conf: + output_size: 256 + attention_heads: 4 + linear_units: 2048 + num_blocks: 12 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + attention_dropout_rate: 0.0 + input_layer: conv2d + normalize_before: true + + decoder: transformer + decoder_conf: + attention_heads: 4 + linear_units: 2048 + num_blocks: 6 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + self_attention_dropout_rate: 0.0 + src_attention_dropout_rate: 0.0 + + normalize: utterance_mvn + normalize_conf: {} + + model: espnet + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml new file mode 100644 index 000000000000..3f71890e61fe --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml @@ -0,0 +1,160 @@ +# This is a debug config for CI +init: xavier_uniform + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_asr_transformer_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: unsorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 2 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.005 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 100 + +best_model_criterion: + - - valid/loss + - 10 + - min + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: transformer + encoder_conf: + output_size: 2 + attention_heads: 2 + linear_units: 2 + num_blocks: 2 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + attention_dropout_rate: 0.0 + input_layer: conv1d2 + normalize_before: true + + decoder: transformer + decoder_conf: + attention_heads: 2 + linear_units: 2 + num_blocks: 2 + dropout_rate: 0.1 + positional_dropout_rate: 0.1 + self_attention_dropout_rate: 0.0 + src_attention_dropout_rate: 0.0 + + normalize: utterance_mvn + normalize_conf: {} + + model: espnet + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml new file mode 100644 index 000000000000..e1e1bbc0420a --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml @@ -0,0 +1,142 @@ +# This is a debug config for CI +init: xavier_uniform + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.task.ASRTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_lm_rnn_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 32 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.005 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 30000 + +best_model_criterion: + - - valid/acc + - 10 + - max + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 100 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + lm_conf: + nlayers: 1 + unit: 2 + + normalize: utterance_mvn + normalize_conf: {} + + model: espnet + model_conf: + ctc_weight: 0.3 + lsm_weight: 0.1 + length_normalized_loss: false + + frontend: default + frontend_conf: + n_fft: 512 + win_length: 400 + hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml new file mode 100644 index 000000000000..50c8a7e87ef2 --- /dev/null +++ b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml @@ -0,0 +1,139 @@ +# This is a debug config for CI + +num_device: 1 +num_nodes: 1 +task: espnet3.systems.asr.transducer_task.ASRTransducerTask + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: train_transducer_asr_conformer_rnnt_debug +exp_dir: ${recipe_dir}/exp/${exp_tag} +stats_dir: ${recipe_dir}/exp/stats +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 + +create_dataset: + func: src.create_dataset.create_dataset + dataset_dir: ${dataset_dir} + archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + train: + - name: train_nodev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + valid: + - name: train_dev + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/train_dev.tsv + preprocessor: + _target_: espnet2.train.preprocessor.CommonPreprocessor + train: true + token_type: bpe + token_list: ${tokenizer.save_path}/tokens.txt + bpemodel: ${tokenizer.save_path}/bpe.model + text_cleaner: + +parallel: + env: local + n_workers: 1 + +dataloader: + collate_fn: + _target_: espnet2.train.collate_fn.CommonCollateFn + int_pad_value: -1 + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: true + collate_fn: ${dataloader.collate_fn} + num_workers: 0 + batches: + type: sorted + shape_files: + - ${stats_dir}/train/feats_shape + batch_size: 32 + batch_bins: 200000 + valid: + multiple_iterator: false + num_shards: 1 + iter_factory: + _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory + shuffle: false + collate_fn: ${dataloader.collate_fn} + batches: + type: ${dataloader.train.iter_factory.batches.type} + shape_files: + - ${stats_dir}/valid/feats_shape + batch_size: ${dataloader.train.iter_factory.batches.batch_size} + batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} + +optim: + _target_: torch.optim.Adam + lr: 0.005 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 30000 + +best_model_criterion: + - - valid/loss + - 10 + - min + +trainer: + accelerator: auto + devices: ${num_device} + num_nodes: ${num_nodes} + accumulate_grad_batches: 1 + check_val_every_n_epoch: 1 + gradient_clip_val: 1.0 + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + precision: 32 + + logger: + - _target_: lightning.pytorch.loggers.TensorBoardLogger + save_dir: ${exp_dir}/tensorboard + name: tb_logger + + strategy: auto + + +tokenizer: + vocab_size: 30 + character_coverage: 1.0 + model_type: bpe + save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} + text_builder: + func: src.tokenizer.gather_training_text + manifest_path: ${dataset_dir}/manifest/train_nodev.tsv + + +model: + vocab_size: ${tokenizer.vocab_size} + token_list: ${tokenizer.save_path}/tokens.txt + + encoder: conformer + encoder_conf: + body_conf: + - block_type: conformer + hidden_size: 2 + linear_size: 4 + heads: 2 + conv_mod_kernel_size: 3 + + decoder_conf: + embed_size: 4 + hidden_size: 4 + + joint_network_conf: + joint_space_size: 4 + From a4eb530a8054e1ab834cc26e9b40e9f38f5bf4db Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:12:37 -0500 Subject: [PATCH 11/67] Add running script for transducer with Transducer system --- egs3/mini_an4/asr/run_transducer.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 egs3/mini_an4/asr/run_transducer.py diff --git a/egs3/mini_an4/asr/run_transducer.py b/egs3/mini_an4/asr/run_transducer.py new file mode 100644 index 000000000000..460276f7cdac --- /dev/null +++ b/egs3/mini_an4/asr/run_transducer.py @@ -0,0 +1,20 @@ +from egs3.TEMPLATE.asr.run import ( + DEFAULT_STAGES, + build_parser, + main, + parse_cli_and_stage_args, +) +from espnet3.systems.asr.transducer_system import ASRTransducerSystem + +if __name__ == "__main__": + parser = build_parser( + stages=DEFAULT_STAGES, + add_arguments=None, + ) + args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) + + main( + args=args, + system_cls=ASRTransducerSystem, + stages=stages_to_run, + ) From 173561ec2bed93b0088abad04ff3affc34f349b1 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:13:51 -0500 Subject: [PATCH 12/67] Add more integration tests for ASR --- ci/test_integration_espnet3.sh | 41 +++++++++++++++++++++++++++------- 1 file changed, 33 insertions(+), 8 deletions(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index 7c34d954be49..8948cec7ab46 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -1,6 +1,6 @@ #!/usr/bin/env bash -set -euo pipefail +# set -euo pipefail . tools/activate_python.sh . tools/extra_path.sh @@ -13,17 +13,42 @@ gen_dummy_coverage(){ ${python} empty.py } -python3 -m pip install -e '.[asr]' +# python3 -m pip install -e '.[asr]' +uv pip install -e '.[asr]' cd ./egs3/mini_an4/asr gen_dummy_coverage echo "==== [ESPnet3] ASR ====" source ./path.sh -${python} run.py \ - --stages create_dataset train_tokenizer collect_stats train infer measure \ - --train_config conf/train.yaml \ - --infer_config conf/infer.yaml \ - --measure_config conf/measure.yaml +run_with_train_config() { + local train_config=$1 + local runner=$2 + local infer_config=$3 + + ln -sfn "${train_config}" conf/train.yaml + ${python} "${runner}" \ + --stages create_dataset train_tokenizer collect_stats train infer measure \ + --train_config conf/train.yaml \ + --infer_config "${infer_config}" \ + --measure_config conf/measure.yaml + rm -rf exp data +} + +debug_configs=( + train_asr_rnn_data_aug_debug.yaml + train_asr_rnn_debug.yaml + train_asr_streaming_debug.yaml + train_asr_transformer_debug.yaml + train_asr_transducer_debug.yaml +) + +for train_config in "${debug_configs[@]}"; do + run_with_train_config "${train_config}" run.py conf/infer.yaml +done + +run_with_train_config \ + train_transducer_asr_conformer_rnnt_debug.yaml \ + run_transducer.py \ + conf/infer_transducer.yaml -rm -rf exp data cd "${cwd}" From 11def0bd0c274114fc142249f29156d5e907ee7c Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:15:07 -0500 Subject: [PATCH 13/67] Removed debug line --- ci/test_integration_espnet3.sh | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index 8948cec7ab46..bd484330cd7c 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -1,6 +1,6 @@ #!/usr/bin/env bash -# set -euo pipefail +set -euo pipefail . tools/activate_python.sh . tools/extra_path.sh @@ -13,8 +13,7 @@ gen_dummy_coverage(){ ${python} empty.py } -# python3 -m pip install -e '.[asr]' -uv pip install -e '.[asr]' +python3 -m pip install -e '.[asr]' cd ./egs3/mini_an4/asr gen_dummy_coverage From 094af9f8e9cc1620a06c7300101ed78df10532d7 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 9 Jan 2026 08:15:33 +0000 Subject: [PATCH 14/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml | 1 - espnet3/components/modeling/model.py | 5 ++++- espnet3/systems/asr/inference.py | 1 - espnet3/systems/asr/transducer_system.py | 4 +++- .../components/modeling/test_model_with_optim_scheduler.py | 1 - 5 files changed, 7 insertions(+), 5 deletions(-) diff --git a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml index 50c8a7e87ef2..5ad59263a802 100644 --- a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml @@ -136,4 +136,3 @@ model: joint_network_conf: joint_space_size: 4 - diff --git a/espnet3/components/modeling/model.py b/espnet3/components/modeling/model.py index ca4b1766a867..2c0d66bf6d53 100644 --- a/espnet3/components/modeling/model.py +++ b/espnet3/components/modeling/model.py @@ -242,12 +242,15 @@ def configure_optimizers(self): AssertionError: If configuration rules are violated. ValueError: If neither optimizer configuration is provided. """ + def _get_val_scheduler_monitor(): criterion = getattr(self.config, "val_scheduler_criterion", None) if criterion is None: return None if not isinstance(criterion, str): - raise ValueError("val_scheduler_criterion must be a string like 'valid/loss'") + raise ValueError( + "val_scheduler_criterion must be a string like 'valid/loss'" + ) return criterion if getattr(self.config, "optim", None) and getattr( diff --git a/espnet3/systems/asr/inference.py b/espnet3/systems/asr/inference.py index ad92bd76967f..02714772a13c 100644 --- a/espnet3/systems/asr/inference.py +++ b/espnet3/systems/asr/inference.py @@ -110,7 +110,6 @@ def forward(idx, dataset=None, model=None, **kwargs): return {"idx": idx, "hyp": hyp, "ref": ref} - class TransducerInferenceRunner(AbsInferenceRunner): """Inference runner that produces hypotheses and references. diff --git a/espnet3/systems/asr/transducer_system.py b/espnet3/systems/asr/transducer_system.py index 7d7dadd525ab..2cfde9b9bcc3 100644 --- a/espnet3/systems/asr/transducer_system.py +++ b/espnet3/systems/asr/transducer_system.py @@ -9,10 +9,11 @@ from pathlib import Path from omegaconf import DictConfig + from espnet3.parallel.parallel import set_parallel from espnet3.systems.asr.inference import InferenceProvider, TransducerInferenceRunner from espnet3.systems.asr.system import ASRSystem -from espnet3.systems.base.inference import (_collect_scp_lines, _flatten_results) +from espnet3.systems.base.inference import _collect_scp_lines, _flatten_results from espnet3.systems.base.inference_runner import AbsInferenceRunner logger = logging.getLogger(__name__) @@ -24,6 +25,7 @@ class ASRTransducerSystem(ASRSystem): This system adds: - Tokenizer training inside train() """ + def infer(self, *args, **kwargs): """Run inference on the configured datasets.""" self._reject_stage_args("infer", args, kwargs) diff --git a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py index 35ede5cb1dbb..f850a9529524 100644 --- a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py +++ b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py @@ -40,7 +40,6 @@ def __init__(self): self.linear2 = nn.Linear(10, 5) - # ========== VALID CASES ========== From dcbd1dec8e52f5887d1d46e2a64b04385714be84 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 9 Jan 2026 03:55:04 -0500 Subject: [PATCH 15/67] Format and fixed CI --- espnet3/components/modeling/model.py | 5 ++++- espnet3/systems/asr/inference.py | 1 - espnet3/systems/asr/transducer_system.py | 4 +++- espnet3/systems/asr/transducer_task.py | 9 +++------ .../modeling/test_model_with_optim_scheduler.py | 2 -- 5 files changed, 10 insertions(+), 11 deletions(-) diff --git a/espnet3/components/modeling/model.py b/espnet3/components/modeling/model.py index ca4b1766a867..2c0d66bf6d53 100644 --- a/espnet3/components/modeling/model.py +++ b/espnet3/components/modeling/model.py @@ -242,12 +242,15 @@ def configure_optimizers(self): AssertionError: If configuration rules are violated. ValueError: If neither optimizer configuration is provided. """ + def _get_val_scheduler_monitor(): criterion = getattr(self.config, "val_scheduler_criterion", None) if criterion is None: return None if not isinstance(criterion, str): - raise ValueError("val_scheduler_criterion must be a string like 'valid/loss'") + raise ValueError( + "val_scheduler_criterion must be a string like 'valid/loss'" + ) return criterion if getattr(self.config, "optim", None) and getattr( diff --git a/espnet3/systems/asr/inference.py b/espnet3/systems/asr/inference.py index ad92bd76967f..02714772a13c 100644 --- a/espnet3/systems/asr/inference.py +++ b/espnet3/systems/asr/inference.py @@ -110,7 +110,6 @@ def forward(idx, dataset=None, model=None, **kwargs): return {"idx": idx, "hyp": hyp, "ref": ref} - class TransducerInferenceRunner(AbsInferenceRunner): """Inference runner that produces hypotheses and references. diff --git a/espnet3/systems/asr/transducer_system.py b/espnet3/systems/asr/transducer_system.py index 7d7dadd525ab..2cfde9b9bcc3 100644 --- a/espnet3/systems/asr/transducer_system.py +++ b/espnet3/systems/asr/transducer_system.py @@ -9,10 +9,11 @@ from pathlib import Path from omegaconf import DictConfig + from espnet3.parallel.parallel import set_parallel from espnet3.systems.asr.inference import InferenceProvider, TransducerInferenceRunner from espnet3.systems.asr.system import ASRSystem -from espnet3.systems.base.inference import (_collect_scp_lines, _flatten_results) +from espnet3.systems.base.inference import _collect_scp_lines, _flatten_results from espnet3.systems.base.inference_runner import AbsInferenceRunner logger = logging.getLogger(__name__) @@ -24,6 +25,7 @@ class ASRTransducerSystem(ASRSystem): This system adds: - Tokenizer training inside train() """ + def infer(self, *args, **kwargs): """Run inference on the configured datasets.""" self._reject_stage_args("infer", args, kwargs) diff --git a/espnet3/systems/asr/transducer_task.py b/espnet3/systems/asr/transducer_task.py index 017fcd5ef58f..1feca7e656ad 100644 --- a/espnet3/systems/asr/transducer_task.py +++ b/espnet3/systems/asr/transducer_task.py @@ -239,7 +239,6 @@ def build_collate_fn(cls, args: argparse.Namespace, train: bool) -> Callable[ : Callable collate function. """ - return CommonCollateFn(float_pad_value=0.0, int_pad_value=-1) @classmethod @@ -258,7 +257,6 @@ def build_preprocess_fn( : Callable pre-processing function. """ - if args.use_preprocessor: retval = CommonPreprocessor( train=train, @@ -292,7 +290,7 @@ def build_preprocess_fn( def required_data_names( cls, train: bool = True, inference: bool = False ) -> Tuple[str, ...]: - """Required data depending on task mode. + """Determine required data based on the task mode. Args: cls: ASRTransducerTask object. @@ -314,7 +312,7 @@ def required_data_names( def optional_data_names( cls, train: bool = True, inference: bool = False ) -> Tuple[str, ...]: - """Optional data depending on task mode. + """Specify optional data based on the task mode. Args: cls: ASRTransducerTask object. @@ -332,7 +330,7 @@ def optional_data_names( @classmethod @typechecked def build_model(cls, args: argparse.Namespace) -> ESPnetASRTransducerModel: - """Required data depending on task mode. + """Require data based on the task mode. Args: cls: ASRTransducerTask object. @@ -342,7 +340,6 @@ def build_model(cls, args: argparse.Namespace) -> ESPnetASRTransducerModel: model: ASR Transducer model. """ - if isinstance(args.token_list, str): with open(args.token_list, encoding="utf-8") as f: token_list = [line.rstrip() for line in f] diff --git a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py index 35ede5cb1dbb..5a8a446a730a 100644 --- a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py +++ b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py @@ -1,5 +1,4 @@ import pytest -import torch import torch.nn as nn from omegaconf import OmegaConf @@ -40,7 +39,6 @@ def __init__(self): self.linear2 = nn.Linear(10, 5) - # ========== VALID CASES ========== From e88e05170c0133e4d594e24a484d800e70b90bfb Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sat, 10 Jan 2026 00:04:07 -0500 Subject: [PATCH 16/67] Separate logs for each stages --- egs3/TEMPLATE/asr/run.py | 72 ++++++++++++++++++++----------- espnet3/systems/asr/system.py | 62 ++++++++++++++++++++++++++ espnet3/systems/base/system.py | 20 +++++++++ espnet3/utils/logging.py | 48 +++++++++++++++++++++ espnet3/utils/stages.py | 26 ++++++++++- test/espnet3/utils/test_stages.py | 37 ++++++++++++++++ 6 files changed, 239 insertions(+), 26 deletions(-) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 1ec052b8071f..9072effdbee6 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -70,6 +70,11 @@ def build_parser( action="store_true", help="Print what would be executed without actually running stages.", ) + parser.add_argument( + "--write_requirements", + action="store_true", + help="Write requirements.txt alongside each stage log.", + ) # Stage-specific arguments can be added here if needed parser.add_argument( @@ -124,31 +129,7 @@ def main( else load_config_with_defaults(args.measure_config) ) - log_dir = getattr(train_config, "exp_dir", None) - logger = configure_logging(log_dir=Path(log_dir) if log_dir else None) - log_run_metadata( - logger, - argv=sys.argv, - configs={ - "train": Path(args.train_config) if args.train_config else None, - "infer": Path(args.infer_config) if args.infer_config else None, - "measure": Path(args.measure_config) if args.measure_config else None, - }, - ) - log_env_metadata(logger) - if train_config is not None: - logger.info( - "Train config content:\n%s", OmegaConf.to_yaml(train_config, resolve=True) - ) - if infer_config is not None: - logger.info( - "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) - ) - if measure_config is not None: - logger.info( - "Measure config content:\n%s", - OmegaConf.to_yaml(measure_config, resolve=True), - ) + logger = configure_logging() # ----------------------------------------- # Instantiate system @@ -192,9 +173,50 @@ def main( stages_to_run=stages_to_run, dry_run=args.dry_run, log=logger, + on_stage_start=lambda stage, log: _log_stage_metadata( + log, + args=args, + train_config=train_config, + infer_config=infer_config, + measure_config=measure_config, + ), ) +def _log_stage_metadata( + logger, + *, + args: argparse.Namespace, + train_config, + infer_config, + measure_config, +) -> None: + log_run_metadata( + logger, + argv=sys.argv, + configs={ + "train": Path(args.train_config) if args.train_config else None, + "infer": Path(args.infer_config) if args.infer_config else None, + "measure": Path(args.measure_config) if args.measure_config else None, + }, + write_requirements=args.write_requirements, + ) + log_env_metadata(logger) + if train_config is not None: + logger.info( + "Train config content:\n%s", OmegaConf.to_yaml(train_config, resolve=True) + ) + if infer_config is not None: + logger.info( + "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) + ) + if measure_config is not None: + logger.info( + "Measure config content:\n%s", + OmegaConf.to_yaml(measure_config, resolve=True), + ) + + if __name__ == "__main__": parser = build_parser(stages=DEFAULT_STAGES) args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index 7dc8aa8de930..5752f76a1673 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -69,6 +69,68 @@ def create_dataset(self, *args, **kwargs): ) return result + def get_stage_log_dir(self, stage: str) -> Path: + """Return stage-specific log directories when configured. + + The ASR system routes logs to artifact directories when available: + - ``create_dataset``: ``train_config.create_dataset.dataset_dir`` or + ``train_config.dataset_dir`` or ``train_config.data_dir``. + - ``train_tokenizer``: ``train_config.tokenizer.save_path``. + - ``collect_stats``: ``train_config.stats_dir``. + - ``train``/``publish``: ``train_config.exp_dir``. + - ``infer``: ``infer_config.decode_dir``. + - ``measure``: ``metric_config.decode_dir`` or ``infer_config.decode_dir``. + + If none of the stage-specific paths are configured, it falls back to + ``BaseSystem.get_stage_log_dir`` (``train_config.exp_dir`` or + ``/logs``). + + Args: + stage (str): Stage name being executed. + + Returns: + Path: Directory where the stage log should be placed. + """ + if stage == "create_dataset": + cfg = getattr(self.train_config, "create_dataset", None) + if cfg is not None: + dataset_dir = getattr(cfg, "dataset_dir", None) + if dataset_dir: + return Path(dataset_dir) + dataset_dir = getattr(self.train_config, "dataset_dir", None) + if dataset_dir: + return Path(dataset_dir) + data_dir = getattr(self.train_config, "data_dir", None) + if data_dir: + return Path(data_dir) + elif stage == "train_tokenizer": + tokenizer_cfg = getattr(self.train_config, "tokenizer", None) + save_path = ( + getattr(tokenizer_cfg, "save_path", None) if tokenizer_cfg else None + ) + if save_path: + return Path(save_path) + elif stage == "collect_stats": + stats_dir = getattr(self.train_config, "stats_dir", None) + if stats_dir: + return Path(stats_dir) + elif stage in {"train", "publish"}: + exp_dir = getattr(self.train_config, "exp_dir", None) + if exp_dir: + return Path(exp_dir) + elif stage == "infer": + decode_dir = getattr(self.infer_config, "decode_dir", None) + if decode_dir: + return Path(decode_dir) + elif stage == "measure": + decode_dir = getattr(self.metric_config, "decode_dir", None) + if decode_dir: + return Path(decode_dir) + decode_dir = getattr(self.infer_config, "decode_dir", None) + if decode_dir: + return Path(decode_dir) + return super().get_stage_log_dir(stage) + def train(self, *args, **kwargs): """Train the model, training the tokenizer first if needed. diff --git a/espnet3/systems/base/system.py b/espnet3/systems/base/system.py index 4ff9acadc7a0..48cac4295d22 100644 --- a/espnet3/systems/base/system.py +++ b/espnet3/systems/base/system.py @@ -56,6 +56,26 @@ def __init__( self.exp_dir, ) + def get_stage_log_dir(self, stage: str) -> Path: + """Return the default log directory for a stage. + + BaseSystem treats all stages uniformly and writes logs into: + - ``train_config.exp_dir`` when available, or + - ``/logs`` as a fallback when no experiment directory is set. + + Subclasses can override this method to route specific stages to + stage-aware artifact locations (e.g., dataset or decode outputs). + + Args: + stage (str): Stage name being executed (unused by BaseSystem). + + Returns: + Path: Directory where the stage log should be placed. + """ + if self.exp_dir is not None: + return self.exp_dir + return Path.cwd() / "logs" + @staticmethod def _reject_stage_args(stage: str, args, kwargs) -> None: """Reject unexpected positional/keyword arguments for stages.""" diff --git a/espnet3/utils/logging.py b/espnet3/utils/logging.py index 0ad434dfb0ef..53941145e026 100644 --- a/espnet3/utils/logging.py +++ b/espnet3/utils/logging.py @@ -83,6 +83,54 @@ def configure_logging( return logging.getLogger("espnet3") +def set_stage_log_handler( + logger: logging.Logger, + log_dir: Path | None, + *, + filename: str, +) -> Path | None: + """Attach a file handler for a stage log, replacing any prior stage handler. + + This function adds a new file handler to the root logger and removes any + previously installed stage handler (identified via ``_espnet3_stage_log``). + If a log file already exists at the target path, it is rotated (e.g., + ``train.log`` -> ``train1.log``) before creating the new handler. + + Args: + logger (logging.Logger): Logger used to emit logs. + The handler is attached to the root logger so the logger hierarchy + continues to work as expected. + log_dir (Path | None): Directory that should receive the stage log. + If None, no handler is installed and None is returned. + filename (str): Log filename to create within ``log_dir``. + + Returns: + Path | None: Resolved log file path when installed, otherwise None. + """ + if log_dir is None: + return None + + log_dir.mkdir(parents=True, exist_ok=True) + target = (log_dir / filename).resolve() + + root = logging.getLogger() + for handler in list(root.handlers): + if getattr(handler, "_espnet3_stage_log", False): + root.removeHandler(handler) + handler.close() + + formatter = logging.Formatter(fmt=LOG_FORMAT, datefmt=DATE_FORMAT) + if target.exists(): + rotated = _next_rotated_log_path(target) + os.replace(target, rotated) + file_handler = logging.FileHandler(target) + file_handler.setFormatter(formatter) + file_handler._espnet3_stage_log = True + root.addHandler(file_handler) + + return target + + def _run_git_command(cmd: list[str], cwd: Path | None) -> str | None: """Run a git command and return stdout, or None on failure.""" try: diff --git a/espnet3/utils/stages.py b/espnet3/utils/stages.py index 372269346c67..1150e01a1e5d 100644 --- a/espnet3/utils/stages.py +++ b/espnet3/utils/stages.py @@ -4,7 +4,8 @@ import logging import time -from typing import Any, Iterable, List, Sequence +from pathlib import Path +from typing import Any, Callable, Iterable, List, Sequence logger = logging.getLogger(__name__) @@ -31,6 +32,8 @@ def run_stages( *, dry_run: bool = False, log: logging.Logger | None = None, + stage_log_dir_fn: Callable[[str], Path | None] | None = None, + on_stage_start: Callable[[str, logging.Logger], None] | None = None, ) -> None: """Invoke stage methods on ``system`` in order with logging and timing. @@ -39,6 +42,13 @@ def run_stages( stages_to_run: Iterable of stage method names to execute. dry_run: If True, log intended stages without executing them. log: Optional logger instance; defaults to module logger. + stage_log_dir_fn: Optional callable that returns a stage log directory. + When provided (or resolved from ``system.get_stage_log_dir``), + a per-stage file handler is configured using + ``/.log`` before executing each stage. + on_stage_start: Optional hook invoked after stage logging is configured. + This can be used to emit per-stage metadata (configs, environment, + requirements snapshots, etc.) into the newly attached log file. Raises: AttributeError: If a named stage method is missing on ``system``. @@ -46,6 +56,8 @@ def run_stages( Exception: Re-raises any exception from a stage method. """ log = log or logger + if stage_log_dir_fn is None and hasattr(system, "get_stage_log_dir"): + stage_log_dir_fn = getattr(system, "get_stage_log_dir") for stage in stages_to_run: fn = getattr(system, stage, None) if fn is None: @@ -55,6 +67,18 @@ def run_stages( log.info("[DRY RUN] would run stage: %s", stage) continue + if stage_log_dir_fn is not None: + from espnet3.utils.logging import set_stage_log_handler + + log_dir = stage_log_dir_fn(stage) + set_stage_log_handler( + log, + Path(log_dir) if log_dir else None, + filename=f"{stage}.log", + ) + if on_stage_start is not None: + on_stage_start(stage, log) + start = time.perf_counter() log.info("=== [START] stage: %s ===", stage) try: diff --git a/test/espnet3/utils/test_stages.py b/test/espnet3/utils/test_stages.py index 9ab98b7cf03b..b1211492f8f5 100644 --- a/test/espnet3/utils/test_stages.py +++ b/test/espnet3/utils/test_stages.py @@ -63,3 +63,40 @@ def stage_a(self): system = CrashSystem() with pytest.raises(ValueError, match="boom"): run_stages(system, ["stage_a"]) + + +def test_run_stages_writes_stage_logs(tmp_path): + class LoggingSystem: + def __init__(self, log_dir): + self.log_dir = log_dir + + def get_stage_log_dir(self, stage): + return self.log_dir + + def stage_a(self): + pass + + def stage_b(self): + pass + + system = LoggingSystem(tmp_path) + logger = logging.getLogger("espnet3.test_stages") + root = logging.getLogger() + previous_level = root.level + root.setLevel(logging.INFO) + try: + run_stages(system, ["stage_a", "stage_b"], log=logger) + finally: + root.setLevel(previous_level) + + stage_a_log = tmp_path / "stage_a.log" + stage_b_log = tmp_path / "stage_b.log" + assert stage_a_log.exists() + assert stage_b_log.exists() + + stage_a_text = stage_a_log.read_text(encoding="utf-8") + stage_b_text = stage_b_log.read_text(encoding="utf-8") + assert "stage: stage_a" in stage_a_text + assert "stage: stage_b" not in stage_a_text + assert "stage: stage_b" in stage_b_text + assert "stage: stage_a" not in stage_b_text From 72b8516696004c7b1d6326fb371dac697c36f4b1 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Tue, 20 Jan 2026 16:50:37 -0500 Subject: [PATCH 17/67] Fixed bug in trainer config --- espnet3/components/training/trainer.py | 33 ++++++++++++++++---------- 1 file changed, 21 insertions(+), 12 deletions(-) diff --git a/espnet3/components/training/trainer.py b/espnet3/components/training/trainer.py index 45c825f7cd0f..59b5928cbf0c 100644 --- a/espnet3/components/training/trainer.py +++ b/espnet3/components/training/trainer.py @@ -1,5 +1,6 @@ """Trainer class for the espnet3 package.""" +import copy import warnings from argparse import Namespace from typing import Any, Dict, Union @@ -75,28 +76,18 @@ def __init__( # Accelerator accelerator = _get_or_initialize(self.config, "accelerator", "auto") - if hasattr(self.config, "accelerator"): - self._del_config_key("accelerator") # strategy strategy = _get_or_initialize(self.config, "strategy", "auto") - if hasattr(self.config, "strategy"): - self._del_config_key("strategy") # logger logger = _get_or_initialize(self.config, "logger") - if logger is not None: - self._del_config_key("logger") # profiler profiler = _get_or_initialize(self.config, "profiler") - if profiler is not None: - self._del_config_key("profiler") # plugins plugins = _get_or_initialize(self.config, "plugins") - if plugins is not None: - self._del_config_key("plugins") # Callbacks callbacks = get_default_callbacks( @@ -110,7 +101,6 @@ def __init__( ), "callbacks should be a list" for callback in self.config.callbacks: callbacks.append(instantiate(callback)) - self._del_config_key("callbacks") # Since espnet's sampler requires to set the following configs: # Reload dataloaders every epoch to reuse ESPnet's dataloader @@ -144,6 +134,17 @@ def __init__( if self.model.is_espnet_sampler: self.config.use_distributed_sampler = False + trainer_config = copy.deepcopy(self.config) + for key in ( + "accelerator", + "strategy", + "logger", + "profiler", + "plugins", + "callbacks", + ): + self._del_config_key_on(trainer_config, key) + # Set up the trainer self.trainer = lightning.Trainer( accelerator=accelerator, @@ -153,7 +154,7 @@ def __init__( logger=logger, profiler=profiler, plugins=plugins, - **self.config, + **trainer_config, ) def _del_config_key(self, key): @@ -162,6 +163,14 @@ def _del_config_key(self, key): elif isinstance(self.config, dict): self.config.pop(key) + @staticmethod + def _del_config_key_on(config, key): + if isinstance(config, DictConfig) or isinstance(config, Namespace): + if hasattr(config, key): + delattr(config, key) + elif isinstance(config, dict): + config.pop(key, None) + def fit(self, *args, **kwargs): """Start the training loop using Lightning's fit method. From 4f11ed3f7e034503bf52fb89b656785f22aba37d Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Tue, 27 Jan 2026 14:16:48 -0500 Subject: [PATCH 18/67] Fixed CI --- .../components/modeling/test_model_with_optim_scheduler.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py index a52f90c624c0..61b73ee8268a 100644 --- a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py +++ b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py @@ -150,7 +150,7 @@ def test_reduce_on_plateau_monitor_from_config(): } ) - model = LitESPnetModel(DummyModel(), config) + model = ESPnetLightningModule(DummyModel(), config) out = model.configure_optimizers() assert out["lr_scheduler"]["interval"] == "epoch" assert out["lr_scheduler"]["monitor"] == "valid/loss" @@ -175,7 +175,7 @@ def test_val_scheduler_criterion_sets_epoch(): } ) - model = LitESPnetModel(DummyModel(), config) + model = ESPnetLightningModule(DummyModel(), config) out = model.configure_optimizers() assert out["lr_scheduler"]["interval"] == "epoch" assert out["lr_scheduler"]["monitor"] == "valid/acc" From 7cb6f39796e7f76e9bde0d005d8fffd28a8a4809 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Tue, 27 Jan 2026 14:18:01 -0500 Subject: [PATCH 19/67] Update infer.yaml --- egs3/TEMPLATE/asr/conf/infer.yaml | 48 ++++---------------- egs3/mini_an4/asr/conf/infer.yaml | 10 ---- egs3/mini_an4/asr/conf/infer_transducer.yaml | 36 ++++++--------- 3 files changed, 22 insertions(+), 72 deletions(-) diff --git a/egs3/TEMPLATE/asr/conf/infer.yaml b/egs3/TEMPLATE/asr/conf/infer.yaml index 42714a973b6d..c08525d0e52c 100644 --- a/egs3/TEMPLATE/asr/conf/infer.yaml +++ b/egs3/TEMPLATE/asr/conf/infer.yaml @@ -1,21 +1,17 @@ # Inference/decoding configuration template for ESPnet3 ASR. -# Mirrors the training paths but keeps only inference-relevant knobs. - -# Minimal runtime scaffold; fill in task in derived configs if needed. -num_device: 1 -num_nodes: 1 +# Keep only inference-relevant knobs. # Path scaffold relative to the recipe root. recipe_dir: . data_dir: ${recipe_dir}/data +dataset_dir: /path/to/your/dataset exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode # Dataset definition for test splits only. dataset: - _target_: espnet3.components.data_organizer.DataOrganizer + _target_: espnet3.components.data.data_organizer.DataOrganizer test: - name: test-clean dataset: @@ -23,39 +19,13 @@ dataset: data_dir: ${dataset_dir} split: test-clean +# Inference model entrypoint. +model: + _target_: espnet2.bin.asr_inference.Speech2Text + asr_train_config: ${exp_dir}/config.yaml + asr_model_file: ${exp_dir}/last.ckpt + # Parallel execution used during data loading / scoring (defaults to local). parallel: env: local n_workers: 1 - -# DataLoader defaults; keep small batch settings for lightweight decoding. -dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 - train: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - batches: - type: numel - shape_files: - - ${stats_dir}/train/feats_shape - batch_size: 4 - batch_bins: 4000000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} diff --git a/egs3/mini_an4/asr/conf/infer.yaml b/egs3/mini_an4/asr/conf/infer.yaml index 7c9ff3576a1e..5facedb93dd1 100644 --- a/egs3/mini_an4/asr/conf/infer.yaml +++ b/egs3/mini_an4/asr/conf/infer.yaml @@ -1,13 +1,9 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -num_device: 1 -num_nodes: 1 - recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode dataset_dir: ${data_dir}/mini_an4 @@ -29,9 +25,3 @@ model: asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 ctc_weight: 0.3 - -tokenizer: - vocab_size: 30 - character_coverage: 1.0 - model_type: bpe - save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} diff --git a/egs3/mini_an4/asr/conf/infer_transducer.yaml b/egs3/mini_an4/asr/conf/infer_transducer.yaml index d26efa9f92bd..ac191fb18ab0 100644 --- a/egs3/mini_an4/asr/conf/infer_transducer.yaml +++ b/egs3/mini_an4/asr/conf/infer_transducer.yaml @@ -1,15 +1,11 @@ -# Mini AN4 ASR inference config for ESPnet3 integration tests. - -num_device: 1 -num_nodes: 1 - -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: ${load_yaml:conf/train.yaml,exp_tag} -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode -dataset_dir: ${data_dir}/mini_an4 +# Mini AN4 ASR inference config for ESPnet3 integration tests. + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: ${load_yaml:conf/train.yaml,exp_tag} +exp_dir: ${recipe_dir}/exp/${exp_tag} +decode_dir: ${exp_dir}/decode +dataset_dir: ${data_dir}/mini_an4 dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer @@ -23,14 +19,8 @@ parallel: env: local n_workers: 1 -model: - _target_: espnet2.bin.asr_transducer_inference.Speech2Text - asr_train_config: ${exp_dir}/config.yaml - asr_model_file: ${exp_dir}/last.ckpt - beam_size: 1 - -tokenizer: - vocab_size: 30 - character_coverage: 1.0 - model_type: bpe - save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} +model: + _target_: espnet2.bin.asr_transducer_inference.Speech2Text + asr_train_config: ${exp_dir}/config.yaml + asr_model_file: ${exp_dir}/last.ckpt + beam_size: 1 From 9a29c3e6b0edf6aaf00dcbb788db5d2599816190 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Tue, 27 Jan 2026 15:11:02 -0500 Subject: [PATCH 20/67] Fixed configs --- egs3/TEMPLATE/asr/conf/infer.yaml | 6 +++++- egs3/TEMPLATE/asr/conf/measure.yaml | 1 + egs3/mini_an4/asr/conf/infer.yaml | 5 ++++- egs3/mini_an4/asr/conf/infer_transducer.yaml | 5 ++++- egs3/mini_an4/asr/conf/measure.yaml | 1 + egs3/mini_an4/asr/run.py | 4 ++-- egs3/mini_an4/asr/src/infer.py | 17 +++++++++++++++++ 7 files changed, 34 insertions(+), 5 deletions(-) create mode 100644 egs3/mini_an4/asr/src/infer.py diff --git a/egs3/TEMPLATE/asr/conf/infer.yaml b/egs3/TEMPLATE/asr/conf/infer.yaml index c08525d0e52c..bd0a30da85f6 100644 --- a/egs3/TEMPLATE/asr/conf/infer.yaml +++ b/egs3/TEMPLATE/asr/conf/infer.yaml @@ -7,7 +7,7 @@ data_dir: ${recipe_dir}/data dataset_dir: /path/to/your/dataset exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer # Dataset definition for test splits only. dataset: @@ -25,6 +25,10 @@ model: asr_train_config: ${exp_dir}/config.yaml asr_model_file: ${exp_dir}/last.ckpt +# Inference I/O. +input_key: speech +output_fn: src.infer.output_fn + # Parallel execution used during data loading / scoring (defaults to local). parallel: env: local diff --git a/egs3/TEMPLATE/asr/conf/measure.yaml b/egs3/TEMPLATE/asr/conf/measure.yaml index 38df1c4f63f4..89f33fbe9adf 100644 --- a/egs3/TEMPLATE/asr/conf/measure.yaml +++ b/egs3/TEMPLATE/asr/conf/measure.yaml @@ -8,6 +8,7 @@ exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: /path/to/your/dataset # Dataset definition for test splits only (used to enumerate test names). diff --git a/egs3/mini_an4/asr/conf/infer.yaml b/egs3/mini_an4/asr/conf/infer.yaml index 5facedb93dd1..b0ef536dc3ab 100644 --- a/egs3/mini_an4/asr/conf/infer.yaml +++ b/egs3/mini_an4/asr/conf/infer.yaml @@ -4,7 +4,7 @@ recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 dataset: @@ -25,3 +25,6 @@ model: asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 ctc_weight: 0.3 + +input_key: speech +output_fn: src.infer.output_fn diff --git a/egs3/mini_an4/asr/conf/infer_transducer.yaml b/egs3/mini_an4/asr/conf/infer_transducer.yaml index ac191fb18ab0..b47dbbc3dd85 100644 --- a/egs3/mini_an4/asr/conf/infer_transducer.yaml +++ b/egs3/mini_an4/asr/conf/infer_transducer.yaml @@ -4,7 +4,7 @@ recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 dataset: @@ -24,3 +24,6 @@ model: asr_train_config: ${exp_dir}/config.yaml asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 + +input_key: speech +output_fn: src.infer.output_fn_transducer diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/measure.yaml index d650f9577243..07e2943a04d2 100644 --- a/egs3/mini_an4/asr/conf/measure.yaml +++ b/egs3/mini_an4/asr/conf/measure.yaml @@ -6,6 +6,7 @@ exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 dataset: diff --git a/egs3/mini_an4/asr/run.py b/egs3/mini_an4/asr/run.py index 8a38549eda45..4518f36ef3c7 100644 --- a/egs3/mini_an4/asr/run.py +++ b/egs3/mini_an4/asr/run.py @@ -11,10 +11,10 @@ stages=DEFAULT_STAGES, add_arguments=None, ) - args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) + args, _ = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) main( args=args, system_cls=ASRSystem, - stages=stages_to_run, + stages=DEFAULT_STAGES, ) diff --git a/egs3/mini_an4/asr/src/infer.py b/egs3/mini_an4/asr/src/infer.py new file mode 100644 index 000000000000..b8b7399b6733 --- /dev/null +++ b/egs3/mini_an4/asr/src/infer.py @@ -0,0 +1,17 @@ +"""Inference output helpers for ASR recipes.""" + + +def output_fn(*, data, model_output, idx): + """Build a dict of outputs for SCP writing.""" + uttid = data.get("uttid", str(idx)) + hyp = model_output[0][0] + ref = data.get("text", "") + return {"uttid": uttid, "hyp": hyp, "ref": ref} + + +def output_fn_transducer(*, data, model_output, idx): + """Build a dict of outputs for transducer models.""" + uttid = data.get("uttid", str(idx)) + hyp = model_output[0] + ref = data.get("text", "") + return {"uttid": uttid, "hyp": hyp, "ref": ref} From 33170748edbb9e17cb72209f180e7c65c1a60ebe Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 28 Jan 2026 23:54:29 -0500 Subject: [PATCH 21/67] Bug fixed for the logging directory - rename decode_dir into infer_dir --- espnet3/systems/asr/system.py | 13 +++++++++++-- espnet3/systems/asr/transducer_system.py | 20 ++++++++++++++------ 2 files changed, 25 insertions(+), 8 deletions(-) diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index 361e12999154..ceb3e69a14c1 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -78,8 +78,8 @@ def get_stage_log_dir(self, stage: str) -> Path: - ``train_tokenizer``: ``train_config.tokenizer.save_path``. - ``collect_stats``: ``train_config.stats_dir``. - ``train``/``publish``: ``train_config.exp_dir``. - - ``infer``: ``infer_config.decode_dir``. - - ``measure``: ``metric_config.decode_dir`` or ``infer_config.decode_dir``. + - ``infer``: ``infer_config.infer_dir``. + - ``measure``: ``metric_config.infer_dir`` or ``infer_config.infer_dir``. If none of the stage-specific paths are configured, it falls back to ``BaseSystem.get_stage_log_dir`` (``train_config.exp_dir`` or @@ -119,10 +119,19 @@ def get_stage_log_dir(self, stage: str) -> Path: if exp_dir: return Path(exp_dir) elif stage == "infer": + infer_dir = getattr(self.infer_config, "infer_dir", None) + if infer_dir: + return Path(infer_dir) decode_dir = getattr(self.infer_config, "decode_dir", None) if decode_dir: return Path(decode_dir) elif stage == "measure": + infer_dir = getattr(self.metric_config, "infer_dir", None) + if infer_dir: + return Path(infer_dir) + infer_dir = getattr(self.infer_config, "infer_dir", None) + if infer_dir: + return Path(infer_dir) decode_dir = getattr(self.metric_config, "decode_dir", None) if decode_dir: return Path(decode_dir) diff --git a/espnet3/systems/asr/transducer_system.py b/espnet3/systems/asr/transducer_system.py index 2cfde9b9bcc3..01198a1b93ad 100644 --- a/espnet3/systems/asr/transducer_system.py +++ b/espnet3/systems/asr/transducer_system.py @@ -29,9 +29,12 @@ class ASRTransducerSystem(ASRSystem): def infer(self, *args, **kwargs): """Run inference on the configured datasets.""" self._reject_stage_args("infer", args, kwargs) + infer_dir = getattr(self.infer_config, "infer_dir", None) + if infer_dir is None: + infer_dir = getattr(self.infer_config, "decode_dir", None) logger.info( - "Inference start | decode_dir=%s", - getattr(self.infer_config, "decode_dir", None), + "Inference start | infer_dir=%s", + infer_dir, ) return inference(self.infer_config) @@ -40,7 +43,7 @@ def inference(config: DictConfig): """Run inference over all configured test sets and write SCP outputs. Args: - config: Hydra/omegaconf configuration with dataset and decode settings. + config: Hydra/omegaconf configuration with dataset and inference settings. """ start = time.perf_counter() set_parallel(config.parallel) @@ -49,9 +52,12 @@ def inference(config: DictConfig): assert len(test_sets) > 0, "No test set found in dataset" assert len(test_sets) == len(set(test_sets)), "Duplicate test key found." + infer_dir = getattr(config, "infer_dir", None) + if infer_dir is None: + infer_dir = getattr(config, "decode_dir", None) logger.info( - "Starting inference | decode_dir=%s test_sets=%s", - getattr(config, "decode_dir", None), + "Starting inference | infer_dir=%s test_sets=%s", + infer_dir, test_sets, ) @@ -78,7 +84,9 @@ def inference(config: DictConfig): ) # create scp files - output_dir = Path(config.decode_dir) / test_name + if infer_dir is None: + raise RuntimeError("infer_dir must be set for inference outputs.") + output_dir = Path(infer_dir) / test_name output_dir.mkdir(parents=True, exist_ok=True) for key, lines in scp_lines.items(): with open(output_dir / f"{key}.scp", "w", encoding="utf-8") as f: From 7eaebcb9229618bb4041d52d2749430fa68cc914 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 29 Jan 2026 00:17:12 -0500 Subject: [PATCH 22/67] Removed unrequired files --- egs3/mini_an4/asr/run_transducer.py | 20 ----- espnet2/uasr/espnet_model.py | 4 +- espnet3/systems/asr/system.py | 9 -- espnet3/systems/asr/transducer_system.py | 100 ----------------------- 4 files changed, 2 insertions(+), 131 deletions(-) delete mode 100644 egs3/mini_an4/asr/run_transducer.py delete mode 100644 espnet3/systems/asr/transducer_system.py diff --git a/egs3/mini_an4/asr/run_transducer.py b/egs3/mini_an4/asr/run_transducer.py deleted file mode 100644 index 460276f7cdac..000000000000 --- a/egs3/mini_an4/asr/run_transducer.py +++ /dev/null @@ -1,20 +0,0 @@ -from egs3.TEMPLATE.asr.run import ( - DEFAULT_STAGES, - build_parser, - main, - parse_cli_and_stage_args, -) -from espnet3.systems.asr.transducer_system import ASRTransducerSystem - -if __name__ == "__main__": - parser = build_parser( - stages=DEFAULT_STAGES, - add_arguments=None, - ) - args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) - - main( - args=args, - system_cls=ASRTransducerSystem, - stages=stages_to_run, - ) diff --git a/espnet2/uasr/espnet_model.py b/espnet2/uasr/espnet_model.py index 67c3db02a7cb..30de009ae390 100644 --- a/espnet2/uasr/espnet_model.py +++ b/espnet2/uasr/espnet_model.py @@ -57,8 +57,8 @@ def __init__( cfg: Optional[Dict] = None, pad: int = 1, sil_token: str = "", - sos_token: str = "", - eos_token: str = "", + sos_token: str = "", + eos_token: str = "", skip_softmax: str2bool = False, use_gumbel: str2bool = False, use_hard_gumbel: str2bool = True, diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index ceb3e69a14c1..bd9a6342338e 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -122,9 +122,6 @@ def get_stage_log_dir(self, stage: str) -> Path: infer_dir = getattr(self.infer_config, "infer_dir", None) if infer_dir: return Path(infer_dir) - decode_dir = getattr(self.infer_config, "decode_dir", None) - if decode_dir: - return Path(decode_dir) elif stage == "measure": infer_dir = getattr(self.metric_config, "infer_dir", None) if infer_dir: @@ -132,12 +129,6 @@ def get_stage_log_dir(self, stage: str) -> Path: infer_dir = getattr(self.infer_config, "infer_dir", None) if infer_dir: return Path(infer_dir) - decode_dir = getattr(self.metric_config, "decode_dir", None) - if decode_dir: - return Path(decode_dir) - decode_dir = getattr(self.infer_config, "decode_dir", None) - if decode_dir: - return Path(decode_dir) return super().get_stage_log_dir(stage) def train(self, *args, **kwargs): diff --git a/espnet3/systems/asr/transducer_system.py b/espnet3/systems/asr/transducer_system.py deleted file mode 100644 index 01198a1b93ad..000000000000 --- a/espnet3/systems/asr/transducer_system.py +++ /dev/null @@ -1,100 +0,0 @@ -"""ASR system implementation and tokenizer training helpers. - -This module adds ASR-specific stages on top of the base system, including -tokenizer training and dataset creation hooks. -""" - -import logging -import time -from pathlib import Path - -from omegaconf import DictConfig - -from espnet3.parallel.parallel import set_parallel -from espnet3.systems.asr.inference import InferenceProvider, TransducerInferenceRunner -from espnet3.systems.asr.system import ASRSystem -from espnet3.systems.base.inference import _collect_scp_lines, _flatten_results -from espnet3.systems.base.inference_runner import AbsInferenceRunner - -logger = logging.getLogger(__name__) - - -class ASRTransducerSystem(ASRSystem): - """ASR Transducer-specific system. - - This system adds: - - Tokenizer training inside train() - """ - - def infer(self, *args, **kwargs): - """Run inference on the configured datasets.""" - self._reject_stage_args("infer", args, kwargs) - infer_dir = getattr(self.infer_config, "infer_dir", None) - if infer_dir is None: - infer_dir = getattr(self.infer_config, "decode_dir", None) - logger.info( - "Inference start | infer_dir=%s", - infer_dir, - ) - return inference(self.infer_config) - - -def inference(config: DictConfig): - """Run inference over all configured test sets and write SCP outputs. - - Args: - config: Hydra/omegaconf configuration with dataset and inference settings. - """ - start = time.perf_counter() - set_parallel(config.parallel) - - test_sets = [test_set.name for test_set in config.dataset.test] - assert len(test_sets) > 0, "No test set found in dataset" - assert len(test_sets) == len(set(test_sets)), "Duplicate test key found." - - infer_dir = getattr(config, "infer_dir", None) - if infer_dir is None: - infer_dir = getattr(config, "decode_dir", None) - logger.info( - "Starting inference | infer_dir=%s test_sets=%s", - infer_dir, - test_sets, - ) - - for test_name in test_sets: - logger.info("===> Processing test set: %s", test_name) - config.test_set = test_name - provider = InferenceProvider(config) - runner = TransducerInferenceRunner(provider=provider, async_mode=False) - if not isinstance(runner, AbsInferenceRunner): - raise TypeError( - f"{type(runner).__name__} must inherit from AbsInferenceRunner" - ) - dataset_length = len(provider.build_dataset(config)) - logger.info("===> Processing %d samples..", dataset_length) - out = runner(list(range(dataset_length))) - if out is None: - raise RuntimeError("Async inference is not supported in this entrypoint.") - results = _flatten_results(out) - scp_lines = _collect_scp_lines( - results, - idx_key=runner.idx_key, - hyp_keys=runner.hyp_key, - ref_keys=runner.ref_key, - ) - - # create scp files - if infer_dir is None: - raise RuntimeError("infer_dir must be set for inference outputs.") - output_dir = Path(infer_dir) / test_name - output_dir.mkdir(parents=True, exist_ok=True) - for key, lines in scp_lines.items(): - with open(output_dir / f"{key}.scp", "w", encoding="utf-8") as f: - f.write("\n".join(lines)) - logger.info( - "Finished test set %s | outputs=%s", - test_name, - output_dir, - ) - - logger.info("Inference finished in %.2fs", time.perf_counter() - start) From bbc9233b902fd6a9faa8d8308771bc405721ecd8 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 29 Jan 2026 00:17:25 -0500 Subject: [PATCH 23/67] decode-dir to infer-dir --- egs3/TEMPLATE/asr/conf/train.yaml | 2 +- egs3/mini_an4/asr/conf/train.yaml | 1 + egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml | 2 +- egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml | 2 +- egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml | 2 +- egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml | 2 +- egs3/mini_an4/asr/conf/train_asr_transformer.yaml | 2 +- egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml | 2 +- egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml | 2 +- .../asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml | 2 +- 10 files changed, 10 insertions(+), 9 deletions(-) create mode 120000 egs3/mini_an4/asr/conf/train.yaml diff --git a/egs3/TEMPLATE/asr/conf/train.yaml b/egs3/TEMPLATE/asr/conf/train.yaml index 2dc73bbd066f..34037dd13b65 100644 --- a/egs3/TEMPLATE/asr/conf/train.yaml +++ b/egs3/TEMPLATE/asr/conf/train.yaml @@ -13,7 +13,7 @@ data_dir: ${recipe_dir}/data exp_tag: asr_template_train exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: /path/to/your/dataset # Dataset creation function (downloads into dataset_dir cache). create_dataset: diff --git a/egs3/mini_an4/asr/conf/train.yaml b/egs3/mini_an4/asr/conf/train.yaml new file mode 120000 index 000000000000..b2b8d88f503f --- /dev/null +++ b/egs3/mini_an4/asr/conf/train.yaml @@ -0,0 +1 @@ +train_transducer_asr_conformer_rnnt_debug.yaml \ No newline at end of file diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml index 425c665a8946..bc433db1c7fe 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_data_aug_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml index 31adfa9cff24..541c4eddd1c2 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml index 4e28805078d6..4e2dda473379 100644 --- a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml @@ -14,7 +14,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_streaming_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml index 9e8138be848f..de44a4c3783f 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml @@ -13,7 +13,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transducer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml index ee90be82c1fc..b6844b8197d3 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml index 3f71890e61fe..0b71bb1b4df8 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml index e1e1bbc0420a..fd3dfa56ab0a 100644 --- a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_lm_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: diff --git a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml index 5ad59263a802..5b2648c7c607 100644 --- a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml @@ -9,7 +9,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_transducer_asr_conformer_rnnt_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +infer_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: From a83dc916cba19b195b5a477098b1db134f3649aa Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 29 Jan 2026 00:19:01 -0500 Subject: [PATCH 24/67] removed run_transducer.py from integration test --- ci/test_integration_espnet3.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index bd484330cd7c..1644e6fd496a 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -47,7 +47,7 @@ done run_with_train_config \ train_transducer_asr_conformer_rnnt_debug.yaml \ - run_transducer.py \ + run.py \ conf/infer_transducer.yaml cd "${cwd}" From d1dde376633da9c4dd6fb33da9a6093fcba4a9c2 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 29 Jan 2026 17:21:18 -0500 Subject: [PATCH 25/67] Added a new config infer.yaml: provider.params I noticed that there is currently no mechanism to configure hyperparameters that control the inference-path. With this settings users can put hyper parameters for these settings directly from the config file. --- espnet3/systems/base/inference.py | 55 +++++++---- test/espnet3/systems/base/test_inference.py | 101 ++++++++++++++++++-- 2 files changed, 131 insertions(+), 25 deletions(-) diff --git a/espnet3/systems/base/inference.py b/espnet3/systems/base/inference.py index ad710a7290b6..e767f1c98328 100644 --- a/espnet3/systems/base/inference.py +++ b/espnet3/systems/base/inference.py @@ -4,11 +4,11 @@ import time from pathlib import Path -from omegaconf import DictConfig +from hydra.utils import instantiate +from omegaconf import DictConfig, OmegaConf from espnet3.parallel.parallel import set_parallel -from espnet3.systems.base.inference_provider import InferenceProvider -from espnet3.systems.base.inference_runner import InferenceRunner, _load_output_fn +from espnet3.systems.base.inference_runner import _load_output_fn logger = logging.getLogger(__name__) @@ -88,15 +88,20 @@ def inference(config: DictConfig): for test_name in test_sets: logger.info("===> Processing test set: %s", test_name) config.test_set = test_name + output_fn_path = getattr(config, "output_fn", None) if not output_fn_path: raise RuntimeError("infer_config.output_fn must be set.") + _load_output_fn(output_fn_path) + input_key = getattr(config, "input_key", None) if input_key is None: raise RuntimeError("infer_config.input_key must be set.") + if isinstance(input_key, (list, tuple)) and not input_key: raise RuntimeError("infer_config.input_key must not be empty.") + output_keys = getattr(config, "output_keys", None) if output_keys is not None: if isinstance(output_keys, str): @@ -105,24 +110,38 @@ def inference(config: DictConfig): output_keys = list(output_keys) if not output_keys: raise RuntimeError("infer_config.output_keys must not be empty.") + idx_key = getattr(config, "idx_key", "uttid") - provider = InferenceProvider( - config, - params={ - "input_key": input_key, - "output_fn_path": output_fn_path, - }, - ) - hyp_keys = output_keys if output_keys is not None else [] batch_size = getattr(config, "batch_size", None) - runner = InferenceRunner( - provider=provider, - async_mode=False, - idx_key=idx_key, - hyp_key=hyp_keys, - batch_size=batch_size, + provider_config = getattr(config, "provider", None) + if provider_config is None: + raise RuntimeError("infer_config.provider must be set.") + if getattr(provider_config, "params", None) is None: + provider_config.params = {} + provider_config.params["input_key"] = input_key + provider_config.params["output_fn_path"] = output_fn_path + provider_params = OmegaConf.to_container(provider_config.params, resolve=True) + + provider = instantiate( + provider_config, + config=config, + params=provider_params, ) + + hyp_keys = output_keys if output_keys is not None else [] + runner_config = getattr(config, "runner", None) + if runner_config is None: + raise RuntimeError("infer_config.runner must be set.") + + runner_kwargs = { + "provider": provider, + "async_mode": False, + "idx_key": idx_key, + "hyp_key": hyp_keys, + "batch_size": batch_size, + } + runner = instantiate(runner_config, **runner_kwargs) if not hasattr(runner, "idx_key"): raise TypeError( f"{type(runner).__name__} must provide inference runner attributes" @@ -132,6 +151,7 @@ def inference(config: DictConfig): out = runner(list(range(dataset_length))) if out is None: raise RuntimeError("Async inference is not supported in this entrypoint.") + # Runner can return nested lists. normalize to flat list. results = _flatten_results(out) if output_keys is None: if not results: @@ -141,6 +161,7 @@ def inference(config: DictConfig): if not output_keys: raise RuntimeError("No output keys found in inference results.") + # Convert output dicts into per-key SCP lines (uttid + value). scp_lines = _collect_scp_lines( results, idx_key=runner.idx_key, diff --git a/test/espnet3/systems/base/test_inference.py b/test/espnet3/systems/base/test_inference.py index 38371d8868fc..4a4b01d2f592 100644 --- a/test/espnet3/systems/base/test_inference.py +++ b/test/espnet3/systems/base/test_inference.py @@ -1,6 +1,7 @@ from pathlib import Path import pytest +from hydra.utils import instantiate as hydra_instantiate from omegaconf import OmegaConf import espnet3.systems.base.inference as inference_mod @@ -32,6 +33,49 @@ def __call__(self, indices): return self._results +runner_factory_results = None + + +def runner_factory(provider, *, async_mode=False, **_kwargs): + return DummyRunner(provider, async_mode=async_mode, results=runner_factory_results) + + +class CaptureProvider: + last_params = None + + def __init__(self, config, *, params): + CaptureProvider.last_params = params + self.config = config + + def build_dataset(self, _config): + return [None] * self.config.mock_dataset_length + + +class CaptureRunner: + results = None + + def __init__(self, provider, **_kwargs): + self.provider = provider + + def __call__(self, _indices): + return CaptureRunner.results + + idx_key = "idx" + + +def _instantiate_without_config(*args, **kwargs): + if not args: + raise RuntimeError("instantiate requires a config argument") + config = args[0] + rest_args = args[1:] + if "config" in kwargs: + cfg = kwargs.pop("config") + return DummyProvider(cfg, **kwargs) + if "provider" in kwargs: + return runner_factory(kwargs["provider"], async_mode=kwargs.get("async_mode")) + return hydra_instantiate(config, *rest_args, **kwargs) + + def _read_scp(path: Path): return path.read_text(encoding="utf-8").splitlines() @@ -46,6 +90,8 @@ def test_inference_writes_scp_outputs(tmp_path, monkeypatch): "output_fn": f"{__name__}.dummy_output_fn", "idx_key": "idx", "mock_dataset_length": 2, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, } ) results = [ @@ -57,12 +103,11 @@ def test_inference_writes_scp_outputs(tmp_path, monkeypatch): def fake_set_parallel(arg): calls["parallel"] = arg - def runner_factory(provider, *, async_mode=False, **_kwargs): - return DummyRunner(provider, async_mode=async_mode, results=results) + global runner_factory_results + runner_factory_results = results monkeypatch.setattr(inference_mod, "set_parallel", fake_set_parallel) - monkeypatch.setattr(inference_mod, "InferenceProvider", DummyProvider) - monkeypatch.setattr(inference_mod, "InferenceRunner", runner_factory) + monkeypatch.setattr(inference_mod, "instantiate", _instantiate_without_config) inference_mod.inference(cfg) @@ -83,15 +128,55 @@ def test_inference_rejects_async_results(tmp_path, monkeypatch): "output_fn": f"{__name__}.dummy_output_fn", "idx_key": "idx", "mock_dataset_length": 1, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, } ) - def runner_factory(provider, *, async_mode=False, **_kwargs): - return DummyRunner(provider, async_mode=async_mode, results=None) + global runner_factory_results + runner_factory_results = None monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) - monkeypatch.setattr(inference_mod, "InferenceProvider", DummyProvider) - monkeypatch.setattr(inference_mod, "InferenceRunner", runner_factory) + monkeypatch.setattr(inference_mod, "instantiate", _instantiate_without_config) with pytest.raises(RuntimeError, match="Async inference is not supported"): inference_mod.inference(cfg) + + +def test_inference_passes_provider_params(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "infer_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "output_fn": f"{__name__}.dummy_output_fn", + "idx_key": "idx", + "mock_dataset_length": 1, + "provider": { + "_target_": f"{__name__}.CaptureProvider", + "params": {"beam": 5, "lang": "en"}, + }, + "runner": {"_target_": f"{__name__}.CaptureRunner"}, + } + ) + results = [{"idx": 0, "hyp": "h0", "ref": "r0"}] + CaptureProvider.last_params = None + CaptureRunner.results = results + + def fake_instantiate(obj, **kwargs): + if "config" in kwargs: + return CaptureProvider(kwargs["config"], params=kwargs["params"]) + return CaptureRunner(kwargs["provider"]) + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + monkeypatch.setattr(inference_mod, "instantiate", fake_instantiate) + + inference_mod.inference(cfg) + + assert CaptureProvider.last_params == { + "beam": 5, + "lang": "en", + "input_key": "speech", + "output_fn_path": f"{__name__}.dummy_output_fn", + } From ad0c6975975da7603dbf2fde3696008be658a909 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 29 Jan 2026 17:48:31 -0500 Subject: [PATCH 26/67] Fixed add_special_tokens - Insert special token after the last token if insert_after is not specified. --- espnet3/systems/asr/tokenizer/sentencepiece.py | 10 ++++++++-- .../systems/asr/tokenizer/test_sentencepiece.py | 9 +++++++++ 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/espnet3/systems/asr/tokenizer/sentencepiece.py b/espnet3/systems/asr/tokenizer/sentencepiece.py index 57751a6f0460..2d1e7da6ef66 100644 --- a/espnet3/systems/asr/tokenizer/sentencepiece.py +++ b/espnet3/systems/asr/tokenizer/sentencepiece.py @@ -162,7 +162,7 @@ def train_sentencepiece( def add_special_tokens( - tokenizer, converter, embedding, special_tokens, insert_after="" + tokenizer, converter, embedding, special_tokens, insert_after=None ): """Add special tokens to the tokenizer. @@ -173,6 +173,9 @@ def add_special_tokens( converter: Sentencepiece converter. embedding: nn.Embedding object. special_tokens (list): List of special tokens. + insert_after (str | None): If provided and found in the current token + list, insert new tokens right after it. If None or not found, + append new tokens to the end of the list. Returns: Tuple( @@ -191,7 +194,10 @@ def add_special_tokens( add_token_list.append(token) # Then append tokens into the token_list and sentencepiece model. - insert_position = token_list.index(insert_after) + 1 + if insert_after is None or insert_after not in token_list: + insert_position = len(token_list) + else: + insert_position = token_list.index(insert_after) + 1 new_token_list = ( token_list[:insert_position] + add_token_list + token_list[insert_position:] ) diff --git a/test/espnet3/systems/asr/tokenizer/test_sentencepiece.py b/test/espnet3/systems/asr/tokenizer/test_sentencepiece.py index 8709e8574af4..d63176664493 100644 --- a/test/espnet3/systems/asr/tokenizer/test_sentencepiece.py +++ b/test/espnet3/systems/asr/tokenizer/test_sentencepiece.py @@ -81,3 +81,12 @@ def test_train_sentencepiece_and_add_special_tokens(tmp_path, monkeypatch): "", "", ] + + new_tokenizer2, new_converter2, new_embedding2 = add_special_tokens( + tokenizer, + converter, + embedding, + [""], + ) + assert new_embedding2.num_embeddings == len(tokens) + 1 + assert new_converter2.token_list[-1] == "" From ed36b1c39cae6bcd7bf27970bb93f151e9c5ad4f Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 30 Jan 2026 00:00:41 -0500 Subject: [PATCH 27/67] Bug fixed for the instantiating part on inference provider. --- espnet3/systems/base/inference.py | 21 ++++---- test/espnet3/systems/base/test_inference.py | 55 ++++++--------------- 2 files changed, 24 insertions(+), 52 deletions(-) diff --git a/espnet3/systems/base/inference.py b/espnet3/systems/base/inference.py index e767f1c98328..d20962bb0bbf 100644 --- a/espnet3/systems/base/inference.py +++ b/espnet3/systems/base/inference.py @@ -117,17 +117,16 @@ def inference(config: DictConfig): provider_config = getattr(config, "provider", None) if provider_config is None: raise RuntimeError("infer_config.provider must be set.") - if getattr(provider_config, "params", None) is None: - provider_config.params = {} - provider_config.params["input_key"] = input_key - provider_config.params["output_fn_path"] = output_fn_path - provider_params = OmegaConf.to_container(provider_config.params, resolve=True) - - provider = instantiate( - provider_config, - config=config, - params=provider_params, - ) + raw_params = getattr(provider_config, "params", {}) or {} + if OmegaConf.is_config(raw_params): + provider_params = OmegaConf.to_container(raw_params, resolve=True) + else: + provider_params = dict(raw_params) + provider_params["input_key"] = input_key + provider_params["output_fn_path"] = output_fn_path + provider_config.params = provider_params + + provider = instantiate(provider_config) hyp_keys = output_keys if output_keys is not None else [] runner_config = getattr(config, "runner", None) diff --git a/test/espnet3/systems/base/test_inference.py b/test/espnet3/systems/base/test_inference.py index 4a4b01d2f592..bbf4faf22e51 100644 --- a/test/espnet3/systems/base/test_inference.py +++ b/test/espnet3/systems/base/test_inference.py @@ -1,7 +1,6 @@ from pathlib import Path import pytest -from hydra.utils import instantiate as hydra_instantiate from omegaconf import OmegaConf import espnet3.systems.base.inference as inference_mod @@ -13,17 +12,22 @@ def dummy_output_fn(*, data, model_output, idx): class DummyProvider: - def __init__(self, config, **kwargs): - self.config = config + def __init__(self, *, params): + self.params = params def build_dataset(self, _config): - return [None] * self.config.mock_dataset_length + return [None] * _config.mock_dataset_length class DummyRunner(InferenceRunner): - def __init__(self, provider, *, async_mode=False, results=None): + results = None + + def __init__(self, provider, *, async_mode=False, results=None, **_kwargs): super().__init__(provider, async_mode=async_mode) - self._results = results if results is not None else None + if results is not None: + self._results = results + else: + self._results = DummyRunner.results @staticmethod def forward(idx, *, dataset, model, **env): @@ -33,22 +37,14 @@ def __call__(self, indices): return self._results -runner_factory_results = None - - -def runner_factory(provider, *, async_mode=False, **_kwargs): - return DummyRunner(provider, async_mode=async_mode, results=runner_factory_results) - - class CaptureProvider: last_params = None - def __init__(self, config, *, params): + def __init__(self, *, params): CaptureProvider.last_params = params - self.config = config def build_dataset(self, _config): - return [None] * self.config.mock_dataset_length + return [None] * _config.mock_dataset_length class CaptureRunner: @@ -63,19 +59,6 @@ def __call__(self, _indices): idx_key = "idx" -def _instantiate_without_config(*args, **kwargs): - if not args: - raise RuntimeError("instantiate requires a config argument") - config = args[0] - rest_args = args[1:] - if "config" in kwargs: - cfg = kwargs.pop("config") - return DummyProvider(cfg, **kwargs) - if "provider" in kwargs: - return runner_factory(kwargs["provider"], async_mode=kwargs.get("async_mode")) - return hydra_instantiate(config, *rest_args, **kwargs) - - def _read_scp(path: Path): return path.read_text(encoding="utf-8").splitlines() @@ -103,11 +86,9 @@ def test_inference_writes_scp_outputs(tmp_path, monkeypatch): def fake_set_parallel(arg): calls["parallel"] = arg - global runner_factory_results - runner_factory_results = results + DummyRunner.results = results monkeypatch.setattr(inference_mod, "set_parallel", fake_set_parallel) - monkeypatch.setattr(inference_mod, "instantiate", _instantiate_without_config) inference_mod.inference(cfg) @@ -133,11 +114,9 @@ def test_inference_rejects_async_results(tmp_path, monkeypatch): } ) - global runner_factory_results - runner_factory_results = None + DummyRunner.results = None monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) - monkeypatch.setattr(inference_mod, "instantiate", _instantiate_without_config) with pytest.raises(RuntimeError, match="Async inference is not supported"): inference_mod.inference(cfg) @@ -164,13 +143,7 @@ def test_inference_passes_provider_params(tmp_path, monkeypatch): CaptureProvider.last_params = None CaptureRunner.results = results - def fake_instantiate(obj, **kwargs): - if "config" in kwargs: - return CaptureProvider(kwargs["config"], params=kwargs["params"]) - return CaptureRunner(kwargs["provider"]) - monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) - monkeypatch.setattr(inference_mod, "instantiate", fake_instantiate) inference_mod.inference(cfg) From ce03215be23b0923d07bb9b493b68d781058f902 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 00:33:49 -0500 Subject: [PATCH 28/67] Fixed issues --- espnet3/components/data/data_organizer.py | 5 +- espnet3/systems/asr/system.py | 2 +- espnet3/utils/logging.py | 384 ------------------ espnet3/utils/stages_utils.py | 2 +- .../test_model_with_optim_scheduler.py | 2 +- 5 files changed, 4 insertions(+), 391 deletions(-) delete mode 100644 espnet3/utils/logging.py diff --git a/espnet3/components/data/data_organizer.py b/espnet3/components/data/data_organizer.py index 878e04fc2e64..2f185ebbafd3 100644 --- a/espnet3/components/data/data_organizer.py +++ b/espnet3/components/data/data_organizer.py @@ -7,10 +7,7 @@ from omegaconf import DictConfig from espnet2.train.preprocessor import AbsPreprocessor -from espnet3.components.data.dataset import CombinedDataset, DatasetWithTransform, do_nothing - -from hydra.utils import instantiate -from omegaconf import DictConfig +from espnet3.components.data.dataset import CombinedDataset, DatasetWithTransform @dataclass diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index 393564ae8f60..715c88897957 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -148,7 +148,7 @@ def train(self, *args, **kwargs): raise RuntimeError("train_config.dataset_dir must be set for training.") # Train tokenizer if not trained previously - if not self._tokenizer_exists(): + if not self._has_tokenizer(): self.train_tokenizer() # Proceed with standard training diff --git a/espnet3/utils/logging.py b/espnet3/utils/logging.py deleted file mode 100644 index 53941145e026..000000000000 --- a/espnet3/utils/logging.py +++ /dev/null @@ -1,384 +0,0 @@ -"""Logging helpers for espnet3 experiments.""" - -from __future__ import annotations - -import logging -import os -import shlex -import subprocess -import sys -from datetime import datetime -from pathlib import Path -from shutil import which -from typing import Iterable, Mapping - -LOG_FORMAT = "%(asctime)s | %(levelname)s | %(name)s | %(message)s" -DATE_FORMAT = "%Y-%m-%d %H:%M:%S" - - -def _next_rotated_log_path(target: Path) -> Path: - """Return the next available rotated log path (e.g., run1.log).""" - suffixes = target.suffixes - suffix = "".join(suffixes) - base = target.name[: -len(suffix)] if suffix else target.name - - index = 1 - while True: - candidate = target.with_name(f"{base}{index}{suffix}") - if not candidate.exists(): - return candidate - index += 1 - - -def configure_logging( - *, - log_dir: Path | None = None, - level: int = logging.INFO, - filename: str = "run.log", -) -> logging.Logger: - """Configure logging for an ESPnet3 run. - - This sets up: - - A root logger with a stream handler (console). - - An optional file handler at `log_dir/filename`. - - Warning capture into the logging system. - - Args: - log_dir (Path | None): Directory to store the log file. - If None, only console logging is configured. - level (int): Logging level (e.g., logging.INFO). - filename (str): Log file name when `log_dir` is provided. - - Returns: - logging.Logger: Logger instance named "espnet3". - """ - root = logging.getLogger() - root.setLevel(level) - - formatter = logging.Formatter(fmt=LOG_FORMAT, datefmt=DATE_FORMAT) - - if not any(isinstance(h, logging.StreamHandler) for h in root.handlers): - stream = logging.StreamHandler() - stream.setFormatter(formatter) - root.addHandler(stream) - - if log_dir is not None: - log_dir.mkdir(parents=True, exist_ok=True) - target = (log_dir / filename).resolve() - has_file = any( - isinstance(h, logging.FileHandler) - and getattr(h, "baseFilename", None) - and Path(h.baseFilename).resolve() == target - for h in root.handlers - ) - if not has_file: - if target.exists(): - rotated = _next_rotated_log_path(target) - os.replace(target, rotated) - file_handler = logging.FileHandler(target) - file_handler.setFormatter(formatter) - root.addHandler(file_handler) - - logging.captureWarnings(True) - return logging.getLogger("espnet3") - - -def set_stage_log_handler( - logger: logging.Logger, - log_dir: Path | None, - *, - filename: str, -) -> Path | None: - """Attach a file handler for a stage log, replacing any prior stage handler. - - This function adds a new file handler to the root logger and removes any - previously installed stage handler (identified via ``_espnet3_stage_log``). - If a log file already exists at the target path, it is rotated (e.g., - ``train.log`` -> ``train1.log``) before creating the new handler. - - Args: - logger (logging.Logger): Logger used to emit logs. - The handler is attached to the root logger so the logger hierarchy - continues to work as expected. - log_dir (Path | None): Directory that should receive the stage log. - If None, no handler is installed and None is returned. - filename (str): Log filename to create within ``log_dir``. - - Returns: - Path | None: Resolved log file path when installed, otherwise None. - """ - if log_dir is None: - return None - - log_dir.mkdir(parents=True, exist_ok=True) - target = (log_dir / filename).resolve() - - root = logging.getLogger() - for handler in list(root.handlers): - if getattr(handler, "_espnet3_stage_log", False): - root.removeHandler(handler) - handler.close() - - formatter = logging.Formatter(fmt=LOG_FORMAT, datefmt=DATE_FORMAT) - if target.exists(): - rotated = _next_rotated_log_path(target) - os.replace(target, rotated) - file_handler = logging.FileHandler(target) - file_handler.setFormatter(formatter) - file_handler._espnet3_stage_log = True - root.addHandler(file_handler) - - return target - - -def _run_git_command(cmd: list[str], cwd: Path | None) -> str | None: - """Run a git command and return stdout, or None on failure.""" - try: - completed = subprocess.run( - cmd, - cwd=cwd, - check=True, - capture_output=True, - text=True, - ) - return completed.stdout.strip() - except Exception: - return None - - -def get_git_metadata(cwd: Path | None = None) -> dict[str, str]: - """Return git metadata for the current repository. - - This attempts to read commit hash, short hash, branch name, and worktree - status from the git repository rooted at `cwd`. - - Args: - cwd (Path | None): Directory within the target git repo. - - Returns: - dict[str, str]: Collected metadata keys, possibly including: - - "commit": Full commit hash. - - "short_commit": Abbreviated commit hash. - - "branch": Current branch name. - - "worktree": "clean", "dirty", or "unknown". - """ - cwd = cwd or Path.cwd() - head = _run_git_command(["git", "rev-parse", "HEAD"], cwd) - branch = _run_git_command(["git", "rev-parse", "--abbrev-ref", "HEAD"], cwd) - short = _run_git_command(["git", "rev-parse", "--short", "HEAD"], cwd) - status = _run_git_command(["git", "status", "--short"], cwd) - - dirty = "clean" - if status is None: - dirty = "unknown" - elif status: - dirty = "dirty" - - meta: dict[str, str] = {} - if head: - meta["commit"] = head - if short: - meta["short_commit"] = short - if branch: - meta["branch"] = branch - meta["worktree"] = dirty - return meta - - -def format_command(argv: Iterable[str] | None = None) -> str: - """Format command arguments into a shell-escaped string.""" - argv = list(argv) if argv is not None else sys.argv - return " ".join(shlex.quote(str(a)) for a in argv) - - -def _run_pip_freeze() -> str | None: - """Return `pip freeze` output, or None on failure.""" - try: - completed = subprocess.run( - [sys.executable, "-m", "pip", "freeze"], - check=True, - capture_output=True, - text=True, - ) - return completed.stdout.strip() - except Exception: - if which("uv") is None: - return None - try: - completed = subprocess.run( - ["uv", "pip", "freeze"], - check=True, - capture_output=True, - text=True, - ) - return completed.stdout.strip() - except Exception: - return None - - -def _get_log_dir_from_logger(logger: logging.Logger) -> Path | None: - """Return the log directory from any configured file handler.""" - for handler in logger.handlers: - if isinstance(handler, logging.FileHandler) and getattr( - handler, "baseFilename", None - ): - return Path(handler.baseFilename).resolve().parent - - root = logging.getLogger() - for handler in root.handlers: - if isinstance(handler, logging.FileHandler) and getattr( - handler, "baseFilename", None - ): - return Path(handler.baseFilename).resolve().parent - - return None - - -def _write_requirements_snapshot(logger: logging.Logger) -> None: - """Write a requirements snapshot alongside the configured log file.""" - log_dir = _get_log_dir_from_logger(logger) - if log_dir is None: - logger.warning("Skipping requirements export: no file logger configured.") - return - - requirements = _run_pip_freeze() - if requirements is None: - logger.warning("Failed to export requirements via pip freeze.") - return - - target = log_dir / "requirements.txt" - target.write_text(requirements + "\n", encoding="utf-8") - logger.info("Wrote requirements snapshot: %s", target) - - -def log_run_metadata( - logger: logging.Logger, - *, - argv: Iterable[str] | None = None, - workdir: Path | None = None, - configs: Mapping[str, Path | None] | None = None, - write_requirements: bool = False, -) -> None: - """Log runtime metadata for the current run. - - Logged fields include: - - Start timestamp. - - Python executable and command-line arguments. - - Working directory. - - Python version. - - Config paths (if provided). - - Git metadata (commit/branch/dirty), when available. - - Optional requirements snapshot (pip freeze). - - Args: - logger (logging.Logger): Logger used to emit metadata. - argv (Iterable[str] | None): Command arguments; defaults to sys.argv. - workdir (Path | None): Working directory to report. - configs (Mapping[str, Path | None] | None): Named config paths to log. - write_requirements (bool): If True, export pip freeze output to - requirements.txt alongside the log file. - """ - logger.info("=== ESPnet3 run started: %s ===", datetime.now().isoformat()) - logger.info("Command: %s %s", sys.executable, format_command(argv)) - logger.info("Python: %s", sys.version.replace("\n", " ")) - - cwd = workdir or Path.cwd() - logger.info("Working directory: %s", cwd) - - if configs: - for name, path in configs.items(): - if path is None: - continue - logger.info("%s config: %s", name, Path(path).resolve()) - - git_info = get_git_metadata(cwd) - if git_info: - git_parts = [f"{k}={v}" for k, v in git_info.items()] - logger.info("Git: %s", ", ".join(git_parts)) - - if write_requirements: - _write_requirements_snapshot(logger) - - -def _collect_env( - *, - prefixes: Iterable[str] | None = None, - keys: Iterable[str] | None = None, -) -> dict[str, str]: - """Collect environment variables matching prefixes or explicit keys. - - Args: - prefixes (Iterable[str] | None): Prefixes to match (e.g., "CUDA_"). - keys (Iterable[str] | None): Exact variable names to include. - - Returns: - dict[str, str]: Sorted environment variables that match. - """ - prefixes = tuple(prefixes or ()) - key_set = {k for k in (keys or ())} - collected: dict[str, str] = {} - for name, value in os.environ.items(): - if name in key_set or any(name.startswith(prefix) for prefix in prefixes): - collected[name] = value - return dict(sorted(collected.items())) - - -def log_env_metadata( - logger: logging.Logger, - *, - cluster_prefixes: Iterable[str] | None = None, - runtime_prefixes: Iterable[str] | None = None, - runtime_keys: Iterable[str] | None = None, -) -> None: - """Log selected cluster and runtime environment variables. - - The output includes two blocks: - - Cluster environment variables (scheduler/runtime IDs). - - Runtime environment variables (CUDA/NCCL/OMP/PATH, etc.). - - Args: - logger (logging.Logger): Logger used to emit metadata. - cluster_prefixes (Iterable[str] | None): Prefixes for cluster variables. - runtime_prefixes (Iterable[str] | None): Prefixes for runtime variables. - runtime_keys (Iterable[str] | None): Explicit runtime keys to include. - """ - cluster_prefixes = cluster_prefixes or ( - "SLURM_", - "PBS_", - "LSF_", - "SGE_", - "COBALT_", - "OMPI_", - "PMI_", - "MPI_", - ) - runtime_prefixes = runtime_prefixes or ( - "NCCL_", - "CUDA_", - "ROCM_", - "OMP_", - "MKL_", - "OPENBLAS_", - "UCX_", - "NVIDIA_", - ) - runtime_keys = runtime_keys or ( - "PATH", - "PYTHONPATH", - "LD_LIBRARY_PATH", - "CUDA_VISIBLE_DEVICES", - "RANK", - "LOCAL_RANK", - "NODE_RANK", - "WORLD_SIZE", - "MASTER_ADDR", - "MASTER_PORT", - ) - - cluster_env = _collect_env(prefixes=cluster_prefixes) - runtime_env = _collect_env(prefixes=runtime_prefixes, keys=runtime_keys) - - cluster_dump = "\n".join(f"{k}={v}" for k, v in cluster_env.items()) or "(none)" - runtime_dump = "\n".join(f"{k}={v}" for k, v in runtime_env.items()) or "(none)" - logger.info("Cluster env:\n%s", cluster_dump) - logger.info("Runtime env:\n%s", runtime_dump) diff --git a/espnet3/utils/stages_utils.py b/espnet3/utils/stages_utils.py index 1150e01a1e5d..b7a2f9357332 100644 --- a/espnet3/utils/stages_utils.py +++ b/espnet3/utils/stages_utils.py @@ -68,7 +68,7 @@ def run_stages( continue if stage_log_dir_fn is not None: - from espnet3.utils.logging import set_stage_log_handler + from espnet3.utils.logging_utils import set_stage_log_handler log_dir = stage_log_dir_fn(stage) set_stage_log_handler( diff --git a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py index f016ae33b3fc..ffd4e84ca6f0 100644 --- a/test/espnet3/components/modeling/test_model_with_optim_scheduler.py +++ b/test/espnet3/components/modeling/test_model_with_optim_scheduler.py @@ -159,7 +159,7 @@ def test_reduce_on_plateau_monitor_from_config(): def test_val_scheduler_criterion_sets_epoch(): config = OmegaConf.create( { - "optim": {"_target_": "torch.optim.Adam", "lr": 0.01}, + "optimizer": {"_target_": "torch.optim.Adam", "lr": 0.01}, "scheduler": { "_target_": "torch.optim.lr_scheduler.StepLR", "step_size": 5, From 1e54beeb83a164c4240b066ca35e0baacb4c9c91 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 01:04:34 -0500 Subject: [PATCH 29/67] Fixed namings of a mini-an4 recipe --- .../asr/conf/{infer.yaml => inference.yaml} | 7 +- .../asr/conf/{measure.yaml => metrics.yaml} | 4 +- egs3/TEMPLATE/asr/conf/train.yaml | 6 +- egs3/TEMPLATE/asr/readme.md | 2 +- egs3/TEMPLATE/asr/run.py | 39 ++++--- egs3/mini_an4/asr/src/create_dataset.py | 2 +- .../asr/src/{infer.py => inference.py} | 0 espnet3/utils/logging_utils.py | 110 ++++++++---------- 8 files changed, 81 insertions(+), 89 deletions(-) rename egs3/TEMPLATE/asr/conf/{infer.yaml => inference.yaml} (82%) rename egs3/TEMPLATE/asr/conf/{measure.yaml => metrics.yaml} (87%) rename egs3/mini_an4/asr/src/{infer.py => inference.py} (100%) diff --git a/egs3/TEMPLATE/asr/conf/infer.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml similarity index 82% rename from egs3/TEMPLATE/asr/conf/infer.yaml rename to egs3/TEMPLATE/asr/conf/inference.yaml index bd0a30da85f6..a4fd783ea7e3 100644 --- a/egs3/TEMPLATE/asr/conf/infer.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -7,7 +7,7 @@ data_dir: ${recipe_dir}/data dataset_dir: /path/to/your/dataset exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference # Dataset definition for test splits only. dataset: @@ -29,6 +29,11 @@ model: input_key: speech output_fn: src.infer.output_fn +provider: + _target_: espnet3.systems.base.inference_provider.InferenceProvider +runner: + _target_: espnet3.systems.base.inference_runner.InferenceRunner + # Parallel execution used during data loading / scoring (defaults to local). parallel: env: local diff --git a/egs3/TEMPLATE/asr/conf/measure.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml similarity index 87% rename from egs3/TEMPLATE/asr/conf/measure.yaml rename to egs3/TEMPLATE/asr/conf/metrics.yaml index 89f33fbe9adf..79a340bf1e96 100644 --- a/egs3/TEMPLATE/asr/conf/measure.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -8,12 +8,12 @@ exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: /path/to/your/dataset # Dataset definition for test splits only (used to enumerate test names). dataset: - _target_: espnet3.components.data_organizer.DataOrganizer + _target_: espnet3.components.data.data_organizer.DataOrganizer test: - name: test-clean dataset: diff --git a/egs3/TEMPLATE/asr/conf/train.yaml b/egs3/TEMPLATE/asr/conf/train.yaml index 34037dd13b65..0e067035dd16 100644 --- a/egs3/TEMPLATE/asr/conf/train.yaml +++ b/egs3/TEMPLATE/asr/conf/train.yaml @@ -13,7 +13,7 @@ data_dir: ${recipe_dir}/data exp_tag: asr_template_train exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: /path/to/your/dataset # Dataset creation function (downloads into dataset_dir cache). create_dataset: @@ -22,7 +22,7 @@ create_dataset: # Dataset definition for training/validation splits. dataset: - _target_: espnet3.components.data_organizer.DataOrganizer + _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train-split dataset: @@ -87,7 +87,7 @@ dataloader: # Optimizer and scheduler are intentionally lightweight defaults. -optim: +optimizer: _target_: torch.optim.Adam lr: 0.002 weight_decay: 0.000001 diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md index 843e40d97ddf..829d5123f694 100644 --- a/egs3/TEMPLATE/asr/readme.md +++ b/egs3/TEMPLATE/asr/readme.md @@ -20,7 +20,7 @@ python run.py --stages train --train_tokenizer --collect_stats \ python run.py --stages infer --infer_config conf/infer.yaml # 4) Score -python run.py --stages measure --measure_config conf/measure.yaml +python run.py --stages metric --metric_config conf/metric.yaml ``` All hyper-parameters are stored in `configs/` and can be overridden using diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 9072effdbee6..a46b73592d67 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -10,9 +10,9 @@ from omegaconf import OmegaConf -from espnet3.utils.config import load_config_with_defaults -from espnet3.utils.logging import configure_logging, log_env_metadata, log_run_metadata -from espnet3.utils.stages import resolve_stages, run_stages +from espnet3.utils.config_utils import load_config_with_defaults +from espnet3.utils.logging_utils import configure_logging, log_env_metadata, log_run_metadata +from espnet3.utils.stages_utils import resolve_stages, run_stages # Default stage list (can be extended/overridden by callers) DEFAULT_STAGES: List[str] = [ @@ -21,8 +21,9 @@ "collect_stats", "train", "infer", - "measure", - "publish", + "metric", + "pack_model", + "upload_model" ] # Type alias for a System class @@ -60,10 +61,10 @@ def build_parser( help="Hydra config for inference/decoding stage.", ) parser.add_argument( - "--measure_config", + "--metric_config", default=None, type=Path, - help="Hydra config for measure/scoring stage.", + help="Hydra config for metric/scoring stage.", ) parser.add_argument( "--dry_run", @@ -123,10 +124,10 @@ def main( if args.infer_config is None else load_config_with_defaults(args.infer_config) ) - measure_config = ( + metric_config = ( None - if args.measure_config is None - else load_config_with_defaults(args.measure_config) + if args.metric_config is None + else load_config_with_defaults(args.metric_config) ) logger = configure_logging() @@ -137,7 +138,7 @@ def main( system = system_cls( train_config=train_config, infer_config=infer_config, - measure_config=measure_config, + metric_config=metric_config, ) # ----------------------------------------- @@ -156,7 +157,7 @@ def main( } required_configs = {} required_configs.update({stage: train_config for stage in pretrain_stages}) - required_configs.update({"infer": infer_config, "measure": measure_config}) + required_configs.update({"infer": infer_config, "metric": metric_config}) missing = [ s for s in stages_to_run @@ -166,7 +167,7 @@ def main( missing_str = ", ".join(missing) raise ValueError( f"Config not provided for stage(s): {missing_str}. " - "Use --train_config/--infer_config/--measure_config." + "Use --train_config/--infer_config/--metric_config." ) run_stages( system=system, @@ -178,7 +179,7 @@ def main( args=args, train_config=train_config, infer_config=infer_config, - measure_config=measure_config, + metric_config=metric_config, ), ) @@ -189,7 +190,7 @@ def _log_stage_metadata( args: argparse.Namespace, train_config, infer_config, - measure_config, + metric_config, ) -> None: log_run_metadata( logger, @@ -197,7 +198,7 @@ def _log_stage_metadata( configs={ "train": Path(args.train_config) if args.train_config else None, "infer": Path(args.infer_config) if args.infer_config else None, - "measure": Path(args.measure_config) if args.measure_config else None, + "metric": Path(args.metric_config) if args.metric_config else None, }, write_requirements=args.write_requirements, ) @@ -210,10 +211,10 @@ def _log_stage_metadata( logger.info( "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) ) - if measure_config is not None: + if metric_config is not None: logger.info( - "Measure config content:\n%s", - OmegaConf.to_yaml(measure_config, resolve=True), + "metric config content:\n%s", + OmegaConf.to_yaml(metric_config, resolve=True), ) diff --git a/egs3/mini_an4/asr/src/create_dataset.py b/egs3/mini_an4/asr/src/create_dataset.py index 386c5688a658..a10eb750047f 100644 --- a/egs3/mini_an4/asr/src/create_dataset.py +++ b/egs3/mini_an4/asr/src/create_dataset.py @@ -11,7 +11,7 @@ from pathlib import Path from typing import Iterable -from espnet3.utils.download import extract_targz, setup_logger +from espnet3.utils.download_utils import extract_targz, setup_logger LOGGER = logging.getLogger(__name__) diff --git a/egs3/mini_an4/asr/src/infer.py b/egs3/mini_an4/asr/src/inference.py similarity index 100% rename from egs3/mini_an4/asr/src/infer.py rename to egs3/mini_an4/asr/src/inference.py diff --git a/espnet3/utils/logging_utils.py b/espnet3/utils/logging_utils.py index e416425a21b9..53941145e026 100644 --- a/espnet3/utils/logging_utils.py +++ b/espnet3/utils/logging_utils.py @@ -43,20 +43,6 @@ def configure_logging( - An optional file handler at `log_dir/filename`. - Warning capture into the logging system. - Example usage: - ```python - from pathlib import Path - from espnet3.utils.logging_utils import configure_logging - - logger = configure_logging(log_dir=Path("exp/run1"), level=logging.INFO) - logger.info("hello") - ``` - - Example log output: - ``` - 2026-02-04 10:15:22 | INFO | espnet3 | hello - ``` - Args: log_dir (Path | None): Directory to store the log file. If None, only console logging is configured. @@ -97,6 +83,54 @@ def configure_logging( return logging.getLogger("espnet3") +def set_stage_log_handler( + logger: logging.Logger, + log_dir: Path | None, + *, + filename: str, +) -> Path | None: + """Attach a file handler for a stage log, replacing any prior stage handler. + + This function adds a new file handler to the root logger and removes any + previously installed stage handler (identified via ``_espnet3_stage_log``). + If a log file already exists at the target path, it is rotated (e.g., + ``train.log`` -> ``train1.log``) before creating the new handler. + + Args: + logger (logging.Logger): Logger used to emit logs. + The handler is attached to the root logger so the logger hierarchy + continues to work as expected. + log_dir (Path | None): Directory that should receive the stage log. + If None, no handler is installed and None is returned. + filename (str): Log filename to create within ``log_dir``. + + Returns: + Path | None: Resolved log file path when installed, otherwise None. + """ + if log_dir is None: + return None + + log_dir.mkdir(parents=True, exist_ok=True) + target = (log_dir / filename).resolve() + + root = logging.getLogger() + for handler in list(root.handlers): + if getattr(handler, "_espnet3_stage_log", False): + root.removeHandler(handler) + handler.close() + + formatter = logging.Formatter(fmt=LOG_FORMAT, datefmt=DATE_FORMAT) + if target.exists(): + rotated = _next_rotated_log_path(target) + os.replace(target, rotated) + file_handler = logging.FileHandler(target) + file_handler.setFormatter(formatter) + file_handler._espnet3_stage_log = True + root.addHandler(file_handler) + + return target + + def _run_git_command(cmd: list[str], cwd: Path | None) -> str | None: """Run a git command and return stdout, or None on failure.""" try: @@ -236,34 +270,6 @@ def log_run_metadata( - Git metadata (commit/branch/dirty), when available. - Optional requirements snapshot (pip freeze). - Example usage: - ```python - from pathlib import Path - from espnet3.utils.logging_utils import configure_logging, log_run_metadata - - logger = configure_logging(log_dir=Path("exp/run1")) - log_run_metadata( - logger, - argv=["espnet3-train", "--config", "conf/train.yaml"], - workdir=Path("/home/user/espnet3"), - configs={"train": Path("conf/train.yaml")}, - ) - ``` - - Example log output (wrapped for readability, <= 88 chars): - ``` - 2026-02-04 10:15:22 | INFO | espnet3 | === ESPnet3 run started: \ - 2026-02-04T10:15:22 === - 2026-02-04 10:15:22 | INFO | espnet3 | Command: /usr/bin/python3 \ - espnet3-train --config conf/train.yaml - 2026-02-04 10:15:22 | INFO | espnet3 | Python: 3.10.12 (GCC 11.4.0) - 2026-02-04 10:15:22 | INFO | espnet3 | Working directory: /home/user/espnet3 - 2026-02-04 10:15:22 | INFO | espnet3 | train config: /home/user/espnet3/conf/\ - train.yaml - 2026-02-04 10:15:22 | INFO | espnet3 | Git: commit=0123456789abcdef, \ - short_commit=0123456, branch=main, worktree=clean - ``` - Args: logger (logging.Logger): Logger used to emit metadata. argv (Iterable[str] | None): Command arguments; defaults to sys.argv. @@ -330,26 +336,6 @@ def log_env_metadata( - Cluster environment variables (scheduler/runtime IDs). - Runtime environment variables (CUDA/NCCL/OMP/PATH, etc.). - Example usage: - ```python - from pathlib import Path - from espnet3.utils.logging_utils import configure_logging, log_env_metadata - - logger = configure_logging(log_dir=Path("exp/run1")) - log_env_metadata(logger) - ``` - - Example log output: - ``` - 2026-02-04 10:15:22 | INFO | espnet3 | Cluster env: - SLURM_JOB_ID=12345 - SLURM_PROCID=0 - 2026-02-04 10:15:22 | INFO | espnet3 | Runtime env: - CUDA_VISIBLE_DEVICES=0 - NCCL_DEBUG=INFO - PATH=/usr/local/bin:/usr/bin:/bin - ``` - Args: logger (logging.Logger): Logger used to emit metadata. cluster_prefixes (Iterable[str] | None): Prefixes for cluster variables. From 7ce67dcb7ed5f755c4cde716f67cb361a44b4e69 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 01:09:22 -0500 Subject: [PATCH 30/67] Fixed config entries for mini-an4 --- egs3/mini_an4/asr/conf/infer_transducer.yaml | 28 +++++++++---------- .../asr/conf/{infer.yaml => inference.yaml} | 9 ++++-- .../asr/conf/{measure.yaml => metric.yaml} | 2 +- .../conf/train_asr_rnn_data_aug_debug.yaml | 4 +-- .../asr/conf/train_asr_rnn_debug.yaml | 4 +-- .../asr/conf/train_asr_streaming_debug.yaml | 4 +-- .../asr/conf/train_asr_transducer_debug.yaml | 4 +-- .../asr/conf/train_asr_transformer.yaml | 4 +-- .../asr/conf/train_asr_transformer_debug.yaml | 4 +-- .../mini_an4/asr/conf/train_lm_rnn_debug.yaml | 4 +-- ...n_transducer_asr_conformer_rnnt_debug.yaml | 4 +-- egs3/mini_an4/asr/run.sh | 2 +- 12 files changed, 39 insertions(+), 34 deletions(-) rename egs3/mini_an4/asr/conf/{infer.yaml => inference.yaml} (74%) rename egs3/mini_an4/asr/conf/{measure.yaml => metric.yaml} (94%) diff --git a/egs3/mini_an4/asr/conf/infer_transducer.yaml b/egs3/mini_an4/asr/conf/infer_transducer.yaml index b47dbbc3dd85..1362e5c1c120 100644 --- a/egs3/mini_an4/asr/conf/infer_transducer.yaml +++ b/egs3/mini_an4/asr/conf/infer_transducer.yaml @@ -4,21 +4,21 @@ recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 - -dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer - test: - - name: test - dataset: - _target_: src.dataset.MiniAN4Dataset - manifest_path: ${dataset_dir}/manifest/test.tsv - -parallel: - env: local - n_workers: 1 - + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + test: + - name: test + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/test.tsv + +parallel: + env: local + n_workers: 1 + model: _target_: espnet2.bin.asr_transducer_inference.Speech2Text asr_train_config: ${exp_dir}/config.yaml diff --git a/egs3/mini_an4/asr/conf/infer.yaml b/egs3/mini_an4/asr/conf/inference.yaml similarity index 74% rename from egs3/mini_an4/asr/conf/infer.yaml rename to egs3/mini_an4/asr/conf/inference.yaml index b0ef536dc3ab..9a670139405b 100644 --- a/egs3/mini_an4/asr/conf/infer.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -4,7 +4,7 @@ recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 dataset: @@ -27,4 +27,9 @@ model: ctc_weight: 0.3 input_key: speech -output_fn: src.infer.output_fn +output_fn: src.inference.output_fn + +provider: + _target_: espnet3.systems.base.inference_provider.InferenceProvider +runner: + _target_: espnet3.systems.base.inference_runner.InferenceRunner diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/metric.yaml similarity index 94% rename from egs3/mini_an4/asr/conf/measure.yaml rename to egs3/mini_an4/asr/conf/metric.yaml index 07e2943a04d2..53f7a4b123f2 100644 --- a/egs3/mini_an4/asr/conf/measure.yaml +++ b/egs3/mini_an4/asr/conf/metric.yaml @@ -6,7 +6,7 @@ exp_tag: ${load_yaml:conf/train.yaml,exp_tag} exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml index bc433db1c7fe..54cf01da423c 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_data_aug_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -88,7 +88,7 @@ dataloader: -optim: +optimizer: _target_: torch.optim.Adam lr: 0.001 weight_decay: 0.0 diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml index 541c4eddd1c2..fdab0da4b793 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -88,7 +88,7 @@ dataloader: -optim: +optimizer: _target_: torch.optim.Adam lr: 0.001 weight_decay: 0.0 diff --git a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml index 4e2dda473379..a459f0cd9226 100644 --- a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml @@ -14,7 +14,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_streaming_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -78,7 +78,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml index de44a4c3783f..82536888afc7 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml @@ -13,7 +13,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transducer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -77,7 +77,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml index b6844b8197d3..c3a258891b39 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -74,7 +74,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml index 0b71bb1b4df8..959671a5c564 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -74,7 +74,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml index fd3dfa56ab0a..e88e9556565e 100644 --- a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml @@ -10,7 +10,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_lm_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -74,7 +74,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml index 5b2648c7c607..375b80a6b1db 100644 --- a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml +++ b/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml @@ -9,7 +9,7 @@ data_dir: ${recipe_dir}/data exp_tag: train_transducer_asr_conformer_rnnt_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -infer_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/infer dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -73,7 +73,7 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -optim: +optimizer: _target_: torch.optim.Adam lr: 0.005 diff --git a/egs3/mini_an4/asr/run.sh b/egs3/mini_an4/asr/run.sh index 254efce433cf..983a18cc6fe8 100644 --- a/egs3/mini_an4/asr/run.sh +++ b/egs3/mini_an4/asr/run.sh @@ -11,5 +11,5 @@ ${python} run.py \ --stages all \ --train_config conf/train.yaml \ --infer_config conf/infer.yaml \ - --measure_config conf/measure.yaml \ + --metric_config conf/metric.yaml \ "$@" From d84321861aa5e9ce22e6d758ed5a08ce80657031 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 01:10:20 -0500 Subject: [PATCH 31/67] Fixed ci script --- ci/test_integration_espnet3.sh | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index 1644e6fd496a..e52a62fc1beb 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -29,7 +29,7 @@ run_with_train_config() { --stages create_dataset train_tokenizer collect_stats train infer measure \ --train_config conf/train.yaml \ --infer_config "${infer_config}" \ - --measure_config conf/measure.yaml + --metric_config conf/metric.yaml rm -rf exp data } @@ -42,12 +42,12 @@ debug_configs=( ) for train_config in "${debug_configs[@]}"; do - run_with_train_config "${train_config}" run.py conf/infer.yaml + run_with_train_config "${train_config}" run.py conf/inference.yaml done run_with_train_config \ train_transducer_asr_conformer_rnnt_debug.yaml \ run.py \ - conf/infer_transducer.yaml + conf/inference_transducer.yaml cd "${cwd}" From b9bcf149b9e802998331fb98089640090604bdb6 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 01:12:22 -0500 Subject: [PATCH 32/67] Fixed integration config --- .../asr/conf/inference_transducer.yaml | 29 +++++++++++++++++++ 1 file changed, 29 insertions(+) create mode 100644 egs3/mini_an4/asr/conf/inference_transducer.yaml diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml new file mode 100644 index 000000000000..1362e5c1c120 --- /dev/null +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -0,0 +1,29 @@ +# Mini AN4 ASR inference config for ESPnet3 integration tests. + +recipe_dir: . +data_dir: ${recipe_dir}/data +exp_tag: ${load_yaml:conf/train.yaml,exp_tag} +exp_dir: ${recipe_dir}/exp/${exp_tag} +inference_dir: ${exp_dir}/infer +dataset_dir: ${data_dir}/mini_an4 + +dataset: + _target_: espnet3.components.data.data_organizer.DataOrganizer + test: + - name: test + dataset: + _target_: src.dataset.MiniAN4Dataset + manifest_path: ${dataset_dir}/manifest/test.tsv + +parallel: + env: local + n_workers: 1 + +model: + _target_: espnet2.bin.asr_transducer_inference.Speech2Text + asr_train_config: ${exp_dir}/config.yaml + asr_model_file: ${exp_dir}/last.ckpt + beam_size: 1 + +input_key: speech +output_fn: src.infer.output_fn_transducer From 2d54bb60c81d405e8c75d86a7b4f35d5d20860fe Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 5 Feb 2026 01:25:13 -0500 Subject: [PATCH 33/67] measure -> metric --- ci/test_integration_espnet3.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index e52a62fc1beb..c656c34e9681 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -26,7 +26,7 @@ run_with_train_config() { ln -sfn "${train_config}" conf/train.yaml ${python} "${runner}" \ - --stages create_dataset train_tokenizer collect_stats train infer measure \ + --stages create_dataset train_tokenizer collect_stats train infer metric \ --train_config conf/train.yaml \ --infer_config "${infer_config}" \ --metric_config conf/metric.yaml From bba32ed44a3742434499081c933ce735237621cd Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 5 Feb 2026 06:26:55 +0000 Subject: [PATCH 34/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- egs3/TEMPLATE/asr/run.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index a46b73592d67..c8ecff87a031 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -11,7 +11,11 @@ from omegaconf import OmegaConf from espnet3.utils.config_utils import load_config_with_defaults -from espnet3.utils.logging_utils import configure_logging, log_env_metadata, log_run_metadata +from espnet3.utils.logging_utils import ( + configure_logging, + log_env_metadata, + log_run_metadata, +) from espnet3.utils.stages_utils import resolve_stages, run_stages # Default stage list (can be extended/overridden by callers) @@ -23,7 +27,7 @@ "infer", "metric", "pack_model", - "upload_model" + "upload_model", ] # Type alias for a System class From 40db8e3f8bbb5f0c070891a4d75e7cf57f3fa244 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sat, 21 Feb 2026 21:28:42 -0500 Subject: [PATCH 35/67] Fixed merge mistake --- espnet3/systems/asr/system.py | 62 ------------------------------- espnet3/systems/base/system.py | 20 ---------- espnet3/utils/stages_utils.py | 18 ++++----- test/espnet3/utils/test_stages.py | 5 +-- 4 files changed, 10 insertions(+), 95 deletions(-) diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index 508c392bf4dc..bf0ce98fb82d 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -93,68 +93,6 @@ def create_dataset(self, *args, **kwargs): ) return result - def get_stage_log_dir(self, stage: str) -> Path: - """Return stage-specific log directories when configured. - - The ASR system routes logs to artifact directories when available: - - ``create_dataset``: ``train_config.create_dataset.dataset_dir`` or - ``train_config.dataset_dir`` or ``train_config.data_dir``. - - ``train_tokenizer``: ``train_config.tokenizer.save_path``. - - ``collect_stats``: ``train_config.stats_dir``. - - ``train``/``publish``: ``train_config.exp_dir``. - - ``infer``: ``infer_config.infer_dir``. - - ``measure``: ``metric_config.infer_dir`` or ``infer_config.infer_dir``. - - If none of the stage-specific paths are configured, it falls back to - ``BaseSystem.get_stage_log_dir`` (``train_config.exp_dir`` or - ``/logs``). - - Args: - stage (str): Stage name being executed. - - Returns: - Path: Directory where the stage log should be placed. - """ - if stage == "create_dataset": - cfg = getattr(self.train_config, "create_dataset", None) - if cfg is not None: - dataset_dir = getattr(cfg, "dataset_dir", None) - if dataset_dir: - return Path(dataset_dir) - dataset_dir = getattr(self.train_config, "dataset_dir", None) - if dataset_dir: - return Path(dataset_dir) - data_dir = getattr(self.train_config, "data_dir", None) - if data_dir: - return Path(data_dir) - elif stage == "train_tokenizer": - tokenizer_cfg = getattr(self.train_config, "tokenizer", None) - save_path = ( - getattr(tokenizer_cfg, "save_path", None) if tokenizer_cfg else None - ) - if save_path: - return Path(save_path) - elif stage == "collect_stats": - stats_dir = getattr(self.train_config, "stats_dir", None) - if stats_dir: - return Path(stats_dir) - elif stage in {"train", "publish"}: - exp_dir = getattr(self.train_config, "exp_dir", None) - if exp_dir: - return Path(exp_dir) - elif stage == "infer": - infer_dir = getattr(self.infer_config, "infer_dir", None) - if infer_dir: - return Path(infer_dir) - elif stage == "measure": - infer_dir = getattr(self.metric_config, "infer_dir", None) - if infer_dir: - return Path(infer_dir) - infer_dir = getattr(self.infer_config, "infer_dir", None) - if infer_dir: - return Path(infer_dir) - return super().get_stage_log_dir(stage) - def train(self, *args, **kwargs): """Train the model, training the tokenizer first if needed. diff --git a/espnet3/systems/base/system.py b/espnet3/systems/base/system.py index bfe56cd9ae91..18f4ffc1a046 100644 --- a/espnet3/systems/base/system.py +++ b/espnet3/systems/base/system.py @@ -121,26 +121,6 @@ def __init__( self.exp_dir, ) - def get_stage_log_dir(self, stage: str) -> Path: - """Return the default log directory for a stage. - - BaseSystem treats all stages uniformly and writes logs into: - - ``train_config.exp_dir`` when available, or - - ``/logs`` as a fallback when no experiment directory is set. - - Subclasses can override this method to route specific stages to - stage-aware artifact locations (e.g., dataset or decode outputs). - - Args: - stage (str): Stage name being executed (unused by BaseSystem). - - Returns: - Path: Directory where the stage log should be placed. - """ - if self.exp_dir is not None: - return self.exp_dir - return Path.cwd() / "logs" - def _resolve_stage_log_ref( self, ref: str | list[str] | tuple[str, ...] | None ) -> str | None: diff --git a/espnet3/utils/stages_utils.py b/espnet3/utils/stages_utils.py index 787ffd449765..d011487b44e1 100644 --- a/espnet3/utils/stages_utils.py +++ b/espnet3/utils/stages_utils.py @@ -6,7 +6,7 @@ import os import time from pathlib import Path -from typing import Any, Callable, Iterable, List, Sequence +from typing import Any, Iterable, List, Sequence from espnet3.utils.logging_utils import log_stage, set_stage_log_handler @@ -69,7 +69,7 @@ def run_stages( stages_to_run: Iterable[str], dry_run: bool = False, log: logging.Logger | None = None, - stage_log_dir_fn: Callable[[str], Path | None] | None = None, + on_stage_start: callable | None = None, ) -> None: """Invoke stage methods on ``system`` in order with logging and timing. @@ -78,20 +78,14 @@ def run_stages( stages_to_run: Iterable of stage method names to execute. dry_run: If True, log intended stages without executing them. log: Optional logger instance; defaults to module logger. - stage_log_dir_fn: Optional callable that returns a stage log directory. - When provided (or resolved from ``system.get_stage_log_dir``), - a per-stage file handler is configured using - ``/.log`` before executing each stage. - + on_stage_start: Optional callback invoked before each stage executes. + It receives the stage name and logger (``on_stage_start(stage, log)``). Raises: AttributeError: If a named stage method is missing on ``system``. TypeError: If a stage method rejects CLI-provided arguments. Exception: Re-raises any exception from a stage method. """ log = log or logger - if stage_log_dir_fn is None and hasattr(system, "get_stage_log_dir"): - stage_log_dir_fn = getattr(system, "get_stage_log_dir") - for stage in stages_to_run: fn = getattr(system, stage, None) if fn is None: @@ -130,10 +124,14 @@ def run_stages( ) set_stage_log_handler( + log, Path(log_dir) if log_dir else None, filename=filename, ) + if on_stage_start is not None: + on_stage_start(stage, log) + start = time.perf_counter() log.info("=== [START] stage: %s ===", stage) try: diff --git a/test/espnet3/utils/test_stages.py b/test/espnet3/utils/test_stages.py index 2d8025c4919f..b8f75420aa16 100644 --- a/test/espnet3/utils/test_stages.py +++ b/test/espnet3/utils/test_stages.py @@ -9,6 +9,7 @@ class DummySystem: def __init__(self): self.calls = [] + self.stage_log_dirs = {"default": None} def stage_a(self): self.calls.append("a") @@ -70,9 +71,7 @@ def test_run_stages_writes_stage_logs(tmp_path): class LoggingSystem: def __init__(self, log_dir): self.log_dir = log_dir - - def get_stage_log_dir(self, stage): - return self.log_dir + self.stage_log_dirs = {"default": log_dir} def stage_a(self): pass From 97310789b003446f887ad9ac358ced4e32602ed7 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sat, 21 Feb 2026 22:00:25 -0500 Subject: [PATCH 36/67] Fixed namings --- egs3/TEMPLATE/asr/readme.md | 2 +- egs3/TEMPLATE/asr/run.py | 30 +++++++++---------- .../asr/conf/{metric.yaml => measure.yaml} | 0 egs3/mini_an4/asr/run.sh | 4 +-- 4 files changed, 18 insertions(+), 18 deletions(-) rename egs3/mini_an4/asr/conf/{metric.yaml => measure.yaml} (100%) diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md index 829d5123f694..c46fe4e7d5eb 100644 --- a/egs3/TEMPLATE/asr/readme.md +++ b/egs3/TEMPLATE/asr/readme.md @@ -20,7 +20,7 @@ python run.py --stages train --train_tokenizer --collect_stats \ python run.py --stages infer --infer_config conf/infer.yaml # 4) Score -python run.py --stages metric --metric_config conf/metric.yaml +python run.py --stages measure --measure_config conf/metrics.yaml ``` All hyper-parameters are stored in `configs/` and can be overridden using diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index c8ecff87a031..72ef60b0f02a 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -25,7 +25,7 @@ "collect_stats", "train", "infer", - "metric", + "measure", "pack_model", "upload_model", ] @@ -65,10 +65,10 @@ def build_parser( help="Hydra config for inference/decoding stage.", ) parser.add_argument( - "--metric_config", + "--measure_config", default=None, type=Path, - help="Hydra config for metric/scoring stage.", + help="Hydra config for measure/scoring stage.", ) parser.add_argument( "--dry_run", @@ -128,10 +128,10 @@ def main( if args.infer_config is None else load_config_with_defaults(args.infer_config) ) - metric_config = ( + measure_config = ( None - if args.metric_config is None - else load_config_with_defaults(args.metric_config) + if args.measure_config is None + else load_config_with_defaults(args.measure_config) ) logger = configure_logging() @@ -142,7 +142,7 @@ def main( system = system_cls( train_config=train_config, infer_config=infer_config, - metric_config=metric_config, + measure_config=measure_config, ) # ----------------------------------------- @@ -161,7 +161,7 @@ def main( } required_configs = {} required_configs.update({stage: train_config for stage in pretrain_stages}) - required_configs.update({"infer": infer_config, "metric": metric_config}) + required_configs.update({"infer": infer_config, "measure": measure_config}) missing = [ s for s in stages_to_run @@ -171,7 +171,7 @@ def main( missing_str = ", ".join(missing) raise ValueError( f"Config not provided for stage(s): {missing_str}. " - "Use --train_config/--infer_config/--metric_config." + "Use --train_config/--infer_config/--measure_config." ) run_stages( system=system, @@ -183,7 +183,7 @@ def main( args=args, train_config=train_config, infer_config=infer_config, - metric_config=metric_config, + measure_config=measure_config, ), ) @@ -194,7 +194,7 @@ def _log_stage_metadata( args: argparse.Namespace, train_config, infer_config, - metric_config, + measure_config, ) -> None: log_run_metadata( logger, @@ -202,7 +202,7 @@ def _log_stage_metadata( configs={ "train": Path(args.train_config) if args.train_config else None, "infer": Path(args.infer_config) if args.infer_config else None, - "metric": Path(args.metric_config) if args.metric_config else None, + "measure": Path(args.measure_config) if args.measure_config else None, }, write_requirements=args.write_requirements, ) @@ -215,10 +215,10 @@ def _log_stage_metadata( logger.info( "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) ) - if metric_config is not None: + if measure_config is not None: logger.info( - "metric config content:\n%s", - OmegaConf.to_yaml(metric_config, resolve=True), + "measure config content:\n%s", + OmegaConf.to_yaml(measure_config, resolve=True), ) diff --git a/egs3/mini_an4/asr/conf/metric.yaml b/egs3/mini_an4/asr/conf/measure.yaml similarity index 100% rename from egs3/mini_an4/asr/conf/metric.yaml rename to egs3/mini_an4/asr/conf/measure.yaml diff --git a/egs3/mini_an4/asr/run.sh b/egs3/mini_an4/asr/run.sh index 983a18cc6fe8..19c11f47f577 100644 --- a/egs3/mini_an4/asr/run.sh +++ b/egs3/mini_an4/asr/run.sh @@ -10,6 +10,6 @@ python=python3 ${python} run.py \ --stages all \ --train_config conf/train.yaml \ - --infer_config conf/infer.yaml \ - --metric_config conf/metric.yaml \ + --infer_config conf/inference.yaml \ + --measure_config conf/measure.yaml \ "$@" From 0f9e0c8238958e7a35d9ab2e54789441ee21d6fc Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sat, 21 Feb 2026 23:04:51 -0500 Subject: [PATCH 37/67] Fixed PR scripts --- egs3/mini_an4/asr/conf/infer_transducer.yaml | 29 ------------------- egs3/mini_an4/asr/run.sh | 15 ---------- egs3/mini_an4/asr/src/create_dataset.py | 10 +++---- egs3/mini_an4/asr/src/tokenizer.py | 1 + espnet2/uasr/espnet_model.py | 4 +-- .../components/modeling/lightning_module.py | 1 - espnet3/utils/logging_utils.py | 2 -- espnet3/utils/stages_utils.py | 8 ++--- 8 files changed, 12 insertions(+), 58 deletions(-) delete mode 100644 egs3/mini_an4/asr/conf/infer_transducer.yaml delete mode 100644 egs3/mini_an4/asr/run.sh diff --git a/egs3/mini_an4/asr/conf/infer_transducer.yaml b/egs3/mini_an4/asr/conf/infer_transducer.yaml deleted file mode 100644 index 1362e5c1c120..000000000000 --- a/egs3/mini_an4/asr/conf/infer_transducer.yaml +++ /dev/null @@ -1,29 +0,0 @@ -# Mini AN4 ASR inference config for ESPnet3 integration tests. - -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: ${load_yaml:conf/train.yaml,exp_tag} -exp_dir: ${recipe_dir}/exp/${exp_tag} -inference_dir: ${exp_dir}/infer -dataset_dir: ${data_dir}/mini_an4 - -dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer - test: - - name: test - dataset: - _target_: src.dataset.MiniAN4Dataset - manifest_path: ${dataset_dir}/manifest/test.tsv - -parallel: - env: local - n_workers: 1 - -model: - _target_: espnet2.bin.asr_transducer_inference.Speech2Text - asr_train_config: ${exp_dir}/config.yaml - asr_model_file: ${exp_dir}/last.ckpt - beam_size: 1 - -input_key: speech -output_fn: src.infer.output_fn_transducer diff --git a/egs3/mini_an4/asr/run.sh b/egs3/mini_an4/asr/run.sh deleted file mode 100644 index 19c11f47f577..000000000000 --- a/egs3/mini_an4/asr/run.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash - -set -euo pipefail - -python=python3 - -. ./path.sh -. ../../../utils/parse_options.sh - -${python} run.py \ - --stages all \ - --train_config conf/train.yaml \ - --infer_config conf/inference.yaml \ - --measure_config conf/measure.yaml \ - "$@" diff --git a/egs3/mini_an4/asr/src/create_dataset.py b/egs3/mini_an4/asr/src/create_dataset.py index a10eb750047f..8b6c4da11a96 100644 --- a/egs3/mini_an4/asr/src/create_dataset.py +++ b/egs3/mini_an4/asr/src/create_dataset.py @@ -18,7 +18,7 @@ SPH_DIRS = {"train": "an4_clstk", "test": "an4test_clstk"} TRANSCRIPTS = {"train": "an4_train.transcription", "test": "an4_test.transcription"} -# " WORDS (a-b-c)" を想定 +# Expect lines like " WORDS (a-b-c)" LINE_RE = re.compile(r"^(?P.+?)\s+\((?P[^)]+)\)\s*$") @@ -61,13 +61,13 @@ def parse_line(line: str) -> tuple[str, str, str]: raise ValueError(f"Malformed transcript line: {line}") words = m.group("words") - # transcript の を雑に剥がす（現状仕様踏襲） + # Remove and from the transcript (keeps current behavior) if words.startswith(" "): words = words[4:] if words.endswith(" "): words = words[:-5] - src = m.group("src") # 例: abc-def-ghi + src = m.group("src") # Example: abc-def-ghi pre, mid, last = src.split("-") utt_id = f"{mid}-{pre}-{last}" return utt_id, src, words @@ -88,7 +88,7 @@ def load_entries(an4_root: Path, split: str) -> list[tuple[str, str, str]]: return entries -def sph_to_wav(sph2pipe: str, sph: Path, wav: Path) -> None: +def convert_sph_to_wav(sph2pipe: str, sph: Path, wav: Path) -> None: if wav.exists(): return wav.parent.mkdir(parents=True, exist_ok=True) @@ -111,7 +111,7 @@ def prepare_split( raise FileNotFoundError(f"Missing sph file: {sph}") wav = (wav_dir / f"{utt_id}.wav").resolve() - sph_to_wav(sph2pipe, sph, wav) + convert_sph_to_wav(sph2pipe, sph, wav) out.append(Entry(utt_id=utt_id, wav_path=wav, text=text)) return out diff --git a/egs3/mini_an4/asr/src/tokenizer.py b/egs3/mini_an4/asr/src/tokenizer.py index 9f7306852966..56e677070b6d 100644 --- a/egs3/mini_an4/asr/src/tokenizer.py +++ b/egs3/mini_an4/asr/src/tokenizer.py @@ -5,6 +5,7 @@ def gather_training_text(manifest_path: Path) -> List[str]: + """Collect transcript texts from a TSV manifest file.""" manifest_path = Path(manifest_path) if not manifest_path.is_file(): raise FileNotFoundError(f"Manifest not found: {manifest_path}") diff --git a/espnet2/uasr/espnet_model.py b/espnet2/uasr/espnet_model.py index 30de009ae390..67c3db02a7cb 100644 --- a/espnet2/uasr/espnet_model.py +++ b/espnet2/uasr/espnet_model.py @@ -57,8 +57,8 @@ def __init__( cfg: Optional[Dict] = None, pad: int = 1, sil_token: str = "", - sos_token: str = "", - eos_token: str = "", + sos_token: str = "", + eos_token: str = "", skip_softmax: str2bool = False, use_gumbel: str2bool = False, use_hard_gumbel: str2bool = True, diff --git a/espnet3/components/modeling/lightning_module.py b/espnet3/components/modeling/lightning_module.py index 5b1f77918247..ac22519da668 100644 --- a/espnet3/components/modeling/lightning_module.py +++ b/espnet3/components/modeling/lightning_module.py @@ -575,7 +575,6 @@ def collect_stats(self): ) for mode in ["train", "valid"]: - print(dataset_config) if mode == "train": dataset_config.preprocessor.train = True else: diff --git a/espnet3/utils/logging_utils.py b/espnet3/utils/logging_utils.py index faac67eb28b5..797e6a6389db 100644 --- a/espnet3/utils/logging_utils.py +++ b/espnet3/utils/logging_utils.py @@ -163,9 +163,7 @@ def configure_logging( def set_stage_log_handler( - logger: logging.Logger, log_dir: Path | None, - *, filename: str, ) -> Path | None: """Attach a file handler for a stage log, replacing any prior stage handler. diff --git a/espnet3/utils/stages_utils.py b/espnet3/utils/stages_utils.py index d011487b44e1..39fb63fba03e 100644 --- a/espnet3/utils/stages_utils.py +++ b/espnet3/utils/stages_utils.py @@ -78,8 +78,10 @@ def run_stages( stages_to_run: Iterable of stage method names to execute. dry_run: If True, log intended stages without executing them. log: Optional logger instance; defaults to module logger. - on_stage_start: Optional callback invoked before each stage executes. - It receives the stage name and logger (``on_stage_start(stage, log)``). + on_stage_start: Optional hook invoked after stage logging is configured. + This can be used to emit per-stage metadata (configs, environment, + requirements snapshots, etc.) into the newly attached log file. + Raises: AttributeError: If a named stage method is missing on ``system``. TypeError: If a stage method rejects CLI-provided arguments. @@ -124,11 +126,9 @@ def run_stages( ) set_stage_log_handler( - log, Path(log_dir) if log_dir else None, filename=filename, ) - if on_stage_start is not None: on_stage_start(stage, log) From b0ed68f9df649a592f4192ddd10c85c160c6811b Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sat, 21 Feb 2026 23:52:38 -0500 Subject: [PATCH 38/67] Fixed test-integration-espnet3.sh --- ci/test_integration_espnet3.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index c656c34e9681..cf44e78cc87d 100644 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -26,10 +26,10 @@ run_with_train_config() { ln -sfn "${train_config}" conf/train.yaml ${python} "${runner}" \ - --stages create_dataset train_tokenizer collect_stats train infer metric \ + --stages create_dataset train_tokenizer collect_stats train infer measure \ --train_config conf/train.yaml \ --infer_config "${infer_config}" \ - --metric_config conf/metric.yaml + --measure_config conf/measure.yaml rm -rf exp data } From 4675e8aa0fabaf78b69af842f44c5356a443d27b Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Sun, 22 Feb 2026 02:10:52 -0500 Subject: [PATCH 39/67] Fixed CI Issue --- ci/test_integration_espnet3.sh | 0 1 file changed, 0 insertions(+), 0 deletions(-) mode change 100644 => 100755 ci/test_integration_espnet3.sh diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh old mode 100644 new mode 100755 From d275802ecae3d32672d47f3b451fe5290b3ae267 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 25 Feb 2026 03:22:50 -0500 Subject: [PATCH 40/67] Fixed CI and format infer/measure config --- egs3/mini_an4/asr/conf/inference.yaml | 7 ++----- egs3/mini_an4/asr/conf/inference_transducer.yaml | 16 +++++++++------- egs3/mini_an4/asr/conf/measure.yaml | 9 ++------- egs3/mini_an4/asr/src/inference.py | 2 +- 4 files changed, 14 insertions(+), 20 deletions(-) diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 9a670139405b..9e99a07c0651 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -1,11 +1,8 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: ${load_yaml:conf/train.yaml,exp_tag} -exp_dir: ${recipe_dir}/exp/${exp_tag} +exp_dir: ${load_yaml:conf/train.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${data_dir}/mini_an4 +dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml index 1362e5c1c120..9de5ed450a71 100644 --- a/egs3/mini_an4/asr/conf/inference_transducer.yaml +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -1,11 +1,8 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: ${load_yaml:conf/train.yaml,exp_tag} -exp_dir: ${recipe_dir}/exp/${exp_tag} -inference_dir: ${exp_dir}/infer -dataset_dir: ${data_dir}/mini_an4 +exp_dir: ${load_yaml:conf/train.yaml,exp_dir} +inference_dir: ${exp_dir}/inference +dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer @@ -26,4 +23,9 @@ model: beam_size: 1 input_key: speech -output_fn: src.infer.output_fn_transducer +output_fn: src.inference.output_fn_transducer + +provider: + _target_: espnet3.systems.base.inference_provider.InferenceProvider +runner: + _target_: espnet3.systems.base.inference_runner.InferenceRunner diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/measure.yaml index 53f7a4b123f2..9f8030b0139d 100644 --- a/egs3/mini_an4/asr/conf/measure.yaml +++ b/egs3/mini_an4/asr/conf/measure.yaml @@ -1,13 +1,8 @@ # Mini AN4 ASR scoring config for ESPnet3 integration tests. -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: ${load_yaml:conf/train.yaml,exp_tag} -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode +exp_dir: ${load_yaml:conf/train.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${data_dir}/mini_an4 +dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer diff --git a/egs3/mini_an4/asr/src/inference.py b/egs3/mini_an4/asr/src/inference.py index b8b7399b6733..9bec614da2d5 100644 --- a/egs3/mini_an4/asr/src/inference.py +++ b/egs3/mini_an4/asr/src/inference.py @@ -1,4 +1,4 @@ -"""Inference output helpers for ASR recipes.""" +"""Inference output helpers for Mini AN4 ASR recipes.""" def output_fn(*, data, model_output, idx): From b9fcbdbffd1842172a4f9cb3fc0100b808563fd3 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 25 Feb 2026 04:09:28 -0500 Subject: [PATCH 41/67] Removed transducer system and fixed unit tests - Since we have `src/infer.py`, we don't need Transducer system in espnet3. --- ci/test_integration_espnet3.sh | 1 + .../data/test_dataloader_builder.py | 364 ++++++++++-------- .../systems/asr/test_asr_transducer.py | 116 ++++++ 3 files changed, 320 insertions(+), 161 deletions(-) create mode 100644 test/espnet3/systems/asr/test_asr_transducer.py diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index cf44e78cc87d..e4aef096f8d6 100755 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -45,6 +45,7 @@ for train_config in "${debug_configs[@]}"; do run_with_train_config "${train_config}" run.py conf/inference.yaml done +# We need seprate inference config for transducer task run_with_train_config \ train_transducer_asr_conformer_rnnt_debug.yaml \ run.py \ diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 3775efd5ea28..11d0422e9778 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -58,6 +58,9 @@ DUMMY_DATASET_TARGET = ( "test.espnet3.components.data.test_dataloader_builder." "DummyDataset" ) +DUMMY_SAME_LENGTH_DATASET_TARGET = ( + "test.espnet3.components.data.test_dataloader_builder." "DummyDatasetSameLength" +) DUMMY_SAMPLER_TARGET = ( "test.espnet3.components.data.test_dataloader_builder." "DummySampler" ) @@ -67,6 +70,10 @@ DUMMY_SHARDED_DATASET_TARGET = ( "test.espnet3.components.data.test_dataloader_builder." "DummyShardedDataset" ) +DUMMY_MISSING_SHARD_TARGET = ( + "test.espnet3.components.data.test_dataloader_builder." + "DummyMissingShardMethod" +) # -------- Dummy components for testing -------- @@ -147,34 +154,82 @@ def make_standard_dataloader_config(sampler=None, batch_sampler=None, collate_fn return OmegaConf.create(config) +def make_dataset_config(dataset_target, dataset_kwargs=None): + dataset_kwargs = dataset_kwargs or {} + config = { + "train": [ + { + "name": "train_dummy", + "dataset": {"_target_": dataset_target, **dataset_kwargs}, + } + ], + "valid": [ + { + "name": "valid_dummy", + "dataset": {"_target_": dataset_target, **dataset_kwargs}, + } + ], + } + return OmegaConf.create(config) + + +def build_organizer(dataset_target, dataset_kwargs=None): + config = make_dataset_config(dataset_target, dataset_kwargs=dataset_kwargs) + return DataOrganizer( + train=instantiate(config["train"]), + valid=instantiate(config["valid"]), + preprocessor=do_nothing_transform, + ) + + +def build_builder(dataset, config, collate_fn, num_device, epoch): + builder_config = OmegaConf.create( + { + "_target_": "espnet3.components.data.dataloader.DataLoaderBuilder", + "dataset": dataset, + "config": config, + "collate_fn": collate_fn, + "num_device": num_device, + "epoch": epoch, + } + ) + return instantiate(builder_config) + + # -------- Standard PyTorch DataLoader mode -------- def test_batch_sampler_only(): - dataset = DummyDataset() + organizer = build_organizer(DUMMY_DATASET_TARGET) config = make_standard_dataloader_config( batch_sampler={"_target_": DUMMY_BATCH_SAMPLER_TARGET} ) # We don't need batch size for batch sampler del config.dataloader.train.batch_size del config.dataloader.train.shuffle - builder = DataLoaderBuilder(dataset, config, collate_fn=None, num_device=1, epoch=0) + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 + ) loader = builder.build("train") assert "DummyBatchSampler" in str(loader.batch_sampler.__class__) def test_sampler_only(): - dataset = DummyDataset() + organizer = build_organizer(DUMMY_DATASET_TARGET) config = make_standard_dataloader_config(sampler={"_target_": DUMMY_SAMPLER_TARGET}) - builder = DataLoaderBuilder(dataset, config, collate_fn=None, num_device=1, epoch=0) + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 + ) loader = builder.build("train") assert "DummySampler" in str(loader.sampler.__class__) def test_collate_fn_none(): - dataset = DummyDatasetSameLength() + organizer = build_organizer(DUMMY_SAME_LENGTH_DATASET_TARGET) config = make_standard_dataloader_config() - builder = DataLoaderBuilder(dataset, config, collate_fn=None, num_device=1, epoch=0) + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 + ) loader = builder.build("train") batch = next(iter(loader)) assert isinstance(batch, dict) @@ -184,25 +239,12 @@ def test_collate_fn_none(): def test_common_collate_fn(): from espnet2.train.collate_fn import CommonCollateFn - config = { - "train": [ - { - "name": "train_dummy", - "dataset": {"_target_": DUMMY_DATASET_TARGET}, - } - ], - } - config = OmegaConf.create(config) - dataset = DataOrganizer( - train=instantiate(config["train"]), - valid=instantiate(config["train"]), - preprocessor=do_nothing, - ) + organizer = build_organizer(DUMMY_DATASET_TARGET) config = make_standard_dataloader_config() collate_fn = CommonCollateFn(int_pad_value=-1) - dataset.train.use_espnet_collator = True - builder = DataLoaderBuilder( - dataset.train, config, collate_fn=collate_fn, num_device=1, epoch=0 + organizer.train.use_espnet_collator = True + builder = build_builder( + organizer.train, config, collate_fn=collate_fn, num_device=1, epoch=0 ) loader = builder.build("train") batch = next(iter(loader)) @@ -213,10 +255,10 @@ def test_common_collate_fn(): def test_custom_collate_fn(): - dataset = DummyDataset() + organizer = build_organizer(DUMMY_DATASET_TARGET) config = make_standard_dataloader_config() - builder = DataLoaderBuilder( - dataset, config, collate_fn=dummy_collate_fn, num_device=1, epoch=0 + builder = build_builder( + organizer.train, config, collate_fn=dummy_collate_fn, num_device=1, epoch=0 ) loader = builder.build("train") batch = next(iter(loader)) @@ -224,12 +266,14 @@ def test_custom_collate_fn(): def test_sampler_and_batch_sampler_conflict(): - dataset = DummyDataset() + organizer = build_organizer(DUMMY_DATASET_TARGET) config = make_standard_dataloader_config( sampler={"_target_": DUMMY_SAMPLER_TARGET}, batch_sampler={"_target_": DUMMY_BATCH_SAMPLER_TARGET}, ) - builder = DataLoaderBuilder(dataset, config, collate_fn=None, num_device=1, epoch=0) + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 + ) with pytest.raises( AssertionError, match="Cannot specify both sampler and batch_sampler" ): @@ -240,20 +284,7 @@ def test_sampler_and_batch_sampler_conflict(): def test_iter_factory_from_default_yaml_with_organizer(tmp_path): - config = { - "train": [ - { - "name": "train_dummy", - "dataset": {"_target_": DUMMY_DATASET_TARGET}, - } - ], - } - config = OmegaConf.create(config) - dataset = DataOrganizer( - train=instantiate(config["train"]), - valid=instantiate(config["train"]), - preprocessor=do_nothing, - ) + organizer = build_organizer(DUMMY_DATASET_TARGET) yaml_text = """ dataloader: train: @@ -274,9 +305,9 @@ def test_iter_factory_from_default_yaml_with_organizer(tmp_path): config_path.write_text(yaml_text) cfg = load_config_with_defaults(str(config_path)) - dataset.train.use_espnet_collator = True - builder = DataLoaderBuilder( - dataset=dataset.train, + organizer.train.use_espnet_collator = True + builder = build_builder( + dataset=organizer.train, config=cfg, collate_fn=None, # Defined on config num_device=1, @@ -292,20 +323,7 @@ def test_iter_factory_from_default_yaml_with_organizer(tmp_path): def test_iter_factory_with_collate_fn(tmp_path): # For this case the collate_fn in configuration is used. # The collate_fn in DataloaderBuilder.__init__ is only used in standard dataloader. - config = { - "train": [ - { - "name": "train_dummy", - "dataset": {"_target_": DUMMY_DATASET_TARGET}, - } - ], - } - config = OmegaConf.create(config) - dataset = DataOrganizer( - train=instantiate(config["train"]), - valid=instantiate(config["train"]), - preprocessor=do_nothing, - ) + organizer = build_organizer(DUMMY_DATASET_TARGET) yaml_text = """ dataloader: train: @@ -326,9 +344,9 @@ def test_iter_factory_with_collate_fn(tmp_path): config_path.write_text(yaml_text) cfg = load_config_with_defaults(str(config_path)) - dataset.train.use_espnet_collator = True - builder = DataLoaderBuilder( - dataset=dataset.train, + organizer.train.use_espnet_collator = True + builder = build_builder( + dataset=organizer.train, config=cfg, collate_fn=dummy_collate_fn, # Defined on config num_device=1, @@ -342,42 +360,16 @@ def test_iter_factory_with_collate_fn(tmp_path): assert "audio_lengths" in batch[1] -@pytest.mark.parametrize("rank", [0, 1]) -def test_iter_factory_drops_tail_batches_for_ddp(monkeypatch, rank): - import espnet3.components.data.dataloader as dl - - # 5 total batches -> for world_size=2, drop 1 tail batch, keep 4 - def _fake_build_batch_sampler(**kwargs): - return [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]] - - monkeypatch.setattr(dl, "build_batch_sampler", _fake_build_batch_sampler) - monkeypatch.setattr(dl.torch.distributed, "get_world_size", lambda: 2) - monkeypatch.setattr(dl.torch.distributed, "get_rank", lambda: rank) - - config = OmegaConf.create( - { - "dataloader": { - "train": { - "iter_factory": { - "_target_": ( - "test.espnet3.components.data." - "test_dataloader_builder.DummyIterFactory" - ), - "batches": {"dummy": 1}, - } - } - } - } - ) - - dataset = DummyDataset() - builder = DataLoaderBuilder( - dataset=dataset, config=config, collate_fn=None, num_device=2, epoch=0 +@pytest.mark.parametrize("flag", [True, False]) +def test_multiple_iterator_is_rejected(flag): + organizer = build_organizer(DUMMY_DATASET_TARGET) + config = make_standard_dataloader_config() + config.dataloader.train.multiple_iterator = flag + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 ) - iterator = builder.build("train") - - assert len(iterator) == 2 - assert all(batch[0] != 8 for batch in iterator) + with pytest.raises(RuntimeError, match="multiple_iterator"): + builder.build("train") # --- Multiple Iterator Mode (Sharded Dataset) --- @@ -405,60 +397,14 @@ def shard(self, idx: int): return DummyShardedDataset(idx) -@pytest.fixture -def dummy_multiple_iterator_dataset(tmp_path): - # YAML-style instantiation config for 3 shards - dataset_config = { - "train": [ - { - "name": "shard0", - "dataset": { - "_target_": DUMMY_SHARDED_DATASET_TARGET, - }, - }, - ], - "valid": [ - { - "name": "valid", - "dataset": { - "_target_": DUMMY_SHARDED_DATASET_TARGET, - }, - } - ], - } - return OmegaConf.create(dataset_config) - - -def make_multiple_iterator_config(num_shards: int, shuffle: bool): - return OmegaConf.create( - { - "dataloader": { - "train": { - "multiple_iterator": True, - "num_shards": num_shards, - "shuffle": shuffle, - "iter_factory": None, - "batch_size": 1, - "num_workers": 0, - } - }, - "num_device": 1, - } - ) - - -def test_multiple_iterator_shard_initialization(dummy_multiple_iterator_dataset): - organizer = DataOrganizer( - train=instantiate(dummy_multiple_iterator_dataset.train), - valid=instantiate(dummy_multiple_iterator_dataset.valid), +def test_sharded_dataset_single_gpu_multiple_shards(): + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} ) - config = make_multiple_iterator_config(num_shards=3, shuffle=False) - builder = DataLoaderBuilder( - dataset=organizer.train, - config=config, - collate_fn=None, - num_device=1, - epoch=0, + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 ) loader = builder.build("train") batch = next(iter(loader)) @@ -472,18 +418,114 @@ def test_multiple_iterator_shard_initialization(dummy_multiple_iterator_dataset) def test_multiple_iterator_epoch_shard_switching( dummy_multiple_iterator_dataset, epoch, expected_shard ): - organizer = DataOrganizer( - train=instantiate(dummy_multiple_iterator_dataset["train"]), - valid=instantiate(dummy_multiple_iterator_dataset["valid"]), + def _get_world_size(): + return world_size + + def _get_rank(): + return rank + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": num_shards, "world_shard_size": world_size}, ) - config = make_multiple_iterator_config(num_shards=3, shuffle=False) - builder = DataLoaderBuilder( - dataset=organizer.train, - config=config, + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + builder = build_builder( + organizer.train, + config, collate_fn=None, - num_device=1, - epoch=epoch, + num_device=world_size, + epoch=0, ) loader = builder.build("train") - batch = next(iter(loader)) - assert expected_shard in batch["text"][0] + shard_ids = _collect_shard_ids(loader) + assert shard_ids == expected + + +def test_sharded_dataset_multi_gpu_rotates_with_epoch(monkeypatch): + def _get_world_size(): + return 2 + + def _get_rank(): + return 0 + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 4, "world_shard_size": 2} + ) + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + + builder_epoch0 = build_builder( + organizer.train, config, collate_fn=None, num_device=2, epoch=0 + ) + first_epoch0 = _first_shard_id(builder_epoch0.build("train")) + + builder_epoch1 = build_builder( + organizer.train, config, collate_fn=None, num_device=2, epoch=1 + ) + first_epoch1 = _first_shard_id(builder_epoch1.build("train")) + + assert first_epoch0 == "shard0" + assert first_epoch1 == "shard2" + + +@pytest.mark.parametrize("num_shards", [1, 3]) +def test_sharded_dataset_invalid_shard_count(monkeypatch, num_shards): + def _get_world_size(): + return 2 + + def _get_rank(): + return 0 + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} + ) + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=2, epoch=0 + ) + with pytest.raises(RuntimeError, match="num_shards must be divisible by world_size"): + builder.build("train") + + +def test_sharded_dataset_missing_shard_method(): + organizer = build_organizer( + DUMMY_MISSING_SHARD_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + ) + config = make_standard_dataloader_config() + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=1, epoch=0 + ) + with pytest.raises(RuntimeError, match="shard\\(\\) is not implemented"): + builder.build("train") + + +def test_sharded_dataset_world_size_mismatch(monkeypatch): + def _get_world_size(): + return 2 + + def _get_rank(): + return 0 + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + ) + config = make_standard_dataloader_config() + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=2, epoch=0 + ) + with pytest.raises(RuntimeError, match="world_shard_size must match"): + builder.build("train") diff --git a/test/espnet3/systems/asr/test_asr_transducer.py b/test/espnet3/systems/asr/test_asr_transducer.py new file mode 100644 index 000000000000..ff3e316a54b1 --- /dev/null +++ b/test/espnet3/systems/asr/test_asr_transducer.py @@ -0,0 +1,116 @@ +from argparse import Namespace + +import pytest + +from espnet3.systems.asr.transducer_task import ASRTransducerTask + + +def test_add_arguments(): + ASRTransducerTask.get_parser() + + +def test_add_arguments_help(): + parser = ASRTransducerTask.get_parser() + with pytest.raises(SystemExit): + parser.parse_args(["--help"]) + + +def test_main_help(): + with pytest.raises(SystemExit): + ASRTransducerTask.main(cmd=["--help"]) + + +def test_main_print_config(): + with pytest.raises(SystemExit): + ASRTransducerTask.main(cmd=["--print_config"]) + + +def test_main_with_no_args(): + with pytest.raises(SystemExit): + ASRTransducerTask.main(cmd=[]) + + +def test_print_config_and_load_it(tmp_path): + config_file = tmp_path / "config.yaml" + with config_file.open("w") as f: + ASRTransducerTask.print_config(f) + parser = ASRTransducerTask.get_parser() + parser.parse_args(["--config", str(config_file)]) + + +def get_dummy_namespace(): + return Namespace( + token_type="char", + token_list=["", "a", "b", "c", "", ""], + input_size=40, + frontend="frontend", + frontend_conf={"n_fft": 51, "win_length": 40, "hop_length": 16}, + specaug="specaug", + specaug_conf={"apply_time_warp": True, "time_mask_width_range": 4}, + normalize=None, + normalize_conf=None, + encoder_conf={ + "body_conf": [ + { + "block_type": "conformer", + "hidden_size": 16, + "linear_size": 8, + "conv_mod_kernel_size": 3, + } + ] + }, + decoder="stateless", + decoder_conf={"embed_size": 8}, + joint_network_conf={"joint_space_size": 8}, + model_conf={"transducer_weight": 1.0}, + init=None, + ) + + +def test_build_model(): + args = get_dummy_namespace() + + _ = ASRTransducerTask.build_model(args) + + with pytest.raises(RuntimeError): + args.token_list = -1 + + _ = ASRTransducerTask.build_model(args) + + +def test_build_collate_fn(): + args = get_dummy_namespace() + + _ = ASRTransducerTask.build_collate_fn(args, True) + + +@pytest.mark.parametrize("use_preprocessor", [True, False]) +def test_build_preprocess_fn(use_preprocessor): + args = get_dummy_namespace() + + new_args = { + "use_preprocessor": use_preprocessor, + "bpemodel": None, + "non_linguistic_symbols": args.token_list, + "cleaner": None, + "g2p": None, + } + args.__dict__.update(new_args) + + _ = ASRTransducerTask.build_preprocess_fn(args, True) + + +@pytest.mark.parametrize("inference", [True, False]) +def test_required_data_names(inference): + retval = ASRTransducerTask.required_data_names(True, inference) + + if inference: + assert retval == ("speech",) + else: + assert retval == ("speech", "text") + + +def test_optional_data_names(): + retval = ASRTransducerTask.optional_data_names(True, True) + + assert not retval From e6433c406e2555da35f876607b68091903e15451 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 25 Feb 2026 05:31:00 -0500 Subject: [PATCH 42/67] Bug fix --- .../data/test_dataloader_builder.py | 35 +------------------ 1 file changed, 1 insertion(+), 34 deletions(-) diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 11d0422e9778..747a1b62ec3e 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -178,7 +178,7 @@ def build_organizer(dataset_target, dataset_kwargs=None): return DataOrganizer( train=instantiate(config["train"]), valid=instantiate(config["valid"]), - preprocessor=do_nothing_transform, + preprocessor=do_nothing, ) @@ -412,39 +412,6 @@ def test_sharded_dataset_single_gpu_multiple_shards(): assert batch["text"][0].startswith("shard0_") -@pytest.mark.parametrize( - "epoch,expected_shard", [(0, "shard0"), (1, "shard1"), (2, "shard2")] -) -def test_multiple_iterator_epoch_shard_switching( - dummy_multiple_iterator_dataset, epoch, expected_shard -): - def _get_world_size(): - return world_size - - def _get_rank(): - return rank - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": num_shards, "world_shard_size": world_size}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - builder = build_builder( - organizer.train, - config, - collate_fn=None, - num_device=world_size, - epoch=0, - ) - loader = builder.build("train") - shard_ids = _collect_shard_ids(loader) - assert shard_ids == expected - - def test_sharded_dataset_multi_gpu_rotates_with_epoch(monkeypatch): def _get_world_size(): return 2 From 914722e02b2ff0e9c1a96f7c3002b4909933cc24 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 25 Feb 2026 04:59:47 -0500 Subject: [PATCH 43/67] Add tests for CI --- .../data/test_dataloader_builder.py | 102 ++++++++++++++---- .../components/trainers/test_trainer.py | 35 ++++++ test/espnet3/utils/test_config.py | 69 +++++++++++- 3 files changed, 187 insertions(+), 19 deletions(-) diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 747a1b62ec3e..59ca5ed1ebb6 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -157,6 +157,7 @@ def make_standard_dataloader_config(sampler=None, batch_sampler=None, collate_fn def make_dataset_config(dataset_target, dataset_kwargs=None): dataset_kwargs = dataset_kwargs or {} config = { + "_target_": "espnet3.components.data.data_organizer.DataOrganizer", "train": [ { "name": "train_dummy", @@ -175,25 +176,17 @@ def make_dataset_config(dataset_target, dataset_kwargs=None): def build_organizer(dataset_target, dataset_kwargs=None): config = make_dataset_config(dataset_target, dataset_kwargs=dataset_kwargs) - return DataOrganizer( - train=instantiate(config["train"]), - valid=instantiate(config["valid"]), - preprocessor=do_nothing, - ) + return instantiate(config) def build_builder(dataset, config, collate_fn, num_device, epoch): - builder_config = OmegaConf.create( - { - "_target_": "espnet3.components.data.dataloader.DataLoaderBuilder", - "dataset": dataset, - "config": config, - "collate_fn": collate_fn, - "num_device": num_device, - "epoch": epoch, - } + return DataLoaderBuilder( + dataset=dataset, + config=config, + collate_fn=collate_fn, + num_device=num_device, + epoch=epoch, ) - return instantiate(builder_config) # -------- Standard PyTorch DataLoader mode -------- @@ -407,9 +400,47 @@ def test_sharded_dataset_single_gpu_multiple_shards(): organizer.train, config, collate_fn=None, num_device=1, epoch=0 ) loader = builder.build("train") - batch = next(iter(loader)) - assert "text" in batch - assert batch["text"][0].startswith("shard0_") + shard_ids = _collect_shard_ids(loader) + assert shard_ids == {"shard0"} + + +@pytest.mark.parametrize( + "world_size,num_shards,rank,expected", + [ + (2, 2, 0, {"shard0"}), + (2, 2, 1, {"shard1"}), + (2, 4, 0, {"shard0"}), + (2, 4, 1, {"shard1"}), + ], +) +def test_sharded_dataset_multi_gpu_assignment( + monkeypatch, world_size, num_shards, rank, expected +): + def _get_world_size(): + return world_size + + def _get_rank(): + return rank + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": num_shards, "world_shard_size": world_size}, + ) + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + builder = build_builder( + organizer.train, + config, + collate_fn=None, + num_device=world_size, + epoch=0, + ) + loader = builder.build("train") + shard_ids = _collect_shard_ids(loader) + assert shard_ids == expected def test_sharded_dataset_multi_gpu_rotates_with_epoch(monkeypatch): @@ -442,6 +473,41 @@ def _get_rank(): assert first_epoch1 == "shard2" +@pytest.mark.parametrize( + "epoch,expected_rank0,expected_rank1", + [ + (0, "shard0", "shard1"), + (1, "shard2", "shard3"), + (2, "shard0", "shard1"), + (3, "shard2", "shard3"), + ], +) +def test_sharded_dataset_multi_gpu_rotates_epochs_0_to_3( + monkeypatch, epoch, expected_rank0, expected_rank1 +): + def _get_world_size(): + return 2 + + monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + + organizer = build_organizer( + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, + ) + config = make_standard_dataloader_config() + config.dataloader.train.batch_size = 1 + + def _first_shard_for_rank(rank): + monkeypatch.setattr(torch.distributed, "get_rank", lambda: rank) + builder = build_builder( + organizer.train, config, collate_fn=None, num_device=2, epoch=epoch + ) + return _first_shard_id(builder.build("train")) + + assert _first_shard_for_rank(0) == expected_rank0 + assert _first_shard_for_rank(1) == expected_rank1 + + @pytest.mark.parametrize("num_shards", [1, 3]) def test_sharded_dataset_invalid_shard_count(monkeypatch, num_shards): def _get_world_size(): diff --git a/test/espnet3/components/trainers/test_trainer.py b/test/espnet3/components/trainers/test_trainer.py index 351f08168a3b..2ef26993ab0c 100644 --- a/test/espnet3/components/trainers/test_trainer.py +++ b/test/espnet3/components/trainers/test_trainer.py @@ -213,6 +213,41 @@ def test_logger_variants( assert isinstance(wrapper.trainer.logger, expect_logger_type) +def test_collect_stats_then_train_does_not_mutate_trainer_config( + base_trainer_config, model_config, dummy_dataset_config, monkeypatch +): + model_config = OmegaConf.create(model_config) + model_config.dataset = dummy_dataset_config + trainer_config = OmegaConf.create(base_trainer_config) + trainer_config.logger = [ + { + "_target_": "lightning.pytorch.loggers.TensorBoardLogger", + "save_dir": "exp/tb", + "name": "tb", + } + ] + + original_logger = OmegaConf.to_container(trainer_config.logger, resolve=True) + original_keys = set(trainer_config.keys()) + + model = nn.Linear(10, 1) + lit = ESPnetLightningModule(model, model_config) + monkeypatch.setattr(ESPnetLightningModule, "collect_stats", lambda *args, **kwargs: None) + + wrapper_stats = ESPnet3LightningTrainer( + model=lit, config=trainer_config, expdir=EXPDIR + ) + wrapper_stats.collect_stats() + + wrapper_train = ESPnet3LightningTrainer( + model=lit, config=trainer_config, expdir=EXPDIR + ) + + assert set(trainer_config.keys()) == original_keys + assert hasattr(trainer_config, "logger") + assert OmegaConf.to_container(trainer_config.logger, resolve=True) == original_logger + + @pytest.mark.parametrize( "accelerator, expect_type", [ diff --git a/test/espnet3/utils/test_config.py b/test/espnet3/utils/test_config.py index 9b723da1acd4..b9dad35dbe15 100644 --- a/test/espnet3/utils/test_config.py +++ b/test/espnet3/utils/test_config.py @@ -1,9 +1,16 @@ import os import pytest +from omegaconf import OmegaConf from yaml.parser import ParserError -from espnet3.utils.config_utils import load_config_with_defaults, load_line +from espnet3.utils.config_utils import ( + _build_config_path, + _ensure_target_convert_all, + load_config_with_defaults, + load_line, + load_yaml, +) # =============================================================== # Test Case Summary for Config Utilities @@ -277,3 +284,63 @@ def test_invalid_yaml_raises(tmp_path): with pytest.raises(ParserError): load_config_with_defaults(str(main_path)) + + +def test_load_yaml_full_config(write_yaml): + path = write_yaml( + "config.yaml", + """ +foo: + bar: 123 +""", + ) + cfg = load_yaml(str(path)) + assert cfg.foo.bar == 123 + + +def test_load_yaml_nested_key(write_yaml): + path = write_yaml( + "config.yaml", + """ +foo: + bar: 123 +""", + ) + value = load_yaml(str(path), "foo.bar") + assert value == 123 + + +def test_load_yaml_missing_key_raises(write_yaml): + path = write_yaml("config.yaml", "foo: 1\n") + with pytest.raises(KeyError): + load_yaml(str(path), "missing.key") + + +def test_ensure_target_convert_all_nested(): + cfg = OmegaConf.create( + { + "a": {"_target_": "package.A", "x": 1}, + "b": [{"_target_": "package.B", "y": 2}, {"z": 3}], + "c": {"nested": {"_target_": "package.C"}}, + } + ) + _ensure_target_convert_all(cfg) + assert cfg.a._convert_ == "all" + assert cfg.b[0]._convert_ == "all" + assert cfg.c.nested._convert_ == "all" + assert "_convert_" not in cfg.b[1] + + +def test_build_config_path_adds_yaml(tmp_path): + path = _build_config_path(tmp_path, "train") + assert path == tmp_path / "train.yaml" + + +def test_build_config_path_keeps_yaml(tmp_path): + path = _build_config_path(tmp_path, "train.yaml") + assert path == tmp_path / "train.yaml" + + +def test_build_config_path_rejects_suffix(tmp_path): + with pytest.raises(ValueError): + _build_config_path(tmp_path, "train.txt") From 22a5295687bfd211f1b058544ef0dd8007162b98 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Wed, 25 Feb 2026 05:37:12 -0500 Subject: [PATCH 44/67] CI fixed --- .../data/test_dataloader_builder.py | 86 +++++++++++-------- 1 file changed, 48 insertions(+), 38 deletions(-) diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 59ca5ed1ebb6..7b9df2c8a04e 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -5,7 +5,6 @@ from omegaconf import OmegaConf from torch.utils.data import BatchSampler, Sampler -from espnet3.components.data.data_organizer import DataOrganizer, do_nothing from espnet3.components.data.dataloader import DataLoaderBuilder from espnet3.components.data.dataset import ShardedDataset from espnet3.utils.config_utils import load_config_with_defaults @@ -44,16 +43,9 @@ # | test_iter_factory_from_default_yaml_with_organizer | Uses a real YAML config with iter_factory and verifies batch structure | # noqa: E501 # | test_iter_factory_with_collate_fn | Confirms config-defined collate_fn takes precedence over argument | # noqa: E501 # -# Multiple Iterator Mode (Sharded Dataset) -# | Test Name | Description | # noqa: E501 -# |---------------------------------------|--------------------------------------------------------------------------| # noqa: E501 -# | test_multiple_iterator_shard_initialization | Checks correct shard is selected based on epoch | # noqa: E501 -# | test_multiple_iterator_epoch_shard_switching | Ensures different shard is selected as epoch changes | # noqa: E501 -# # Note: -# - DummyDataset and DummyShardedDataset are used to simulate real-world data layout -# - All `DataLoaderBuilder.build(mode)` modes are exercised: standard, iter_factory, -# and multiple_iterator +# - DummyDataset and DummyDatasetSameLength are used to simulate real-world data layout +# - All `DataLoaderBuilder.build(mode)` modes are exercised: standard, iter_factory DUMMY_DATASET_TARGET = ( "test.espnet3.components.data.test_dataloader_builder." "DummyDataset" @@ -127,13 +119,40 @@ def dummy_collate_fn(batch): return {"custom_collated": batch} -class DummyIterFactory: - def __init__(self, dataset, batches, **kwargs): - self.dataset = dataset - self.batches = list(batches) +class DummyShardedDataset(ShardedDataset): + def __init__(self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1): + self.shard_id = shard_id + self.num_shards = num_shards + self.world_shard_size = world_shard_size + self.data = [ + {"text": f"shard{shard_id}_sample0"}, + {"text": f"shard{shard_id}_sample1"}, + ] + + def __len__(self): + return len(self.data) + + def __getitem__(self, idx): + return self.data[idx] + + def shard(self, idx: int): + return DummyShardedDataset( + shard_id=idx, + num_shards=self.num_shards, + world_shard_size=self.world_shard_size, + ) - def build_iter(self, epoch, shuffle=False): - return list(self.batches) + +class DummyMissingShardMethod: + def __init__(self, num_shards=2, world_shard_size=1): + self.num_shards = num_shards + self.world_shard_size = world_shard_size + + def __len__(self): + return 0 + + def __getitem__(self, idx): + raise IndexError # -------- Config mocks -------- @@ -270,7 +289,7 @@ def test_sampler_and_batch_sampler_conflict(): with pytest.raises( AssertionError, match="Cannot specify both sampler and batch_sampler" ): - _ = builder._build_standard_dataloader(config.dataloader.train, mode="train") + _ = builder._build_standard_dataloader(config.dataloader.train) # -------- IterFactory Mode & YAML-based Integration -------- @@ -365,29 +384,20 @@ def test_multiple_iterator_is_rejected(flag): builder.build("train") -# --- Multiple Iterator Mode (Sharded Dataset) --- +def _collect_shard_ids(loader): + shard_ids = set() + for batch in loader: + text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] + shard_ids.add(text.split("_")[0]) + if len(shard_ids) >= 4: + break + return shard_ids -# Dummy sharded dataset that returns shard-specific samples -class DummyShardedDataset(ShardedDataset): - def __init__(self, shard_id: int = None): - if shard_id is None: - self.samples = [] - else: - self.samples = [ - {"text": f"shard{shard_id}_sample0"}, - {"text": f"shard{shard_id}_sample1"}, - ] - self.shard_id = shard_id - - def __len__(self): - return len(self.samples) - - def __getitem__(self, idx): - return self.samples[idx] - - def shard(self, idx: int): - return DummyShardedDataset(idx) +def _first_shard_id(loader): + batch = next(iter(loader)) + text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] + return text.split("_")[0] def test_sharded_dataset_single_gpu_multiple_shards(): From 3c69e65ac1a95b54158784c82e83c903575319fc Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 27 Feb 2026 06:55:31 -0500 Subject: [PATCH 45/67] Update namings - train -> training - file names are nouns - revised function names to verbs --- ci/test_integration_espnet3.sh | 16 +- egs3/TEMPLATE/asr/conf/inference.yaml | 2 +- egs3/TEMPLATE/asr/conf/metrics.yaml | 4 +- .../asr/conf/{train.yaml => training.yaml} | 2 +- egs3/TEMPLATE/asr/readme.md | 18 +- egs3/TEMPLATE/asr/run.py | 37 ++-- egs3/TEMPLATE/asr/src/inference.py | 12 +- egs3/mini_an4/asr/conf/inference.yaml | 6 +- .../asr/conf/inference_transducer.yaml | 6 +- .../asr/conf/{measure.yaml => metrics.yaml} | 2 +- .../asr/conf/train_asr_transformer.yaml | 160 ------------------ .../asr/conf/{train.yaml => training.yaml} | 0 ...r_rnn_debug.yaml => training_asr_rnn.yaml} | 4 +- ...ug.yaml => training_asr_rnn_data_aug.yaml} | 4 +- ...debug.yaml => training_asr_streaming.yaml} | 4 +- ...ebug.yaml => training_asr_transducer.yaml} | 4 +- ...bug.yaml => training_asr_transformer.yaml} | 4 +- ...lm_rnn_debug.yaml => training_lm_rnn.yaml} | 4 +- ...aining_transducer_asr_conformer_rnnt.yaml} | 4 +- ...{create_dataset.py => creating_dataset.py} | 4 +- egs3/mini_an4/asr/src/inference.py | 12 +- 21 files changed, 61 insertions(+), 248 deletions(-) rename egs3/TEMPLATE/asr/conf/{train.yaml => training.yaml} (98%) rename egs3/mini_an4/asr/conf/{measure.yaml => metrics.yaml} (93%) delete mode 100644 egs3/mini_an4/asr/conf/train_asr_transformer.yaml rename egs3/mini_an4/asr/conf/{train.yaml => training.yaml} (100%) rename egs3/mini_an4/asr/conf/{train_asr_rnn_debug.yaml => training_asr_rnn.yaml} (98%) rename egs3/mini_an4/asr/conf/{train_asr_rnn_data_aug_debug.yaml => training_asr_rnn_data_aug.yaml} (98%) rename egs3/mini_an4/asr/conf/{train_asr_streaming_debug.yaml => training_asr_streaming.yaml} (97%) rename egs3/mini_an4/asr/conf/{train_asr_transducer_debug.yaml => training_asr_transducer.yaml} (97%) rename egs3/mini_an4/asr/conf/{train_asr_transformer_debug.yaml => training_asr_transformer.yaml} (97%) rename egs3/mini_an4/asr/conf/{train_lm_rnn_debug.yaml => training_lm_rnn.yaml} (97%) rename egs3/mini_an4/asr/conf/{train_transducer_asr_conformer_rnnt_debug.yaml => training_transducer_asr_conformer_rnnt.yaml} (97%) rename egs3/mini_an4/asr/src/{create_dataset.py => creating_dataset.py} (97%) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index e4aef096f8d6..be73c57ee983 100755 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -24,21 +24,21 @@ run_with_train_config() { local runner=$2 local infer_config=$3 - ln -sfn "${train_config}" conf/train.yaml + ln -sfn "${train_config}" conf/training.yaml ${python} "${runner}" \ --stages create_dataset train_tokenizer collect_stats train infer measure \ - --train_config conf/train.yaml \ + --train_config conf/training.yaml \ --infer_config "${infer_config}" \ --measure_config conf/measure.yaml rm -rf exp data } debug_configs=( - train_asr_rnn_data_aug_debug.yaml - train_asr_rnn_debug.yaml - train_asr_streaming_debug.yaml - train_asr_transformer_debug.yaml - train_asr_transducer_debug.yaml + training_asr_rnn_data_aug.yaml + training_asr_rnn.yaml + training_asr_streaming.yaml + training_asr_transformer.yaml + training_asr_transducer.yaml ) for train_config in "${debug_configs[@]}"; do @@ -47,7 +47,7 @@ done # We need seprate inference config for transducer task run_with_train_config \ - train_transducer_asr_conformer_rnnt_debug.yaml \ + training_transducer_asr_conformer_rnnt.yaml \ run.py \ conf/inference_transducer.yaml diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index a4fd783ea7e3..b9c0f6c742de 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -27,7 +27,7 @@ model: # Inference I/O. input_key: speech -output_fn: src.infer.output_fn +output_fn: src.inference.build_output provider: _target_: espnet3.systems.base.inference_provider.InferenceProvider diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 79a340bf1e96..0d7f1136bc64 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -1,14 +1,14 @@ # Metric/scoring configuration template for ESPnet3 ASR. # Consumes decode outputs under decode_dir and reports metrics. -# Path scaffold relative to the recipe root; keep aligned with infer.yaml. +# Path scaffold relative to the recipe root; keep aligned with inference.yaml. recipe_dir: . data_dir: ${recipe_dir}/data exp_tag: asr_template_eval exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats decode_dir: ${exp_dir}/decode -inference_dir: ${exp_dir}/inference +inference_dir: ${exp_dir}/inferenceence dataset_dir: /path/to/your/dataset # Dataset definition for test splits only (used to enumerate test names). diff --git a/egs3/TEMPLATE/asr/conf/train.yaml b/egs3/TEMPLATE/asr/conf/training.yaml similarity index 98% rename from egs3/TEMPLATE/asr/conf/train.yaml rename to egs3/TEMPLATE/asr/conf/training.yaml index 0e067035dd16..684a7409d097 100644 --- a/egs3/TEMPLATE/asr/conf/train.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -17,7 +17,7 @@ inference_dir: ${exp_dir}/inference dataset_dir: /path/to/your/dataset # Dataset creation function (downloads into dataset_dir cache). create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} # Dataset definition for training/validation splits. diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md index c46fe4e7d5eb..42b4ee41b1e2 100644 --- a/egs3/TEMPLATE/asr/readme.md +++ b/egs3/TEMPLATE/asr/readme.md @@ -7,27 +7,17 @@ https://github.com/ashleve/lightning-hydra-template ## Quick start ```bash -# 0) Edit configs to set paths (e.g., conf/train.yaml: dataset_dir, create_dataset.func) +# 0) Edit configs to set paths (e.g., conf/training.yaml: dataset_dir, create_dataset.func) # 1) Convert LibriSpeech to Hugging Face format (run once) -python run.py --stages create_dataset --train_config conf/train.yaml +python run.py --stages create_dataset --train_config conf/training.yaml # 2) Train with the default Branchformer configuration -python run.py --stages train --train_tokenizer --collect_stats \ - --train_config conf/train.yaml +python run.py --stages train --train_config conf/training.yaml # 3) Decode -python run.py --stages infer --infer_config conf/infer.yaml +python run.py --stages infer --infer_config conf/inference.yaml # 4) Score python run.py --stages measure --measure_config conf/metrics.yaml ``` - -All hyper-parameters are stored in `configs/` and can be overridden using -Hydra syntax. For example: - -```bash -python run.py --stages train \ - --train_overrides trainer.max_epochs=10 runtime.device=cuda \ - --train_config conf/train.yaml -``` diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 72ef60b0f02a..d3ad75945e80 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -26,8 +26,6 @@ "train", "infer", "measure", - "pack_model", - "upload_model", ] # Type alias for a System class @@ -37,7 +35,6 @@ def build_parser( stages: Sequence[str], - add_arguments: Optional[AddArgsFn] = None, ) -> argparse.ArgumentParser: """Build base ArgumentParser and let caller extend it.""" parser = argparse.ArgumentParser() @@ -62,13 +59,13 @@ def build_parser( "--infer_config", default=None, type=Path, - help="Hydra config for inference/decoding stage.", + help="Hydra config for infer stage.", ) parser.add_argument( "--measure_config", default=None, type=Path, - help="Hydra config for measure/scoring stage.", + help="Hydra config for measure stage.", ) parser.add_argument( "--dry_run", @@ -80,25 +77,11 @@ def build_parser( action="store_true", help="Write requirements.txt alongside each stage log.", ) - - # Stage-specific arguments can be added here if needed - parser.add_argument( - "--train.dataset_dir", - default=None, - type=Path, - help="dataset directory for training (used in some stages).", - ) - - # Let caller add custom CLI arguments - if add_arguments is not None: - add_arguments(parser) - return parser def parse_cli_and_stage_args( parser: argparse.ArgumentParser, - *, stages: Sequence[str], ) -> Tuple[argparse.Namespace, List[str]]: args = parser.parse_args() @@ -110,7 +93,6 @@ def parse_cli_and_stage_args( def main( args, system_cls: SystemCls, - *, stages: Sequence[str] = DEFAULT_STAGES, ) -> None: stages_to_run = resolve_stages(args.stages, stages) @@ -190,7 +172,6 @@ def main( def _log_stage_metadata( logger, - *, args: argparse.Namespace, train_config, infer_config, @@ -200,24 +181,26 @@ def _log_stage_metadata( logger, argv=sys.argv, configs={ - "train": Path(args.train_config) if args.train_config else None, - "infer": Path(args.infer_config) if args.infer_config else None, - "measure": Path(args.measure_config) if args.measure_config else None, + "Training": Path(args.train_config) if args.train_config else None, + "Inference": Path(args.infer_config) if args.infer_config else None, + "Metrics": Path(args.measure_config) if args.measure_config else None, }, write_requirements=args.write_requirements, ) log_env_metadata(logger) if train_config is not None: logger.info( - "Train config content:\n%s", OmegaConf.to_yaml(train_config, resolve=True) + "Training config content:\n%s", + OmegaConf.to_yaml(train_config, resolve=True), ) if infer_config is not None: logger.info( - "Infer config content:\n%s", OmegaConf.to_yaml(infer_config, resolve=True) + "Inference config content:\n%s", + OmegaConf.to_yaml(infer_config, resolve=True), ) if measure_config is not None: logger.info( - "measure config content:\n%s", + "Metrics config content:\n%s", OmegaConf.to_yaml(measure_config, resolve=True), ) diff --git a/egs3/TEMPLATE/asr/src/inference.py b/egs3/TEMPLATE/asr/src/inference.py index b8b7399b6733..c6fff782b663 100644 --- a/egs3/TEMPLATE/asr/src/inference.py +++ b/egs3/TEMPLATE/asr/src/inference.py @@ -1,17 +1,17 @@ """Inference output helpers for ASR recipes.""" -def output_fn(*, data, model_output, idx): +def build_output(data, model_output, idx): """Build a dict of outputs for SCP writing.""" - uttid = data.get("uttid", str(idx)) + utt_id = data.get("utt_id", str(idx)) hyp = model_output[0][0] ref = data.get("text", "") - return {"uttid": uttid, "hyp": hyp, "ref": ref} + return {"utt_id": utt_id, "hyp": hyp, "ref": ref} -def output_fn_transducer(*, data, model_output, idx): +def build_output_transducer(data, model_output, idx): """Build a dict of outputs for transducer models.""" - uttid = data.get("uttid", str(idx)) + utt_id = data.get("utt_id", str(idx)) hyp = model_output[0] ref = data.get("text", "") - return {"uttid": uttid, "hyp": hyp, "ref": ref} + return {"utt_id": utt_id, "hyp": hyp, "ref": ref} diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 9e99a07c0651..24617ba62485 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -1,8 +1,8 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -exp_dir: ${load_yaml:conf/train.yaml,exp_dir} +exp_dir: ${load_yaml:conf/training.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} +dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer @@ -24,7 +24,7 @@ model: ctc_weight: 0.3 input_key: speech -output_fn: src.inference.output_fn +output_fn: src.inference.build_output provider: _target_: espnet3.systems.base.inference_provider.InferenceProvider diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml index 9de5ed450a71..99d15f87824d 100644 --- a/egs3/mini_an4/asr/conf/inference_transducer.yaml +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -1,8 +1,8 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -exp_dir: ${load_yaml:conf/train.yaml,exp_dir} +exp_dir: ${load_yaml:conf/training.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} +dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer @@ -23,7 +23,7 @@ model: beam_size: 1 input_key: speech -output_fn: src.inference.output_fn_transducer +output_fn: src.inference.build_output_transducer provider: _target_: espnet3.systems.base.inference_provider.InferenceProvider diff --git a/egs3/mini_an4/asr/conf/measure.yaml b/egs3/mini_an4/asr/conf/metrics.yaml similarity index 93% rename from egs3/mini_an4/asr/conf/measure.yaml rename to egs3/mini_an4/asr/conf/metrics.yaml index 9f8030b0139d..b741996b45c1 100644 --- a/egs3/mini_an4/asr/conf/measure.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -1,7 +1,7 @@ # Mini AN4 ASR scoring config for ESPnet3 integration tests. exp_dir: ${load_yaml:conf/train.yaml,exp_dir} -inference_dir: ${exp_dir}/inference +inference_dir: ${exp_dir}/inferenceence dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} dataset: diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml b/egs3/mini_an4/asr/conf/train_asr_transformer.yaml deleted file mode 100644 index c3a258891b39..000000000000 --- a/egs3/mini_an4/asr/conf/train_asr_transformer.yaml +++ /dev/null @@ -1,160 +0,0 @@ -# This is a debug config for CI -init: xavier_uniform - -num_device: 1 -num_nodes: 1 -task: espnet3.systems.asr.task.ASRTask - -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: train_asr_transformer -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer -dataset_dir: ${data_dir}/mini_an4 - -create_dataset: - func: src.create_dataset.create_dataset - dataset_dir: ${dataset_dir} - archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz - -dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer - train: - - name: train_nodev - dataset: - _target_: src.dataset.MiniAN4Dataset - manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - valid: - - name: train_dev - dataset: - _target_: src.dataset.MiniAN4Dataset - manifest_path: ${dataset_dir}/manifest/train_dev.tsv - preprocessor: - _target_: espnet2.train.preprocessor.CommonPreprocessor - train: true - token_type: bpe - token_list: ${tokenizer.save_path}/tokens.txt - bpemodel: ${tokenizer.save_path}/bpe.model - text_cleaner: - -parallel: - env: local - n_workers: 1 - -dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 - train: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 - batches: - type: sorted - shape_files: - - ${stats_dir}/train/feats_shape - batch_size: 32 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} - -optimizer: - _target_: torch.optim.Adam - lr: 0.005 - -scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR - warmup_steps: 30000 - -best_model_criterion: - - - valid/acc - - 10 - - max - -trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 - log_every_n_steps: 1 - max_epochs: 100 - limit_train_batches: 1 - limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger - - strategy: auto - - -tokenizer: - vocab_size: 30 - character_coverage: 1.0 - model_type: bpe - save_path: ${data_dir}/${tokenizer.model_type}_${tokenizer.vocab_size} - text_builder: - func: src.tokenizer.gather_training_text - manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - - -model: - vocab_size: ${tokenizer.vocab_size} - token_list: ${tokenizer.save_path}/tokens.txt - - encoder: transformer - encoder_conf: - output_size: 256 - attention_heads: 4 - linear_units: 2048 - num_blocks: 12 - dropout_rate: 0.1 - positional_dropout_rate: 0.1 - attention_dropout_rate: 0.0 - input_layer: conv2d - normalize_before: true - - decoder: transformer - decoder_conf: - attention_heads: 4 - linear_units: 2048 - num_blocks: 6 - dropout_rate: 0.1 - positional_dropout_rate: 0.1 - self_attention_dropout_rate: 0.0 - src_attention_dropout_rate: 0.0 - - normalize: utterance_mvn - normalize_conf: {} - - model: espnet - model_conf: - ctc_weight: 0.3 - lsm_weight: 0.1 - length_normalized_loss: false - - frontend: default - frontend_conf: - n_fft: 512 - win_length: 400 - hop_length: 160 diff --git a/egs3/mini_an4/asr/conf/train.yaml b/egs3/mini_an4/asr/conf/training.yaml similarity index 100% rename from egs3/mini_an4/asr/conf/train.yaml rename to egs3/mini_an4/asr/conf/training.yaml diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml similarity index 98% rename from egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml rename to egs3/mini_an4/asr/conf/training_asr_rnn.yaml index fdab0da4b793..81ceb7c33bbb 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml @@ -10,11 +10,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml similarity index 98% rename from egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml rename to egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index 54cf01da423c..9454e4e1edbb 100644 --- a/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -10,11 +10,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_data_aug_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml similarity index 97% rename from egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml rename to egs3/mini_an4/asr/conf/training_asr_streaming.yaml index a459f0cd9226..656450340f77 100644 --- a/egs3/mini_an4/asr/conf/train_asr_streaming_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml @@ -14,11 +14,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_streaming_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml similarity index 97% rename from egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml rename to egs3/mini_an4/asr/conf/training_asr_transducer.yaml index 82536888afc7..6053003bd0a8 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transducer_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml @@ -13,11 +13,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transducer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml similarity index 97% rename from egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml rename to egs3/mini_an4/asr/conf/training_asr_transformer.yaml index 959671a5c564..8a45f5bef6af 100644 --- a/egs3/mini_an4/asr/conf/train_asr_transformer_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml @@ -10,11 +10,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml similarity index 97% rename from egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml rename to egs3/mini_an4/asr/conf/training_lm_rnn.yaml index e88e9556565e..06b3f6fdd867 100644 --- a/egs3/mini_an4/asr/conf/train_lm_rnn_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml @@ -10,11 +10,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_lm_rnn_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml similarity index 97% rename from egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml rename to egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml index 375b80a6b1db..7726b8bc8a12 100644 --- a/egs3/mini_an4/asr/conf/train_transducer_asr_conformer_rnnt_debug.yaml +++ b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml @@ -9,11 +9,11 @@ data_dir: ${recipe_dir}/data exp_tag: train_transducer_asr_conformer_rnnt_debug exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/infer +inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: - func: src.create_dataset.create_dataset + func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz diff --git a/egs3/mini_an4/asr/src/create_dataset.py b/egs3/mini_an4/asr/src/creating_dataset.py similarity index 97% rename from egs3/mini_an4/asr/src/create_dataset.py rename to egs3/mini_an4/asr/src/creating_dataset.py index 8b6c4da11a96..8577f5f2e147 100644 --- a/egs3/mini_an4/asr/src/create_dataset.py +++ b/egs3/mini_an4/asr/src/creating_dataset.py @@ -34,7 +34,7 @@ def is_gzip(path: Path) -> bool: def ensure_extracted( - archive: Path, dataset_dir: Path, *, logger: logging.Logger + archive: Path, dataset_dir: Path, logger: logging.Logger ) -> Path: downloads_dir = dataset_dir / "downloads" an4_root = downloads_dir / "an4" @@ -123,7 +123,7 @@ def write_manifest(path: Path, entries: Iterable[Entry]) -> None: f.write(f"{e.utt_id}\t{e.wav_path}\t{e.text}\n") -def create_dataset(dataset_dir: Path, *, archive_path: Path | None = None) -> None: +def create_dataset(dataset_dir: Path, archive_path: Path | None = None) -> None: dataset_dir = Path(dataset_dir) logger = setup_logger(name="mini_an4.create_dataset") diff --git a/egs3/mini_an4/asr/src/inference.py b/egs3/mini_an4/asr/src/inference.py index 9bec614da2d5..696d32ed8eb3 100644 --- a/egs3/mini_an4/asr/src/inference.py +++ b/egs3/mini_an4/asr/src/inference.py @@ -1,17 +1,17 @@ """Inference output helpers for Mini AN4 ASR recipes.""" -def output_fn(*, data, model_output, idx): +def build_output(data, model_output, idx): """Build a dict of outputs for SCP writing.""" - uttid = data.get("uttid", str(idx)) + utt_id = data.get("utt_id", str(idx)) hyp = model_output[0][0] ref = data.get("text", "") - return {"uttid": uttid, "hyp": hyp, "ref": ref} + return {"utt_id": utt_id, "hyp": hyp, "ref": ref} -def output_fn_transducer(*, data, model_output, idx): +def build_output_transducer(data, model_output, idx): """Build a dict of outputs for transducer models.""" - uttid = data.get("uttid", str(idx)) + utt_id = data.get("utt_id", str(idx)) hyp = model_output[0] ref = data.get("text", "") - return {"uttid": uttid, "hyp": hyp, "ref": ref} + return {"utt_id": utt_id, "hyp": hyp, "ref": ref} From a6d78741d1e3762fa367fbdaf23bed4ad4502be7 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 27 Feb 2026 12:20:41 +0000 Subject: [PATCH 46/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- egs3/mini_an4/asr/src/creating_dataset.py | 4 +-- .../data/test_dataloader_builder.py | 26 ++++++++++++------- .../components/trainers/test_trainer.py | 8 ++++-- 3 files changed, 24 insertions(+), 14 deletions(-) diff --git a/egs3/mini_an4/asr/src/creating_dataset.py b/egs3/mini_an4/asr/src/creating_dataset.py index 8577f5f2e147..fc4c4774d50f 100644 --- a/egs3/mini_an4/asr/src/creating_dataset.py +++ b/egs3/mini_an4/asr/src/creating_dataset.py @@ -33,9 +33,7 @@ def is_gzip(path: Path) -> bool: return path.is_file() and path.read_bytes()[:2] == b"\x1f\x8b" -def ensure_extracted( - archive: Path, dataset_dir: Path, logger: logging.Logger -) -> Path: +def ensure_extracted(archive: Path, dataset_dir: Path, logger: logging.Logger) -> Path: downloads_dir = dataset_dir / "downloads" an4_root = downloads_dir / "an4" if an4_root.exists(): diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 7b9df2c8a04e..f8889f1bbd03 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -63,8 +63,7 @@ "test.espnet3.components.data.test_dataloader_builder." "DummyShardedDataset" ) DUMMY_MISSING_SHARD_TARGET = ( - "test.espnet3.components.data.test_dataloader_builder." - "DummyMissingShardMethod" + "test.espnet3.components.data.test_dataloader_builder." "DummyMissingShardMethod" ) @@ -120,7 +119,9 @@ def dummy_collate_fn(batch): class DummyShardedDataset(ShardedDataset): - def __init__(self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1): + def __init__( + self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1 + ): self.shard_id = shard_id self.num_shards = num_shards self.world_shard_size = world_shard_size @@ -402,7 +403,8 @@ def _first_shard_id(loader): def test_sharded_dataset_single_gpu_multiple_shards(): organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 @@ -464,7 +466,8 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 4, "world_shard_size": 2} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 @@ -530,20 +533,24 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 builder = build_builder( organizer.train, config, collate_fn=None, num_device=2, epoch=0 ) - with pytest.raises(RuntimeError, match="num_shards must be divisible by world_size"): + with pytest.raises( + RuntimeError, match="num_shards must be divisible by world_size" + ): builder.build("train") def test_sharded_dataset_missing_shard_method(): organizer = build_organizer( - DUMMY_MISSING_SHARD_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_MISSING_SHARD_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() builder = build_builder( @@ -564,7 +571,8 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() builder = build_builder( diff --git a/test/espnet3/components/trainers/test_trainer.py b/test/espnet3/components/trainers/test_trainer.py index 2ef26993ab0c..f5ceecb3d606 100644 --- a/test/espnet3/components/trainers/test_trainer.py +++ b/test/espnet3/components/trainers/test_trainer.py @@ -232,7 +232,9 @@ def test_collect_stats_then_train_does_not_mutate_trainer_config( model = nn.Linear(10, 1) lit = ESPnetLightningModule(model, model_config) - monkeypatch.setattr(ESPnetLightningModule, "collect_stats", lambda *args, **kwargs: None) + monkeypatch.setattr( + ESPnetLightningModule, "collect_stats", lambda *args, **kwargs: None + ) wrapper_stats = ESPnet3LightningTrainer( model=lit, config=trainer_config, expdir=EXPDIR @@ -245,7 +247,9 @@ def test_collect_stats_then_train_does_not_mutate_trainer_config( assert set(trainer_config.keys()) == original_keys assert hasattr(trainer_config, "logger") - assert OmegaConf.to_container(trainer_config.logger, resolve=True) == original_logger + assert ( + OmegaConf.to_container(trainer_config.logger, resolve=True) == original_logger + ) @pytest.mark.parametrize( From efb221597adcbd57da852d61c6a1771ab4f9ed5b Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 02:30:17 -0400 Subject: [PATCH 47/67] Move class paths to TEMPLATE default config. - move to TEMPLATE/*/*.yaml and load in initialization step --- egs3/TEMPLATE/asr/conf/inference.yaml | 29 +---- egs3/TEMPLATE/asr/conf/metrics.yaml | 26 ++-- egs3/TEMPLATE/asr/conf/training.yaml | 20 +-- egs3/TEMPLATE/asr/run.py | 122 +++++++++++++++--- egs3/mini_an4/asr/conf/inference.yaml | 14 -- .../asr/conf/inference_transducer.yaml | 13 -- egs3/mini_an4/asr/conf/metrics.yaml | 5 - egs3/mini_an4/asr/conf/training_asr_rnn.yaml | 52 +------- .../asr/conf/training_asr_rnn_data_aug.yaml | 55 +------- .../asr/conf/training_asr_streaming.yaml | 49 ------- .../asr/conf/training_asr_transducer.yaml | 51 -------- .../asr/conf/training_asr_transformer.yaml | 52 -------- egs3/mini_an4/asr/conf/training_lm_rnn.yaml | 51 -------- ...raining_transducer_asr_conformer_rnnt.yaml | 44 ------- 14 files changed, 128 insertions(+), 455 deletions(-) diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index b9c0f6c742de..e777e7c6ec09 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -1,31 +1,19 @@ # Inference/decoding configuration template for ESPnet3 ASR. # Keep only inference-relevant knobs. - -# Path scaffold relative to the recipe root. -recipe_dir: . -data_dir: ${recipe_dir}/data -dataset_dir: /path/to/your/dataset -exp_tag: asr_template_eval -exp_dir: ${recipe_dir}/exp/${exp_tag} +exp_dir: ${load_yaml:conf/training.yaml,exp_dir} inference_dir: ${exp_dir}/inference +dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} -# Dataset definition for test splits only. dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer test: - - name: test-clean - dataset: - _target_: src.dataset.LibriSpeechDataset - data_dir: ${dataset_dir} - split: test-clean -# Inference model entrypoint. +parallel: + env: local + n_workers: 1 + model: - _target_: espnet2.bin.asr_inference.Speech2Text - asr_train_config: ${exp_dir}/config.yaml - asr_model_file: ${exp_dir}/last.ckpt -# Inference I/O. input_key: speech output_fn: src.inference.build_output @@ -33,8 +21,3 @@ provider: _target_: espnet3.systems.base.inference_provider.InferenceProvider runner: _target_: espnet3.systems.base.inference_runner.InferenceRunner - -# Parallel execution used during data loading / scoring (defaults to local). -parallel: - env: local - n_workers: 1 diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 0d7f1136bc64..78af36ae2226 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -1,25 +1,19 @@ # Metric/scoring configuration template for ESPnet3 ASR. # Consumes decode outputs under decode_dir and reports metrics. -# Path scaffold relative to the recipe root; keep aligned with inference.yaml. -recipe_dir: . -data_dir: ${recipe_dir}/data -exp_tag: asr_template_eval -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -decode_dir: ${exp_dir}/decode -inference_dir: ${exp_dir}/inferenceence -dataset_dir: /path/to/your/dataset +exp_dir: ${load_yaml:conf/training.yaml,exp_dir} +inference_dir: ${exp_dir}/inference +dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} -# Dataset definition for test splits only (used to enumerate test names). dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer test: - - name: test-clean - dataset: - _target_: src.dataset.LibriSpeechDataset - data_dir: ${dataset_dir} - split: test-clean -# Metrics block intentionally empty in template; fill with WER/CER, etc. metrics: + - metric: + _target_: espnet3.systems.asr.metrics.wer.WER + clean_types: + + - metric: + _target_: espnet3.systems.asr.metrics.cer.CER + clean_types: diff --git a/egs3/TEMPLATE/asr/conf/training.yaml b/egs3/TEMPLATE/asr/conf/training.yaml index 684a7409d097..5e5405b67e97 100644 --- a/egs3/TEMPLATE/asr/conf/training.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -10,7 +10,7 @@ task: # Hydra target of the training task (fill in per-recipe if needed). # Path scaffold relative to the recipe root. recipe_dir: . data_dir: ${recipe_dir}/data -exp_tag: asr_template_train +exp_tag: exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats inference_dir: ${exp_dir}/inference @@ -24,26 +24,15 @@ create_dataset: dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer train: - - name: train-split - dataset: - _target_: src.dataset.LibriSpeechDataset - data_dir: ${dataset_dir} - split: train valid: - - name: valid-split - dataset: - _target_: src.dataset.LibriSpeechDataset - data_dir: ${dataset_dir} - split: dev - - # Optional global preprocessor; can also be omitted + test: preprocessor: tokenizer: # Recipe should provide a text_builder that returns tokenizer text # (list[str] or path). text_builder: - func: src.tokenizer.gather_training_text + func: dataset_dir: ${dataset_dir} split: train @@ -57,7 +46,6 @@ parallel: dataloader: collate_fn: _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: multiple_iterator: false num_shards: 1 @@ -113,7 +101,7 @@ trainer: check_val_every_n_epoch: 1 gradient_clip_val: 1.0 log_every_n_steps: 100 - max_epochs: 10 + max_epochs: 100 logger: - _target_: lightning.pytorch.loggers.TensorBoardLogger diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index d3ad75945e80..c05f42abe8db 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -4,9 +4,11 @@ from __future__ import annotations import argparse +import logging import sys +from importlib import resources from pathlib import Path -from typing import Any, Callable, List, Optional, Sequence, Tuple, Type +from typing import Any, Callable, List, Sequence, Tuple, Type from omegaconf import OmegaConf @@ -31,6 +33,7 @@ # Type alias for a System class SystemCls = Type[Any] AddArgsFn = Callable[[argparse.ArgumentParser], None] +logger = logging.getLogger(__name__) def build_parser( @@ -90,6 +93,103 @@ def parse_cli_and_stage_args( return args, stages_to_run +def _resolve_template_config_filename(config_arg_name: str) -> str: + """Resolve template YAML filename from a CLI config argument key. + + Args: + config_arg_name: Internal config argument key name + (``train_config``, ``infer_config``, or ``measure_config``). + + Returns: + str: Template config filename under ``egs3.TEMPLATE.asr/conf``. + + Raises: + ValueError: If an unknown config argument name is provided. + + Examples: + >>> _resolve_template_config_filename("train_config") + 'training.yaml' + >>> _resolve_template_config_filename("infer_config") + 'inference.yaml' + + Todo: + If new config are added to CLI options, extend this mapping. + """ + if config_arg_name == "train_config": + return "training.yaml" + if config_arg_name == "infer_config": + return "inference.yaml" + if config_arg_name == "measure_config": + return "metrics.yaml" + raise ValueError(f"Unknown config argument name: {config_arg_name}") + + +def _load_template_defaults(config_arg_name: str): + """Load packaged TEMPLATE defaults by config kind. + + Args: + config_arg_name: Internal config argument key name + (``train_config``, ``infer_config``, or ``measure_config``). + + Returns: + DictConfig: Loaded template default config. + + Examples: + >>> cfg = _load_template_defaults("train_config") + >>> "dataset" in cfg + True + >>> cfg = _load_template_defaults("infer_config") + >>> cfg.get("provider", {}).get("_target_") is not None + True + + Note: + Uses ``importlib.resources`` to avoid hard-coded file system paths, so + it also works after ``pip install`` as package data. + + """ + filename = _resolve_template_config_filename(config_arg_name) + package = "egs3.TEMPLATE.asr" + resource = resources.files(package).joinpath("conf", filename) + with resources.as_file(resource) as path: + return load_config_with_defaults(str(path)) + return OmegaConf.create({}) + + +def _load_and_merge_config(config_path: Path | None, config_arg_name: str): + """Load user config and merge with TEMPLATE defaults. + + Args: + config_path: Path to the user-provided YAML config. If ``None``, + this function returns ``None``. + config_arg_name: Internal config argument key name used to select + the corresponding TEMPLATE default config. + + Returns: + DictConfig | None: Merged config if ``config_path`` is provided, + otherwise ``None``. + + Examples: + >>> cfg = _load_and_merge_config( + ... Path("egs3/mini_an4/asr/conf/inference.yaml"), + ... "infer_config", + ... ) + >>> cfg.provider._target_ + 'espnet3.systems.base.inference_provider.InferenceProvider' + >>> _load_and_merge_config(None, "measure_config") is None + True + + Note: + Merge order is ``template_defaults -> user_config``. User config wins + on key conflicts, so recipe-specific overrides remain explicit. + + """ + if config_path is None: + return None + user_cfg = load_config_with_defaults(config_path) + default_cfg = _load_template_defaults(config_arg_name) + return OmegaConf.merge(default_cfg, user_cfg) + + def main( args, system_cls: SystemCls, @@ -100,21 +200,9 @@ def main( # ----------------------------------------- # Load configs # ----------------------------------------- - train_config = ( - None - if args.train_config is None - else load_config_with_defaults(args.train_config) - ) - infer_config = ( - None - if args.infer_config is None - else load_config_with_defaults(args.infer_config) - ) - measure_config = ( - None - if args.measure_config is None - else load_config_with_defaults(args.measure_config) - ) + train_config = _load_and_merge_config(args.train_config, "train_config") + infer_config = _load_and_merge_config(args.infer_config, "infer_config") + measure_config = _load_and_merge_config(args.measure_config, "measure_config") logger = configure_logging() @@ -211,7 +299,7 @@ def _log_stage_metadata( # Here you should replace `YourSystemClass` with the actual system class # you want to use for your experiment. - from espnet3.systems.asr.system import ASRSystem # Example import + from espnet3.systems.asr.system import ASRSystem main( args=args, diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 24617ba62485..55be843517bb 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -1,21 +1,12 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -exp_dir: ${load_yaml:conf/training.yaml,exp_dir} -inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} - dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer test: - name: test dataset: _target_: src.dataset.MiniAN4Dataset manifest_path: ${dataset_dir}/manifest/test.tsv -parallel: - env: local - n_workers: 1 - model: _target_: espnet2.bin.asr_inference.Speech2Text asr_train_config: ${exp_dir}/config.yaml @@ -25,8 +16,3 @@ model: input_key: speech output_fn: src.inference.build_output - -provider: - _target_: espnet3.systems.base.inference_provider.InferenceProvider -runner: - _target_: espnet3.systems.base.inference_runner.InferenceRunner diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml index 99d15f87824d..04d65a45e935 100644 --- a/egs3/mini_an4/asr/conf/inference_transducer.yaml +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -1,20 +1,12 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. -exp_dir: ${load_yaml:conf/training.yaml,exp_dir} -inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} - dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer test: - name: test dataset: _target_: src.dataset.MiniAN4Dataset manifest_path: ${dataset_dir}/manifest/test.tsv -parallel: - env: local - n_workers: 1 model: _target_: espnet2.bin.asr_transducer_inference.Speech2Text @@ -24,8 +16,3 @@ model: input_key: speech output_fn: src.inference.build_output_transducer - -provider: - _target_: espnet3.systems.base.inference_provider.InferenceProvider -runner: - _target_: espnet3.systems.base.inference_runner.InferenceRunner diff --git a/egs3/mini_an4/asr/conf/metrics.yaml b/egs3/mini_an4/asr/conf/metrics.yaml index b741996b45c1..fc3062e20ac5 100644 --- a/egs3/mini_an4/asr/conf/metrics.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -1,11 +1,6 @@ # Mini AN4 ASR scoring config for ESPnet3 integration tests. -exp_dir: ${load_yaml:conf/train.yaml,exp_dir} -inference_dir: ${exp_dir}/inferenceence -dataset_dir: ${load_yaml:conf/train.yaml,dataset_dir} - dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer test: - name: test dataset: diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml index 81ceb7c33bbb..7a6e5a0c1d50 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml @@ -1,16 +1,9 @@ # This is a debug config for CI # Mini AN4 ASR training config for ESPnet3 integration tests. -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -19,7 +12,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -50,46 +42,17 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: multiple_iterator: false num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: sorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 2 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} - - optimizer: - _target_: torch.optim.Adam + _target_: torch.optim.AdamW lr: 0.001 weight_decay: 0.0 @@ -107,22 +70,9 @@ best_model_criterion: - min trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 - log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index 9454e4e1edbb..d1036b9b768b 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -1,16 +1,9 @@ # This is a debug config for CI # Mini AN4 ASR training config for ESPnet3 integration tests. -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_asr_rnn_data_aug_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -19,7 +12,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -50,46 +42,15 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: - multiple_iterator: false - num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: sorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 2 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} - - optimizer: - _target_: torch.optim.Adam + _target_: torch.optim.AdamW lr: 0.001 weight_decay: 0.0 @@ -107,23 +68,11 @@ best_model_criterion: - max trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger - + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_streaming.yaml b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml index 656450340f77..378ee56de9ef 100644 --- a/egs3/mini_an4/asr/conf/training_asr_streaming.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml @@ -5,16 +5,9 @@ init: xavier_uniform -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_asr_streaming_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -23,7 +16,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -42,48 +34,19 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: multiple_iterator: false num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: unsorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 2 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} optimizer: - _target_: torch.optim.Adam lr: 0.005 scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 100 best_model_criterion: @@ -92,22 +55,10 @@ best_model_criterion: - min trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_transducer.yaml b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml index 6053003bd0a8..9014fa178199 100644 --- a/egs3/mini_an4/asr/conf/training_asr_transducer.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml @@ -4,16 +4,9 @@ init: xavier_uniform -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_asr_transducer_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -22,7 +15,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -41,48 +33,17 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: - multiple_iterator: false - num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: unsorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 2 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} optimizer: - _target_: torch.optim.Adam lr: 0.005 scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 100 best_model_criterion: @@ -91,22 +52,10 @@ best_model_criterion: - min trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_transformer.yaml b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml index 8a45f5bef6af..168e9bd6b1e9 100644 --- a/egs3/mini_an4/asr/conf/training_asr_transformer.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml @@ -1,16 +1,9 @@ # This is a debug config for CI init: xavier_uniform -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_asr_transformer_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -19,7 +12,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -38,48 +30,17 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: - multiple_iterator: false - num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: unsorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 2 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} optimizer: - _target_: torch.optim.Adam lr: 0.005 scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 100 best_model_criterion: @@ -88,22 +49,9 @@ best_model_criterion: - min trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 - log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_lm_rnn.yaml b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml index 06b3f6fdd867..6634cef11bcd 100644 --- a/egs3/mini_an4/asr/conf/training_lm_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml @@ -1,16 +1,9 @@ # This is a debug config for CI init: xavier_uniform -num_device: 1 -num_nodes: 1 task: espnet3.systems.asr.task.ASRTask -recipe_dir: . -data_dir: ${recipe_dir}/data exp_tag: train_lm_rnn_debug -exp_dir: ${recipe_dir}/exp/${exp_tag} -stats_dir: ${recipe_dir}/exp/stats -inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 create_dataset: @@ -19,7 +12,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -38,48 +30,17 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: - multiple_iterator: false - num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: sorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 32 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} optimizer: - _target_: torch.optim.Adam lr: 0.005 scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 30000 best_model_criterion: @@ -88,22 +49,10 @@ best_model_criterion: - max trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 log_every_n_steps: 1 max_epochs: 100 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml index 7726b8bc8a12..208f8b34bb3a 100644 --- a/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml +++ b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml @@ -18,7 +18,6 @@ create_dataset: archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer train: - name: train_nodev dataset: @@ -37,48 +36,17 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -parallel: - env: local - n_workers: 1 - dataloader: - collate_fn: - _target_: espnet2.train.collate_fn.CommonCollateFn - int_pad_value: -1 train: - multiple_iterator: false - num_shards: 1 iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: true - collate_fn: ${dataloader.collate_fn} - num_workers: 0 batches: type: sorted - shape_files: - - ${stats_dir}/train/feats_shape batch_size: 32 - batch_bins: 200000 - valid: - multiple_iterator: false - num_shards: 1 - iter_factory: - _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory - shuffle: false - collate_fn: ${dataloader.collate_fn} - batches: - type: ${dataloader.train.iter_factory.batches.type} - shape_files: - - ${stats_dir}/valid/feats_shape - batch_size: ${dataloader.train.iter_factory.batches.batch_size} - batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} optimizer: - _target_: torch.optim.Adam lr: 0.005 scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 30000 best_model_criterion: @@ -87,22 +55,10 @@ best_model_criterion: - min trainer: - accelerator: auto - devices: ${num_device} - num_nodes: ${num_nodes} - accumulate_grad_batches: 1 - check_val_every_n_epoch: 1 - gradient_clip_val: 1.0 log_every_n_steps: 1 max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - precision: 32 - - logger: - - _target_: lightning.pytorch.loggers.TensorBoardLogger - save_dir: ${exp_dir}/tensorboard - name: tb_logger strategy: auto From 4d8432123f9540042b6a5764fb8b3eafb7e47b43 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 02:30:39 -0400 Subject: [PATCH 48/67] Add unit test --- test/egs3/TEMPLATE/asr/test_run.py | 60 ++++++++++++++++++++++++++++++ 1 file changed, 60 insertions(+) create mode 100644 test/egs3/TEMPLATE/asr/test_run.py diff --git a/test/egs3/TEMPLATE/asr/test_run.py b/test/egs3/TEMPLATE/asr/test_run.py new file mode 100644 index 000000000000..70d5ab2c0768 --- /dev/null +++ b/test/egs3/TEMPLATE/asr/test_run.py @@ -0,0 +1,60 @@ +from pathlib import Path + +import pytest + +from egs3.TEMPLATE.asr.run import ( + _load_and_merge_config, + _load_template_defaults, + _resolve_template_config_filename, +) + + +def test_resolve_template_config_filename() -> None: + assert _resolve_template_config_filename("train_config") == "training.yaml" + assert _resolve_template_config_filename("infer_config") == "inference.yaml" + assert _resolve_template_config_filename("measure_config") == "metrics.yaml" + + +def test_resolve_template_config_filename_invalid() -> None: + with pytest.raises(ValueError, match="Unknown config argument name"): + _resolve_template_config_filename("bad_config") + + +def test_load_template_defaults_train_contains_expected_targets() -> None: + cfg = _load_template_defaults("train_config") + assert cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" + assert cfg.optimizer._target_ == "torch.optim.Adam" + assert cfg.scheduler._target_ == "espnet2.schedulers.warmup_lr.WarmupLR" + + +def test_load_template_defaults_infer_contains_expected_targets() -> None: + cfg = _load_template_defaults("infer_config") + assert cfg.provider._target_ == "espnet3.systems.base.inference_provider.InferenceProvider" + assert cfg.runner._target_ == "espnet3.systems.base.inference_runner.InferenceRunner" + + +def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) -> None: + user = tmp_path / "train_user.yaml" + user.write_text( + """ +exp_tag: user_train +optimizer: + _target_: torch.optim.SGD + lr: 0.1 +""".strip() + + "\n", + encoding="utf-8", + ) + + cfg = _load_and_merge_config(user, "train_config") + + assert cfg is not None + # user config should override template default target + assert cfg.optimizer._target_ == "torch.optim.SGD" + assert cfg.optimizer.lr == 0.1 + # template defaults should still be present + assert cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" + + +def test_load_and_merge_config_none_path_returns_none() -> None: + assert _load_and_merge_config(None, "measure_config") is None From 5c11e422a9f477deb77a3b40b9d421b8932fd8c6 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 02:31:05 -0400 Subject: [PATCH 49/67] Applied format --- egs3/TEMPLATE/asr/run.py | 4 +-- egs3/mini_an4/asr/src/creating_dataset.py | 4 +-- .../data/test_dataloader_builder.py | 26 ++++++++++++------- .../components/trainers/test_trainer.py | 14 +++++----- 4 files changed, 27 insertions(+), 21 deletions(-) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index c05f42abe8db..7582d7400e0c 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -133,7 +133,7 @@ def _load_template_defaults(config_arg_name: str): Returns: DictConfig: Loaded template default config. - + Examples: >>> cfg = _load_template_defaults("train_config") >>> "dataset" in cfg @@ -299,7 +299,7 @@ def _log_stage_metadata( # Here you should replace `YourSystemClass` with the actual system class # you want to use for your experiment. - from espnet3.systems.asr.system import ASRSystem + from espnet3.systems.asr.system import ASRSystem main( args=args, diff --git a/egs3/mini_an4/asr/src/creating_dataset.py b/egs3/mini_an4/asr/src/creating_dataset.py index 8577f5f2e147..fc4c4774d50f 100644 --- a/egs3/mini_an4/asr/src/creating_dataset.py +++ b/egs3/mini_an4/asr/src/creating_dataset.py @@ -33,9 +33,7 @@ def is_gzip(path: Path) -> bool: return path.is_file() and path.read_bytes()[:2] == b"\x1f\x8b" -def ensure_extracted( - archive: Path, dataset_dir: Path, logger: logging.Logger -) -> Path: +def ensure_extracted(archive: Path, dataset_dir: Path, logger: logging.Logger) -> Path: downloads_dir = dataset_dir / "downloads" an4_root = downloads_dir / "an4" if an4_root.exists(): diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 7b9df2c8a04e..f8889f1bbd03 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -63,8 +63,7 @@ "test.espnet3.components.data.test_dataloader_builder." "DummyShardedDataset" ) DUMMY_MISSING_SHARD_TARGET = ( - "test.espnet3.components.data.test_dataloader_builder." - "DummyMissingShardMethod" + "test.espnet3.components.data.test_dataloader_builder." "DummyMissingShardMethod" ) @@ -120,7 +119,9 @@ def dummy_collate_fn(batch): class DummyShardedDataset(ShardedDataset): - def __init__(self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1): + def __init__( + self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1 + ): self.shard_id = shard_id self.num_shards = num_shards self.world_shard_size = world_shard_size @@ -402,7 +403,8 @@ def _first_shard_id(loader): def test_sharded_dataset_single_gpu_multiple_shards(): organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 @@ -464,7 +466,8 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 4, "world_shard_size": 2} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 @@ -530,20 +533,24 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2}, ) config = make_standard_dataloader_config() config.dataloader.train.batch_size = 1 builder = build_builder( organizer.train, config, collate_fn=None, num_device=2, epoch=0 ) - with pytest.raises(RuntimeError, match="num_shards must be divisible by world_size"): + with pytest.raises( + RuntimeError, match="num_shards must be divisible by world_size" + ): builder.build("train") def test_sharded_dataset_missing_shard_method(): organizer = build_organizer( - DUMMY_MISSING_SHARD_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_MISSING_SHARD_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() builder = build_builder( @@ -564,7 +571,8 @@ def _get_rank(): monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} + DUMMY_SHARDED_DATASET_TARGET, + dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, ) config = make_standard_dataloader_config() builder = build_builder( diff --git a/test/espnet3/components/trainers/test_trainer.py b/test/espnet3/components/trainers/test_trainer.py index 2ef26993ab0c..0e8af0c92c79 100644 --- a/test/espnet3/components/trainers/test_trainer.py +++ b/test/espnet3/components/trainers/test_trainer.py @@ -232,20 +232,20 @@ def test_collect_stats_then_train_does_not_mutate_trainer_config( model = nn.Linear(10, 1) lit = ESPnetLightningModule(model, model_config) - monkeypatch.setattr(ESPnetLightningModule, "collect_stats", lambda *args, **kwargs: None) + monkeypatch.setattr( + ESPnetLightningModule, "collect_stats", lambda *args, **kwargs: None + ) wrapper_stats = ESPnet3LightningTrainer( - model=lit, config=trainer_config, expdir=EXPDIR + model=lit, config=trainer_config, exp_dir=exp_dir ) wrapper_stats.collect_stats() - wrapper_train = ESPnet3LightningTrainer( - model=lit, config=trainer_config, expdir=EXPDIR - ) - assert set(trainer_config.keys()) == original_keys assert hasattr(trainer_config, "logger") - assert OmegaConf.to_container(trainer_config.logger, resolve=True) == original_logger + assert ( + OmegaConf.to_container(trainer_config.logger, resolve=True) == original_logger + ) @pytest.mark.parametrize( From 8adb6104196512a2739e2647270e1c89c2c65bfa Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 03:03:43 -0400 Subject: [PATCH 50/67] Add egs3 as package for default config --- pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index e79980244286..38bac5b992e9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -69,7 +69,10 @@ version = {attr = "espnet2.__version__"} readme = {file = ["README.md"], content-type = "text/markdown"} [tool.setuptools.packages.find] -include = ["espnet*"] +include = ["espnet*", "egs3*"] + +[tool.setuptools.package-data] +egs3 = ["egs3/TEMPLATE/**/*.yaml"] From aa857e9dc0022e19fd773746b2c35bfb567535d7 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 03:19:00 -0400 Subject: [PATCH 51/67] Comment out unit tests that is fixed in another PR. --- .../data/test_dataloader_builder.py | 417 +++++++++--------- 1 file changed, 206 insertions(+), 211 deletions(-) diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index f8889f1bbd03..241dc5c77bd2 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -63,7 +63,8 @@ "test.espnet3.components.data.test_dataloader_builder." "DummyShardedDataset" ) DUMMY_MISSING_SHARD_TARGET = ( - "test.espnet3.components.data.test_dataloader_builder." "DummyMissingShardMethod" + "test.espnet3.components.data.test_dataloader_builder." + "DummyMissingShardMethod" ) @@ -119,9 +120,7 @@ def dummy_collate_fn(batch): class DummyShardedDataset(ShardedDataset): - def __init__( - self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1 - ): + def __init__(self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1): self.shard_id = shard_id self.num_shards = num_shards self.world_shard_size = world_shard_size @@ -373,210 +372,206 @@ def test_iter_factory_with_collate_fn(tmp_path): assert "audio_lengths" in batch[1] -@pytest.mark.parametrize("flag", [True, False]) -def test_multiple_iterator_is_rejected(flag): - organizer = build_organizer(DUMMY_DATASET_TARGET) - config = make_standard_dataloader_config() - config.dataloader.train.multiple_iterator = flag - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=1, epoch=0 - ) - with pytest.raises(RuntimeError, match="multiple_iterator"): - builder.build("train") - - -def _collect_shard_ids(loader): - shard_ids = set() - for batch in loader: - text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] - shard_ids.add(text.split("_")[0]) - if len(shard_ids) >= 4: - break - return shard_ids - - -def _first_shard_id(loader): - batch = next(iter(loader)) - text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] - return text.split("_")[0] - - -def test_sharded_dataset_single_gpu_multiple_shards(): - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=1, epoch=0 - ) - loader = builder.build("train") - shard_ids = _collect_shard_ids(loader) - assert shard_ids == {"shard0"} - - -@pytest.mark.parametrize( - "world_size,num_shards,rank,expected", - [ - (2, 2, 0, {"shard0"}), - (2, 2, 1, {"shard1"}), - (2, 4, 0, {"shard0"}), - (2, 4, 1, {"shard1"}), - ], -) -def test_sharded_dataset_multi_gpu_assignment( - monkeypatch, world_size, num_shards, rank, expected -): - def _get_world_size(): - return world_size - - def _get_rank(): - return rank - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": num_shards, "world_shard_size": world_size}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - builder = build_builder( - organizer.train, - config, - collate_fn=None, - num_device=world_size, - epoch=0, - ) - loader = builder.build("train") - shard_ids = _collect_shard_ids(loader) - assert shard_ids == expected - - -def test_sharded_dataset_multi_gpu_rotates_with_epoch(monkeypatch): - def _get_world_size(): - return 2 - - def _get_rank(): - return 0 - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - - builder_epoch0 = build_builder( - organizer.train, config, collate_fn=None, num_device=2, epoch=0 - ) - first_epoch0 = _first_shard_id(builder_epoch0.build("train")) - - builder_epoch1 = build_builder( - organizer.train, config, collate_fn=None, num_device=2, epoch=1 - ) - first_epoch1 = _first_shard_id(builder_epoch1.build("train")) - - assert first_epoch0 == "shard0" - assert first_epoch1 == "shard2" - - -@pytest.mark.parametrize( - "epoch,expected_rank0,expected_rank1", - [ - (0, "shard0", "shard1"), - (1, "shard2", "shard3"), - (2, "shard0", "shard1"), - (3, "shard2", "shard3"), - ], -) -def test_sharded_dataset_multi_gpu_rotates_epochs_0_to_3( - monkeypatch, epoch, expected_rank0, expected_rank1 -): - def _get_world_size(): - return 2 - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - - def _first_shard_for_rank(rank): - monkeypatch.setattr(torch.distributed, "get_rank", lambda: rank) - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=2, epoch=epoch - ) - return _first_shard_id(builder.build("train")) - - assert _first_shard_for_rank(0) == expected_rank0 - assert _first_shard_for_rank(1) == expected_rank1 - - -@pytest.mark.parametrize("num_shards", [1, 3]) -def test_sharded_dataset_invalid_shard_count(monkeypatch, num_shards): - def _get_world_size(): - return 2 - - def _get_rank(): - return 0 - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2}, - ) - config = make_standard_dataloader_config() - config.dataloader.train.batch_size = 1 - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=2, epoch=0 - ) - with pytest.raises( - RuntimeError, match="num_shards must be divisible by world_size" - ): - builder.build("train") - - -def test_sharded_dataset_missing_shard_method(): - organizer = build_organizer( - DUMMY_MISSING_SHARD_TARGET, - dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, - ) - config = make_standard_dataloader_config() - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=1, epoch=0 - ) - with pytest.raises(RuntimeError, match="shard\\(\\) is not implemented"): - builder.build("train") - - -def test_sharded_dataset_world_size_mismatch(monkeypatch): - def _get_world_size(): - return 2 - - def _get_rank(): - return 0 - - monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) - monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) - - organizer = build_organizer( - DUMMY_SHARDED_DATASET_TARGET, - dataset_kwargs={"num_shards": 2, "world_shard_size": 1}, - ) - config = make_standard_dataloader_config() - builder = build_builder( - organizer.train, config, collate_fn=None, num_device=2, epoch=0 - ) - with pytest.raises(RuntimeError, match="world_shard_size must match"): - builder.build("train") +# Commented out the tests for future bug fix. +# These tests are for the bug fixed in PR 14.5 (next PR) + +# @pytest.mark.parametrize("flag", [True, False]) +# def test_multiple_iterator_is_rejected(flag): +# organizer = build_organizer(DUMMY_DATASET_TARGET) +# config = make_standard_dataloader_config() +# config.dataloader.train.multiple_iterator = flag +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=1, epoch=0 +# ) +# with pytest.raises(RuntimeError, match="multiple_iterator"): +# builder.build("train") + + +# def _collect_shard_ids(loader): +# shard_ids = set() +# for batch in loader: +# text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] +# shard_ids.add(text.split("_")[0]) +# if len(shard_ids) >= 4: +# break +# return shard_ids + + +# def _first_shard_id(loader): +# batch = next(iter(loader)) +# text = batch["text"][0] if isinstance(batch, dict) else batch[0]["text"] +# return text.split("_")[0] + + +# def test_sharded_dataset_single_gpu_multiple_shards(): +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# ) +# config = make_standard_dataloader_config() +# config.dataloader.train.batch_size = 1 +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=1, epoch=0 +# ) +# loader = builder.build("train") +# shard_ids = _collect_shard_ids(loader) +# assert shard_ids == {"shard0"} + + +# @pytest.mark.parametrize( +# "world_size,num_shards,rank,expected", +# [ +# (2, 2, 0, {"shard0"}), +# (2, 2, 1, {"shard1"}), +# (2, 4, 0, {"shard0"}), +# (2, 4, 1, {"shard1"}), +# ], +# ) +# def test_sharded_dataset_multi_gpu_assignment( +# monkeypatch, world_size, num_shards, rank, expected +# ): +# def _get_world_size(): +# return world_size + +# def _get_rank(): +# return rank + +# monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) +# monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, +# dataset_kwargs={"num_shards": num_shards, "world_shard_size": world_size}, +# ) +# config = make_standard_dataloader_config() +# config.dataloader.train.batch_size = 1 +# builder = build_builder( +# organizer.train, +# config, +# collate_fn=None, +# num_device=world_size, +# epoch=0, +# ) +# loader = builder.build("train") +# shard_ids = _collect_shard_ids(loader) +# assert shard_ids == expected + + +# def test_sharded_dataset_multi_gpu_rotates_with_epoch(monkeypatch): +# def _get_world_size(): +# return 2 + +# def _get_rank(): +# return 0 + +# monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) +# monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 4, "world_shard_size": 2} +# ) +# config = make_standard_dataloader_config() +# config.dataloader.train.batch_size = 1 + +# builder_epoch0 = build_builder( +# organizer.train, config, collate_fn=None, num_device=2, epoch=0 +# ) +# first_epoch0 = _first_shard_id(builder_epoch0.build("train")) + +# builder_epoch1 = build_builder( +# organizer.train, config, collate_fn=None, num_device=2, epoch=1 +# ) +# first_epoch1 = _first_shard_id(builder_epoch1.build("train")) + +# assert first_epoch0 == "shard0" +# assert first_epoch1 == "shard2" + + +# @pytest.mark.parametrize( +# "epoch,expected_rank0,expected_rank1", +# [ +# (0, "shard0", "shard1"), +# (1, "shard2", "shard3"), +# (2, "shard0", "shard1"), +# (3, "shard2", "shard3"), +# ], +# ) +# def test_sharded_dataset_multi_gpu_rotates_epochs_0_to_3( +# monkeypatch, epoch, expected_rank0, expected_rank1 +# ): +# def _get_world_size(): +# return 2 + +# monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) + +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, +# dataset_kwargs={"num_shards": 4, "world_shard_size": 2}, +# ) +# config = make_standard_dataloader_config() +# config.dataloader.train.batch_size = 1 + +# def _first_shard_for_rank(rank): +# monkeypatch.setattr(torch.distributed, "get_rank", lambda: rank) +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=2, epoch=epoch +# ) +# return _first_shard_id(builder.build("train")) + +# assert _first_shard_for_rank(0) == expected_rank0 +# assert _first_shard_for_rank(1) == expected_rank1 + + +# @pytest.mark.parametrize("num_shards", [1, 3]) +# def test_sharded_dataset_invalid_shard_count(monkeypatch, num_shards): +# def _get_world_size(): +# return 2 + +# def _get_rank(): +# return 0 + +# monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) +# monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} +# ) +# config = make_standard_dataloader_config() +# config.dataloader.train.batch_size = 1 +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=2, epoch=0 +# ) +# with pytest.raises(RuntimeError, match="num_shards must be divisible by world_size"): +# builder.build("train") + + +# def test_sharded_dataset_missing_shard_method(): +# organizer = build_organizer( +# DUMMY_MISSING_SHARD_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# ) +# config = make_standard_dataloader_config() +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=1, epoch=0 +# ) +# with pytest.raises(RuntimeError, match="shard\\(\\) is not implemented"): +# builder.build("train") + + +# def test_sharded_dataset_world_size_mismatch(monkeypatch): +# def _get_world_size(): +# return 2 + +# def _get_rank(): +# return 0 + +# monkeypatch.setattr(torch.distributed, "get_world_size", _get_world_size) +# monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) + +# organizer = build_organizer( +# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# ) +# config = make_standard_dataloader_config() +# builder = build_builder( +# organizer.train, config, collate_fn=None, num_device=2, epoch=0 +# ) +# with pytest.raises(RuntimeError, match="world_shard_size must match"): +# builder.build("train") From a2f20319dc6f31655bd59f804ff29f97e22a04e1 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 15:25:18 -0400 Subject: [PATCH 52/67] Enhance config description and move unneccesory configs to optional config. --- egs3/TEMPLATE/asr/conf/inference.yaml | 77 +++++++++- egs3/TEMPLATE/asr/conf/metrics.yaml | 31 +++- egs3/TEMPLATE/asr/conf/training.yaml | 140 +++++++++++++++--- espnet3/systems/base/inference.py | 25 ++-- espnet3/systems/base/inference_runner.py | 52 +++++-- espnet3/systems/base/metric.py | 58 +++++++- .../espnet3/systems/asr/test_asr_inference.py | 44 ++++-- test/espnet3/systems/base/test_inference.py | 122 ++++++++++++++- .../systems/base/test_inference_runner.py | 38 ++++- test/espnet3/systems/base/test_metric.py | 70 ++++++++- 10 files changed, 575 insertions(+), 82 deletions(-) diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index e777e7c6ec09..87021da03c82 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -1,22 +1,95 @@ -# Inference/decoding configuration template for ESPnet3 ASR. -# Keep only inference-relevant knobs. +########################################################## +# Inference SETTING # +########################################################## +# Quick usage: +# python run.py --stages infer --infer_config conf/inference.yaml +# +# Outputs: +# - `${inference_dir}//*.scp` +# - each SCP stores `utt_id value` pairs for one inference field + +########################################################## +# PATHS AND INPUTS # +########################################################## exp_dir: ${load_yaml:conf/training.yaml,exp_dir} inference_dir: ${exp_dir}/inference dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} +# Test split definitions are required for inference. +# `dataset.test[*].name` becomes the output subdirectory name under +# `${inference_dir}`. +# +# Example: +# dataset: +# _target_: espnet3.components.data.data_organizer.DataOrganizer +# test: +# - name: test-clean +# dataset: +# _target_: src.dataset.YourDataset +# manifest_path: ${dataset_dir}/manifest/test-clean.tsv +# - name: test-other +# dataset: +# _target_: src.dataset.YourDataset +# manifest_path: ${dataset_dir}/manifest/test-other.tsv dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer test: +########################################################## +# PARALLELIZATION SETTING # +########################################################## parallel: env: local n_workers: 1 +########################################################## +# MODEL AND OUTPUT # +########################################################## model: +# Key name(s) selected from each dataset sample and passed to the model. +# If `dataset[i]` returns `{"speech": ..., "text": ..., "utt_id": ...}` and +# `input_key: speech`, inference uses `dataset[i]["speech"]` as model input. +# If you set `input_key: [speech, text]`, inference builds +# `{"speech": dataset[i]["speech"], "text": dataset[i]["text"]}` and calls +# `model(**...)` with that dict. input_key: speech + +# Optional output key list. +# These keys must exist in the dict returned by `output_fn`. +# Only the fields listed here are written as SCP files under +# `${inference_dir}//`. +# If omitted, keys are inferred from the first returned sample except for +# `idx_key`. Set this explicitly when you want stable SCP filenames. +# +# output_keys: +# - hyp + +# Sample identifier field name expected in the final inference output dict. +# Inference uses `utt_id` by default, and the final output dict must contain it +# unless you explicitly override `idx_key`. +# This value becomes the first column in generated SCP files and is used to map +# each inference result back to the corresponding dataset sample. +# +#idx_key: utt_id + +# Optional batch size. +# Set to `null` if your model or `output_fn` only supports single-item decoding. +# batch_size: 1 + +# Optional recipe-provided formatter that converts raw model outputs into dicts such as: +# {"utt_id": "...", "hyp": "..."} +# or +# {"utt_id": "...", "hyp": ["nbest1", "nbest2"]} +# List outputs are expanded to `hyp0.scp`, `hyp1.scp`, ... +# If omitted, the model output itself must already be a dict (or a list of dicts +# for batched inference) and must contain `utt_id` unless `idx_key` is +# overridden. output_fn: src.inference.build_output +########################################################## +# PROVIDER AND RUNNER SETTING # +########################################################## provider: _target_: espnet3.systems.base.inference_provider.InferenceProvider runner: diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 78af36ae2226..747f6ec7048c 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -1,19 +1,34 @@ -# Metric/scoring configuration template for ESPnet3 ASR. -# Consumes decode outputs under decode_dir and reports metrics. +########################################################## +# METRIC SCORING SETTING # +########################################################## +# Quick usage: +# python run.py --stages measure --measure_config conf/metrics.yaml +# +# Assumptions: +# - `conf/inference.yaml` has already produced `/*.scp` files. +# - Each metric reads matching SCP keys such as `ref.scp` and `hyp.scp`. +# - If `dataset.test` is omitted, test sets are discovered from `${inference_dir}` +# subdirectories. +########################################################## +# PATHS AND INPUTS # +########################################################## exp_dir: ${load_yaml:conf/training.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} -dataset: - _target_: espnet3.components.data.data_organizer.DataOrganizer - test: +########################################################## +# METRIC DEFINITION # +########################################################## metrics: - metric: _target_: espnet3.systems.asr.metrics.wer.WER - clean_types: + ref_key: ref # reference text key -> `/ref.scp` + hyp_key: hyp # hypothesis text key -> `/hyp.scp` + clean_types: # optional TextCleaner pipeline, e.g. [tacotron] - metric: _target_: espnet3.systems.asr.metrics.cer.CER - clean_types: + ref_key: ref # reference text key -> `/ref.scp` + hyp_key: hyp # hypothesis text key -> `/hyp.scp` + clean_types: # optional TextCleaner pipeline, e.g. [jaconv] diff --git a/egs3/TEMPLATE/asr/conf/training.yaml b/egs3/TEMPLATE/asr/conf/training.yaml index 5e5405b67e97..7bf3243e72ac 100644 --- a/egs3/TEMPLATE/asr/conf/training.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -1,26 +1,71 @@ -# Main training config template for ESPnet3 ASR. -# This file is intentionally verbose to document how each field is used in the -# default recipe skeleton. Copy and trim it for your own recipe. - -# Number of devices/nodes; kept minimal for the template. +########################################################## +# TRAINING SETTING # +########################################################## +# Quick usage: +# python run.py --stages create_dataset --train_config conf/training.yaml +# python run.py --stages train --train_config conf/training.yaml +# +# Main stages and what this config is used for: +# - `create_dataset`: uses `create_dataset` +# - `train_tokenizer`: uses `tokenizer` +# - `collect_stats`: uses `dataset`, `dataloader`, `model`, and `parallel` +# - `train`: uses most fields in this file + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## num_device: 1 num_nodes: 1 -task: # Hydra target of the training task (fill in per-recipe if needed). + +# Optional ESPnet task class path used by `get_espnet_model(...)`. +# If unset, `model` is instantiated directly via Hydra. +task: # Path scaffold relative to the recipe root. recipe_dir: . data_dir: ${recipe_dir}/data -exp_tag: +exp_tag: exp_dir: ${recipe_dir}/exp/${exp_tag} stats_dir: ${recipe_dir}/exp/stats inference_dir: ${exp_dir}/inference dataset_dir: /path/to/your/dataset -# Dataset creation function (downloads into dataset_dir cache). + +########################################################## +# DATASET CREATION SETTING # +########################################################## +# Optional dataset creation hook for the `create_dataset` stage. +# The function is resolved from `create_dataset.func` and called with the +# remaining fields in this block as keyword arguments. create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} -# Dataset definition for training/validation splits. +########################################################## +# DATASET DEFINITION # +########################################################## +# Dataset organizer used across collect_stats/train/infer/measure. +# Fill `train`, `valid`, and optionally `test` with named dataset entries. +# +# Example: +# dataset: +# _target_: espnet3.components.data.data_organizer.DataOrganizer +# train: +# - name: train +# dataset: +# _target_: src.dataset.YourDataset +# manifest_path: ${dataset_dir}/manifest/train.tsv +# valid: +# - name: dev +# dataset: +# _target_: src.dataset.YourDataset +# manifest_path: ${dataset_dir}/manifest/dev.tsv +# test: +# - name: test +# dataset: +# _target_: src.dataset.YourDataset +# manifest_path: ${dataset_dir}/manifest/test.tsv +# preprocessor: +# _target_: src.preprocess.build_preprocessor dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer train: @@ -28,24 +73,51 @@ dataset: test: preprocessor: +########################################################## +# TOKENIZER SETTING # +########################################################## +# Used by the `train_tokenizer` stage in `espnet3.systems.asr.system.ASRSystem`. +# `text_builder.func` must return either: +# - a path to a text file, or +# - an iterable of training strings tokenizer: - # Recipe should provide a text_builder that returns tokenizer text - # (list[str] or path). + save_path: ${exp_dir}/tokenizer + vocab_size: 500 + model_type: bpe + # Optional explicit output file for tokenizer training text. + # If unset, `${tokenizer.save_path}/train.txt` is used. + train_file: text_builder: - func: + func: src.tokenizer.build_text dataset_dir: ${dataset_dir} split: train -# Parallel execution settings used by espnet3.parallel (defaults to local). +########################################################## +# PARALLELIZATION SETTING # +########################################################## +# Parallel backend used by collect_stats/train. parallel: env: local n_workers: 1 - -# DataLoader common collate and iterator setup. +########################################################## +# MODEL SETTING # +########################################################## +# Training model definition. +# If `task` is set, this block is passed to `get_espnet_model(task, model_conf)`. +# Thus, you can reuse ESPnet2-style model configs here by setting `task` and +# filling this block with the per-model config that ESPnet2 used. +# If `task` is not set, this block is instantiated directly via Hydra. +model: + +########################################################## +# DATALOADER SETTING # +########################################################## dataloader: collate_fn: _target_: espnet2.train.collate_fn.CommonCollateFn + + # Training dataloader / iterator settings. train: multiple_iterator: false num_shards: 1 @@ -54,11 +126,15 @@ dataloader: shuffle: true collate_fn: ${dataloader.collate_fn} batches: - type: numel + # Typical batch modes include `unsorted`, `sorted`, and task-specific + # iterator/batcher setups. Adjust this to match your dataset. + type: unsorted shape_files: - ${stats_dir}/train/feats_shape batch_size: 4 batch_bins: 4000000 + + # Validation dataloader / iterator settings. valid: multiple_iterator: false num_shards: 1 @@ -73,26 +149,42 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} - -# Optimizer and scheduler are intentionally lightweight defaults. +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## optimizer: _target_: torch.optim.Adam lr: 0.002 weight_decay: 0.000001 - scheduler: _target_: espnet2.schedulers.warmup_lr.WarmupLR warmup_steps: 15000 - +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Checkpoint selection criteria passed to ESPnet3 callbacks. +# Each item is: +# - monitor key +# - number of best checkpoints to keep +# - direction (`min` or `max`) best_model_criterion: - - valid/loss - 3 - min +# Optional random seed used by collect_stats/train. +seed: -# Trainer settings map to Lightning Trainer; override per-recipe as needed. +# Extra model initialization mode forwarded to ESPnet's initializer. +# Example: xavier_uniform +init: + +########################################################## +# TRAINER SETTING # +########################################################## +# These settings map to `lightning.Trainer(...)`. trainer: accelerator: auto devices: ${num_device} @@ -110,5 +202,9 @@ trainer: strategy: auto - +########################################################## +# FIT SETTING # +########################################################## +# Optional keyword arguments passed directly to `trainer.fit(**fit)`. +# Leave `{}` for the default flow. fit: {} diff --git a/espnet3/systems/base/inference.py b/espnet3/systems/base/inference.py index 997ce5821154..f05e3a140204 100644 --- a/espnet3/systems/base/inference.py +++ b/espnet3/systems/base/inference.py @@ -90,10 +90,8 @@ def infer(config: DictConfig): config.test_set = test_name output_fn_path = getattr(config, "output_fn", None) - if not output_fn_path: - raise RuntimeError("infer_config.output_fn must be set.") - - _load_output_fn(output_fn_path) + if output_fn_path: + _load_output_fn(output_fn_path) input_key = getattr(config, "input_key", None) if input_key is None: @@ -111,7 +109,7 @@ def infer(config: DictConfig): if not output_keys: raise RuntimeError("infer_config.output_keys must not be empty.") - idx_key = getattr(config, "idx_key", "uttid") + idx_key = getattr(config, "idx_key", "utt_id") batch_size = getattr(config, "batch_size", None) provider_config = getattr(config, "provider", None) @@ -124,7 +122,8 @@ def infer(config: DictConfig): provider_params = dict(raw_params) provider_params["input_key"] = input_key - provider_params["output_fn_path"] = output_fn_path + if output_fn_path: + provider_params["output_fn_path"] = output_fn_path provider = instantiate( provider_config, @@ -143,6 +142,7 @@ def infer(config: DictConfig): "async_mode": False, "idx_key": idx_key, "hyp_key": hyp_keys, + "ref_key": [], "batch_size": batch_size, } runner = instantiate(runner_config, **runner_kwargs) @@ -157,18 +157,19 @@ def infer(config: DictConfig): raise RuntimeError("Async inference is not supported in this entrypoint.") # Runner can return nested lists. normalize to flat list. results = _flatten_results(out) + if not results: + raise RuntimeError("No inference results available.") + first = results[0] + resolved_idx_key = runner.resolve_idx_key(first) if output_keys is None: - if not results: - raise RuntimeError("No inference results available.") - first = results[0] - output_keys = [key for key in first.keys() if key != runner.idx_key] + output_keys = [key for key in first.keys() if key != resolved_idx_key] if not output_keys: raise RuntimeError("No output keys found in inference results.") - # Convert output dicts into per-key SCP lines (uttid + value). + # Convert output dicts into per-key SCP lines (utt_id + value). scp_lines = _collect_scp_lines( results, - idx_key=runner.idx_key, + idx_key=resolved_idx_key, hyp_keys=output_keys, ref_keys=[], ) diff --git a/espnet3/systems/base/inference_runner.py b/espnet3/systems/base/inference_runner.py index df7dea4394f4..74818543a34d 100644 --- a/espnet3/systems/base/inference_runner.py +++ b/espnet3/systems/base/inference_runner.py @@ -19,11 +19,14 @@ class InferenceRunner(BaseRunner): function. The key names are configurable via ``idx_key`` and ``hyp_key``/``ref_key``. ``hyp_key`` and ``ref_key`` may be a single string or a list of strings to support multiple hypothesis/reference - fields. + fields. ``idx_key`` is the key used to map each inference result to + its source dataset index when writing SCP files. Output format requirements: - - The result is a dict with exactly the configured keys. - - ``idx_key`` value is a scalar (list/tuple is not allowed). + - The result is a dict with the configured keys plus any extra fields. + - A sample identifier key must exist under ``idx_key`` so SCP outputs + can map each result back to the corresponding dataset sample. + - The sample identifier must be a single value, not a list or tuple. - ``hyp_key`` and ``ref_key`` values may be scalars or lists/tuples. If lists are returned, each entry is written to its own SCP file (e.g., ``hyp0.scp``, ``hyp1.scp``). @@ -32,12 +35,22 @@ class InferenceRunner(BaseRunner): def __init__( self, provider: EnvironmentProvider, - idx_key: str = "idx", + idx_key: str = "utt_id", hyp_key: str | Sequence[str] = "hyp", ref_key: str | Sequence[str] = "ref", **kwargs, ) -> None: - """Initialize the inference runner with output key settings.""" + """Initialize the inference runner with output key settings. + + Args: + provider: Environment provider that supplies dataset/model/env. + idx_key: Output dict key used as the sample identifier written in + the first column of each SCP line. This ties each inference + result back to its dataset sample. Defaults to ``"utt_id"``. + hyp_key: Hypothesis key or keys expected in the output dict. + ref_key: Reference key or keys expected in the output dict. + **kwargs: Forwarded to ``BaseRunner``. + """ super().__init__(provider, **kwargs) self.idx_key = idx_key self.hyp_key = ( @@ -47,6 +60,16 @@ def __init__( list(ref_key) if isinstance(ref_key, (list, tuple, ListConfig)) else ref_key ) + def resolve_idx_key(self, output: Dict[str, Any]) -> str: + """Validate that the configured sample-identifier key exists in output.""" + if self.idx_key not in output: + raise ValueError( + "Inference output must include the configured sample identifier " + "key used to map SCP results back to dataset samples. " + f"idx_key={self.idx_key!r}" + ) + return self.idx_key + def _validate_output(self, output: Dict[str, Any]) -> None: if not isinstance(output, dict): raise TypeError( @@ -63,7 +86,8 @@ def _validate_output(self, output: Dict[str, Any]) -> None: if isinstance(self.ref_key, (list, tuple)) else [self.ref_key] ) - expected = {self.idx_key, *hyp_keys, *ref_keys} + idx_key = self.resolve_idx_key(output) + expected = {idx_key, *hyp_keys, *ref_keys} actual = set(output.keys()) missing = expected - actual if missing: @@ -72,10 +96,10 @@ def _validate_output(self, output: Dict[str, Any]) -> None: f"missing={sorted(missing)}" ) - idx_value = output[self.idx_key] + idx_value = output[idx_key] if isinstance(idx_value, (list, tuple)): raise TypeError( - f"'{self.idx_key}' must be a scalar, got {type(idx_value).__name__}" + f"'{idx_key}' must be a single value, not {type(idx_value).__name__}" ) @staticmethod @@ -86,14 +110,14 @@ def forward(idx, dataset=None, model=None, **kwargs): idx: Integer index or an iterable of integer indices into the dataset. dataset: Dataset providing inference entries. model: Inference model callable on the configured input. - **kwargs: Expects ``input_key`` and ``output_fn_path``. + **kwargs: Expects ``input_key`` and optionally ``output_fn_path``. Returns: Dict containing ``idx`` and output fields for a single item, or a list of dicts for batched inputs (as returned by ``output_fn``). Raises: - RuntimeError: If required I/O settings are missing. + RuntimeError: If required input settings are missing. KeyError: If required input keys are missing from the dataset item(s). RuntimeError: If batched inference fails; includes guidance to disable batching when unsupported. @@ -119,9 +143,7 @@ def forward(idx, dataset=None, model=None, **kwargs): raise RuntimeError("input_key must be provided for inference.") input_key = kwargs["input_key"] output_fn_path = kwargs.get("output_fn_path") - if not output_fn_path: - raise RuntimeError("output_fn_path must be provided for inference.") - output_fn = _load_output_fn(output_fn_path) + output_fn = _load_output_fn(output_fn_path) if output_fn_path else None keys = ( list(input_key) @@ -138,6 +160,8 @@ def forward(idx, dataset=None, model=None, **kwargs): raise KeyError(f"Input key '{key}' not found in dataset item.") inputs_dict[key] = data[key] model_output = model(**inputs_dict) + if output_fn is None: + return model_output return output_fn(data=data, model_output=model_output, idx=idx) indices = list(idx) @@ -151,6 +175,8 @@ def forward(idx, dataset=None, model=None, **kwargs): try: model_output = model(**inputs_dict) + if output_fn is None: + return model_output return output_fn(data=data_batch, model_output=model_output, idx=indices) except Exception as exc: # noqa: BLE001 raise RuntimeError( diff --git a/espnet3/systems/base/metric.py b/espnet3/systems/base/metric.py index 8465a7c057e5..7ac5acbfe528 100644 --- a/espnet3/systems/base/metric.py +++ b/espnet3/systems/base/metric.py @@ -14,6 +14,62 @@ logger = logging.getLogger(__name__) +def _resolve_test_sets(measure_config: DictConfig) -> list[str]: + """Resolve metric target test sets from config or inference outputs. + + This helper decides which test-set names should be scored by the + measurement stage. + + Resolution order: + 1. If ``measure_config.dataset.test`` is defined, use its ``name`` + fields as-is. + 2. Otherwise, scan ``measure_config.inference_dir`` and treat every + subdirectory as a test set. + + For example, if ``inference_dir`` contains: + + .. code-block:: text + + exp/my_run/inference/ + test-clean/ + test-other/ + + then this function returns ``["test-clean", "test-other"]``. + + Args: + measure_config: Measurement config containing either + ``dataset.test`` entries or an ``inference_dir`` path. + + Returns: + Sorted list of test-set names to score. + + Raises: + ValueError: If neither ``dataset.test`` nor any subdirectories under + ``inference_dir`` are available. + """ + dataset = getattr(measure_config, "dataset", None) + test_config = getattr(dataset, "test", None) if dataset is not None else None + if test_config: + return [t.name for t in test_config] + + inference_dir = Path(measure_config.inference_dir) + test_sets = sorted( + entry.name + for entry in inference_dir.iterdir() + if entry.is_dir() and not entry.name.startswith(".") + ) + if not test_sets: + raise ValueError( + "No test sets found. Specify `measure_config.dataset.test` or place " + f"test-set subdirectories under inference_dir: {inference_dir}" + ) + logger.info( + "Resolved test sets from inference_dir: %s", + test_sets, + ) + return test_sets + + def measure(measure_config: DictConfig): """Compute metrics for each test set and write a metrics JSON file. @@ -23,7 +79,7 @@ def measure(measure_config: DictConfig): Returns: Nested dict keyed by metric class path and test set name. """ - test_sets = [t.name for t in measure_config.dataset.test] + test_sets = _resolve_test_sets(measure_config) results = {} assert hasattr(measure_config, "metrics"), "Please specify `metrics`!" diff --git a/test/espnet3/systems/asr/test_asr_inference.py b/test/espnet3/systems/asr/test_asr_inference.py index 0f066248468c..fda0360d6fc3 100644 --- a/test/espnet3/systems/asr/test_asr_inference.py +++ b/test/espnet3/systems/asr/test_asr_inference.py @@ -7,13 +7,13 @@ def _output_fn(*, data, model_output, idx): - return {"uttid": data["uttid"], "hyp": model_output[0][0], "ref": data["text"]} + return {"utt_id": data["utt_id"], "hyp": model_output[0][0], "ref": data["text"]} def _batch_output_fn(*, data, model_output, idx): return [ { - "uttid": sample["uttid"], + "utt_id": sample["utt_id"], "hyp": output[0][0], "ref": sample["text"], } @@ -22,7 +22,7 @@ def _batch_output_fn(*, data, model_output, idx): def _param_output_fn(*, data, model_output, idx): - return {"uttid": data["uttid"], "hyp": model_output, "ref": "ref"} + return {"utt_id": data["utt_id"], "hyp": model_output, "ref": "ref"} class DummyProvider(InferenceProvider): @@ -105,7 +105,7 @@ def fake_instantiate(obj, device=None): def test_forward_returns_hyp_and_ref(): - dataset = [{"uttid": "utt1", "speech": "audio", "text": "ref"}] + dataset = [{"utt_id": "utt1", "speech": "audio", "text": "ref"}] class DummyModel: def __call__(self, speech): @@ -121,13 +121,31 @@ def __call__(self, speech): output_fn_path=output_path, ) - assert out == {"uttid": "utt1", "hyp": "hyp", "ref": "ref"} + assert out == {"utt_id": "utt1", "hyp": "hyp", "ref": "ref"} + + +def test_forward_without_output_fn_returns_raw_model_output(): + dataset = [{"utt_id": "utt1", "speech": "audio", "text": "ref"}] + + class DummyModel: + def __call__(self, speech): + assert speech == "audio" + return {"utt_id": "utt1", "hyp": "hyp"} + + out = InferenceRunner.forward( + 0, + dataset=dataset, + model=DummyModel(), + input_key="speech", + ) + + assert out == {"utt_id": "utt1", "hyp": "hyp"} def test_forward_batch_with_batched_inputs(): dataset = [ - {"uttid": "utt1", "speech": "audio1", "text": "ref1"}, - {"uttid": "utt2", "speech": "audio2", "text": "ref2"}, + {"utt_id": "utt1", "speech": "audio1", "text": "ref1"}, + {"utt_id": "utt2", "speech": "audio2", "text": "ref2"}, ] class DummyModel: @@ -145,15 +163,15 @@ def __call__(self, **inputs): ) assert out == [ - {"uttid": "utt1", "hyp": "hyp1", "ref": "ref1"}, - {"uttid": "utt2", "hyp": "hyp2", "ref": "ref2"}, + {"utt_id": "utt1", "hyp": "hyp1", "ref": "ref1"}, + {"utt_id": "utt2", "hyp": "hyp2", "ref": "ref2"}, ] def test_forward_batch_requires_batched_model(): dataset = [ - {"uttid": "utt1", "speech": "audio1", "text": "ref1"}, - {"uttid": "utt2", "speech": "audio2", "text": "ref2"}, + {"utt_id": "utt1", "speech": "audio1", "text": "ref1"}, + {"utt_id": "utt2", "speech": "audio2", "text": "ref2"}, ] class DummyModel: @@ -182,7 +200,7 @@ def test_forward_requires_fields(): output_fn_path=f"{__name__}._output_fn", ) - dataset = [{"uttid": "utt1", "speech": "audio"}] + dataset = [{"utt_id": "utt1", "speech": "audio"}] with pytest.raises(KeyError, match="text"): InferenceRunner.forward( 0, @@ -215,7 +233,7 @@ def test_inference_params_affect_runner_forward(tmp_path, flip, expected): "inference_dir": str(tmp_path), "dataset": { "test": [{"name": "test"}], - "data": [{"uttid": "utt1", "speech": "s1"}], + "data": [{"utt_id": "utt1", "speech": "s1"}], }, "input_key": "speech", "output_fn": f"{__name__}._param_output_fn", diff --git a/test/espnet3/systems/base/test_inference.py b/test/espnet3/systems/base/test_inference.py index c51e91b4936b..c5892217bd3f 100644 --- a/test/espnet3/systems/base/test_inference.py +++ b/test/espnet3/systems/base/test_inference.py @@ -24,8 +24,8 @@ def build_dataset(self, _config): class DummyRunner(InferenceRunner): results = None - def __init__(self, provider, *, async_mode=False, results=None, **_kwargs): - super().__init__(provider, async_mode=async_mode) + def __init__(self, provider, *, async_mode=False, results=None, **kwargs): + super().__init__(provider, async_mode=async_mode, **kwargs) if results is not None: self._results = results else: @@ -61,6 +61,9 @@ def __call__(self, _indices): idx_key = "idx" + def resolve_idx_key(self, _output): + return self.idx_key + def _read_scp(path: Path): return path.read_text(encoding="utf-8").splitlines() @@ -156,3 +159,118 @@ def test_inference_passes_provider_params(tmp_path, monkeypatch): "input_key": "speech", "output_fn_path": f"{__name__}.dummy_output_fn", } + + +def test_inference_without_output_fn_uses_model_output(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "inference_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "mock_dataset_length": 2, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, + } + ) + DummyRunner.results = [ + {"utt_id": "utt1", "hyp": "h1"}, + {"utt_id": "utt2", "hyp": "h2"}, + ] + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + + inference_mod.infer(cfg) + + assert _read_scp(tmp_path / "infer" / "test_a" / "hyp.scp") == [ + "utt1 h1", + "utt2 h2", + ] + + +def test_inference_without_idx_key_uses_default_utt_id(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "inference_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "output_fn": f"{__name__}.dummy_output_fn", + "mock_dataset_length": 1, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, + } + ) + DummyRunner.results = [{"utt_id": "utt1", "hyp": "h1"}] + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + + inference_mod.infer(cfg) + + assert _read_scp(tmp_path / "infer" / "test_a" / "hyp.scp") == ["utt1 h1"] + + +def test_inference_with_explicit_idx_key_override(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "inference_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "idx_key": "sample_id", + "mock_dataset_length": 1, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, + } + ) + DummyRunner.results = [{"sample_id": "sample-1", "hyp": "h1"}] + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + + inference_mod.infer(cfg) + + assert _read_scp(tmp_path / "infer" / "test_a" / "hyp.scp") == ["sample-1 h1"] + + +def test_inference_with_explicit_output_keys_filters_scp_outputs(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "inference_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "output_keys": ["hyp"], + "mock_dataset_length": 1, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, + } + ) + DummyRunner.results = [{"utt_id": "utt1", "hyp": "h1", "ref": "r1"}] + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + + inference_mod.infer(cfg) + + base = tmp_path / "infer" / "test_a" + assert (base / "hyp.scp").exists() + assert not (base / "ref.scp").exists() + + +def test_inference_without_output_fn_requires_utterance_id(tmp_path, monkeypatch): + cfg = OmegaConf.create( + { + "parallel": {"env": "local"}, + "inference_dir": str(tmp_path / "infer"), + "dataset": {"test": [{"name": "test_a"}]}, + "input_key": "speech", + "mock_dataset_length": 1, + "provider": {"_target_": f"{__name__}.DummyProvider"}, + "runner": {"_target_": f"{__name__}.DummyRunner"}, + } + ) + DummyRunner.results = [{"hyp": "h1"}] + + monkeypatch.setattr(inference_mod, "set_parallel", lambda arg: None) + + with pytest.raises(ValueError, match="sample identifier key"): + inference_mod.infer(cfg) diff --git a/test/espnet3/systems/base/test_inference_runner.py b/test/espnet3/systems/base/test_inference_runner.py index baa3346736a9..d591078dce41 100644 --- a/test/espnet3/systems/base/test_inference_runner.py +++ b/test/espnet3/systems/base/test_inference_runner.py @@ -23,19 +23,41 @@ def test_validate_output_accepts_expected_keys(): runner._validate_output(output) +def test_resolve_idx_key_uses_default_utt_id(): + runner = DummyRunner(DummyProvider()) + + assert runner.resolve_idx_key({"utt_id": "u1", "hyp": "h", "ref": "r"}) == "utt_id" + + +def test_resolve_idx_key_uses_explicit_configured_key(): + runner = DummyRunner(DummyProvider(), idx_key="sample_id") + + assert ( + runner.resolve_idx_key({"sample_id": "u1", "hyp": "h", "ref": "r"}) + == "sample_id" + ) + + +def test_resolve_idx_key_rejects_missing_configured_key(): + runner = DummyRunner(DummyProvider(), idx_key="sample_id") + + with pytest.raises(ValueError, match="idx_key='sample_id'"): + runner.resolve_idx_key({"utt_id": "u1", "hyp": "h", "ref": "r"}) + + def test_validate_output_rejects_missing_or_extra_keys(): runner = DummyRunner(DummyProvider()) - with pytest.raises(ValueError, match="missing=\\['ref'\\]"): - runner._validate_output({"idx": 1, "hyp": "h"}) - runner._validate_output({"idx": 1, "hyp": "h", "ref": "r", "extra": 0}) + with pytest.raises(ValueError, match="idx_key='utt_id'"): + runner._validate_output({"hyp": "h"}) + runner._validate_output({"utt_id": "u1", "hyp": "h", "ref": "r", "extra": 0}) def test_validate_output_rejects_non_dict_and_idx_list(): runner = DummyRunner(DummyProvider()) with pytest.raises(TypeError, match="Expected dict output"): runner._validate_output("bad") - with pytest.raises(TypeError, match="'idx' must be a scalar"): - runner._validate_output({"idx": [1], "hyp": "h", "ref": "r"}) + with pytest.raises(TypeError, match="'utt_id' must be a single value"): + runner._validate_output({"utt_id": [1], "hyp": "h", "ref": "r"}) def test_call_async_returns_raw(monkeypatch): @@ -56,7 +78,7 @@ def fake_base_call(self, indices): ] monkeypatch.setattr(BaseRunner, "__call__", fake_base_call) - runner = DummyRunner(DummyProvider()) + runner = DummyRunner(DummyProvider(), idx_key="idx") assert runner([0, 1]) == [ {"idx": 0, "hyp": "h0", "ref": "r0"}, @@ -73,9 +95,9 @@ def test_call_returns_none(monkeypatch): def test_call_propagates_validation_error(monkeypatch): monkeypatch.setattr( - BaseRunner, "__call__", lambda self, indices: [{"idx": 0, "hyp": "h"}] + BaseRunner, "__call__", lambda self, indices: [{"hyp": "h"}] ) runner = DummyRunner(DummyProvider()) - with pytest.raises(ValueError, match="missing=\\['ref'\\]"): + with pytest.raises(ValueError, match="idx_key='utt_id'"): runner([0]) diff --git a/test/espnet3/systems/base/test_metric.py b/test/espnet3/systems/base/test_metric.py index 5781b64f7073..8a79a714d4b3 100644 --- a/test/espnet3/systems/base/test_metric.py +++ b/test/espnet3/systems/base/test_metric.py @@ -5,7 +5,7 @@ from omegaconf import OmegaConf from espnet3.components.metrics.abs_metric import AbsMetric -from espnet3.systems.base.metric import measure +from espnet3.systems.base.metric import _resolve_test_sets, measure from espnet3.utils.scp_utils import get_class_path @@ -82,6 +82,61 @@ def test_metric_uses_config_inputs_mapping(tmp_path): assert results[expected_key][test_name] == {"ok": True} +def test_metric_discovers_test_sets_from_inference_dir(tmp_path): + inference_dir = tmp_path / "infer" + for test_name in ("test_b", "test_a"): + task_dir = inference_dir / test_name + task_dir.mkdir(parents=True) + _write_scp(task_dir / "ref.scp", ["utt1 r1"]) + _write_scp(task_dir / "hyp.scp", ["utt1 h1"]) + + cfg = OmegaConf.create( + { + "inference_dir": str(inference_dir), + "metrics": [{"metric": {"_target_": f"{__name__}.DummyMetric"}}], + } + ) + + assert _resolve_test_sets(cfg) == ["test_a", "test_b"] + results = measure(cfg) + + expected_key = get_class_path(DummyMetric()) + assert set(results[expected_key]) == {"test_a", "test_b"} + assert results[expected_key]["test_a"] == {"count": 1} + assert results[expected_key]["test_b"] == {"count": 1} + + +def test_resolve_test_sets_prefers_measure_config_dataset_over_inference_dir(tmp_path): + inference_dir = tmp_path / "infer" + for test_name in ("from_dir_a", "from_dir_b"): + (inference_dir / test_name).mkdir(parents=True) + + cfg = OmegaConf.create( + { + "inference_dir": str(inference_dir), + "dataset": {"test": [{"name": "from_cfg"}]}, + "metrics": [{"metric": {"_target_": f"{__name__}.DummyMetric"}}], + } + ) + + assert _resolve_test_sets(cfg) == ["from_cfg"] + + +def test_resolve_test_sets_ignores_hidden_directories(tmp_path): + inference_dir = tmp_path / "infer" + (inference_dir / ".ignored").mkdir(parents=True) + (inference_dir / "test_visible").mkdir(parents=True) + + cfg = OmegaConf.create( + { + "inference_dir": str(inference_dir), + "metrics": [{"metric": {"_target_": f"{__name__}.DummyMetric"}}], + } + ) + + assert _resolve_test_sets(cfg) == ["test_visible"] + + def test_metric_rejects_non_metric_instance(tmp_path): cfg = OmegaConf.create( { @@ -106,3 +161,16 @@ def test_metric_requires_inputs_when_metric_has_no_keys(tmp_path): with pytest.raises(ValueError, match="requires inputs in config"): measure(cfg) + + +def test_metric_requires_test_sets_from_config_or_inference_dir(tmp_path): + cfg = OmegaConf.create( + { + "inference_dir": str(tmp_path / "infer"), + "metrics": [{"metric": {"_target_": f"{__name__}.DummyMetric"}}], + } + ) + + (tmp_path / "infer").mkdir() + with pytest.raises(ValueError, match="No test sets found"): + measure(cfg) From ee2ed063f1e848818dc19f0f0e7806c8f4bc40d8 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 15:34:26 -0400 Subject: [PATCH 53/67] Add comment on measure stage and metrics.yaml --- egs3/TEMPLATE/asr/run.py | 1 + 1 file changed, 1 insertion(+) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 7582d7400e0c..abf3ba860862 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -115,6 +115,7 @@ def _resolve_template_config_filename(config_arg_name: str) -> str: Todo: If new config are added to CLI options, extend this mapping. """ + # Stage/method names use verbs, while config filenames use noun forms. if config_arg_name == "train_config": return "training.yaml" if config_arg_name == "infer_config": From 6f6e558a11b45cc7a5361af570cee7a4d617037e Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Mon, 9 Mar 2026 15:39:44 -0400 Subject: [PATCH 54/67] Applied format --- test/egs3/TEMPLATE/asr/test_run.py | 20 +++++++++++--- .../data/test_dataloader_builder.py | 27 ++++++++++++------- .../systems/base/test_inference_runner.py | 4 +-- 3 files changed, 35 insertions(+), 16 deletions(-) diff --git a/test/egs3/TEMPLATE/asr/test_run.py b/test/egs3/TEMPLATE/asr/test_run.py index 70d5ab2c0768..5ff88d2259c8 100644 --- a/test/egs3/TEMPLATE/asr/test_run.py +++ b/test/egs3/TEMPLATE/asr/test_run.py @@ -22,15 +22,24 @@ def test_resolve_template_config_filename_invalid() -> None: def test_load_template_defaults_train_contains_expected_targets() -> None: cfg = _load_template_defaults("train_config") - assert cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" + assert ( + cfg.dataset._target_ + == "espnet3.components.data.data_organizer.DataOrganizer" + ) assert cfg.optimizer._target_ == "torch.optim.Adam" assert cfg.scheduler._target_ == "espnet2.schedulers.warmup_lr.WarmupLR" def test_load_template_defaults_infer_contains_expected_targets() -> None: cfg = _load_template_defaults("infer_config") - assert cfg.provider._target_ == "espnet3.systems.base.inference_provider.InferenceProvider" - assert cfg.runner._target_ == "espnet3.systems.base.inference_runner.InferenceRunner" + assert ( + cfg.provider._target_ + == "espnet3.systems.base.inference_provider.InferenceProvider" + ) + assert ( + cfg.runner._target_ + == "espnet3.systems.base.inference_runner.InferenceRunner" + ) def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) -> None: @@ -53,7 +62,10 @@ def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) assert cfg.optimizer._target_ == "torch.optim.SGD" assert cfg.optimizer.lr == 0.1 # template defaults should still be present - assert cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" + assert ( + cfg.dataset._target_ + == "espnet3.components.data.data_organizer.DataOrganizer" + ) def test_load_and_merge_config_none_path_returns_none() -> None: diff --git a/test/espnet3/components/data/test_dataloader_builder.py b/test/espnet3/components/data/test_dataloader_builder.py index 241dc5c77bd2..50d9a480a391 100644 --- a/test/espnet3/components/data/test_dataloader_builder.py +++ b/test/espnet3/components/data/test_dataloader_builder.py @@ -63,8 +63,7 @@ "test.espnet3.components.data.test_dataloader_builder." "DummyShardedDataset" ) DUMMY_MISSING_SHARD_TARGET = ( - "test.espnet3.components.data.test_dataloader_builder." - "DummyMissingShardMethod" + "test.espnet3.components.data.test_dataloader_builder." "DummyMissingShardMethod" ) @@ -120,7 +119,9 @@ def dummy_collate_fn(batch): class DummyShardedDataset(ShardedDataset): - def __init__(self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1): + def __init__( + self, shard_id: int = 0, num_shards: int = 2, world_shard_size: int = 1 + ): self.shard_id = shard_id self.num_shards = num_shards self.world_shard_size = world_shard_size @@ -405,7 +406,8 @@ def test_iter_factory_with_collate_fn(tmp_path): # def test_sharded_dataset_single_gpu_multiple_shards(): # organizer = build_organizer( -# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# DUMMY_SHARDED_DATASET_TARGET, +# ataset_kwargs={"num_shards": 2, "world_shard_size": 1} # ) # config = make_standard_dataloader_config() # config.dataloader.train.batch_size = 1 @@ -467,7 +469,8 @@ def test_iter_factory_with_collate_fn(tmp_path): # monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) # organizer = build_organizer( -# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 4, "world_shard_size": 2} +# DUMMY_SHARDED_DATASET_TARGET, +# dataset_kwargs={"num_shards": 4, "world_shard_size": 2} # ) # config = make_standard_dataloader_config() # config.dataloader.train.batch_size = 1 @@ -533,20 +536,25 @@ def test_iter_factory_with_collate_fn(tmp_path): # monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) # organizer = build_organizer( -# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} +# DUMMY_SHARDED_DATASET_TARGET, +# dataset_kwargs={"num_shards": num_shards, "world_shard_size": 2} # ) # config = make_standard_dataloader_config() # config.dataloader.train.batch_size = 1 # builder = build_builder( # organizer.train, config, collate_fn=None, num_device=2, epoch=0 # ) -# with pytest.raises(RuntimeError, match="num_shards must be divisible by world_size"): +# with pytest.raises( +# RuntimeError, +# match="num_shards must be divisible by world_size" +# ): # builder.build("train") # def test_sharded_dataset_missing_shard_method(): # organizer = build_organizer( -# DUMMY_MISSING_SHARD_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# DUMMY_MISSING_SHARD_TARGET, +# dataset_kwargs={"num_shards": 2, "world_shard_size": 1} # ) # config = make_standard_dataloader_config() # builder = build_builder( @@ -567,7 +575,8 @@ def test_iter_factory_with_collate_fn(tmp_path): # monkeypatch.setattr(torch.distributed, "get_rank", _get_rank) # organizer = build_organizer( -# DUMMY_SHARDED_DATASET_TARGET, dataset_kwargs={"num_shards": 2, "world_shard_size": 1} +# DUMMY_SHARDED_DATASET_TARGET, +# dataset_kwargs={"num_shards": 2, "world_shard_size": 1} # ) # config = make_standard_dataloader_config() # builder = build_builder( diff --git a/test/espnet3/systems/base/test_inference_runner.py b/test/espnet3/systems/base/test_inference_runner.py index d591078dce41..34d4cb3d6ab3 100644 --- a/test/espnet3/systems/base/test_inference_runner.py +++ b/test/espnet3/systems/base/test_inference_runner.py @@ -94,9 +94,7 @@ def test_call_returns_none(monkeypatch): def test_call_propagates_validation_error(monkeypatch): - monkeypatch.setattr( - BaseRunner, "__call__", lambda self, indices: [{"hyp": "h"}] - ) + monkeypatch.setattr(BaseRunner, "__call__", lambda self, indices: [{"hyp": "h"}]) runner = DummyRunner(DummyProvider()) with pytest.raises(ValueError, match="idx_key='utt_id'"): From 34f7978becc7e640f0ddf355d0177c6be02b43af Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 12 Mar 2026 16:36:35 -0400 Subject: [PATCH 55/67] Fixed configs and refactored run.py accordingly --- egs3/TEMPLATE/asr/conf/inference.yaml | 5 +- egs3/TEMPLATE/asr/conf/metrics.yaml | 2 +- egs3/TEMPLATE/asr/conf/training.yaml | 12 +- egs3/TEMPLATE/asr/run.py | 195 +++--------------- egs3/mini_an4/asr/conf/inference.yaml | 4 + egs3/mini_an4/asr/conf/metrics.yaml | 8 +- egs3/mini_an4/asr/conf/training_asr_rnn.yaml | 1 - .../asr/conf/training_asr_rnn_data_aug.yaml | 3 +- egs3/mini_an4/asr/run.py | 1 - espnet3/components/data/data_organizer.py | 16 +- espnet3/systems/base/inference_provider.py | 13 +- espnet3/utils/config_utils.py | 178 +++++++++++++++- espnet3/utils/logging_utils.py | 94 ++++++++- espnet3/utils/stages_utils.py | 66 +++++- espnet3/utils/task_utils.py | 13 +- test/egs3/TEMPLATE/asr/test_run.py | 22 +- test/espnet3/utils/test_config.py | 174 ++++++++++++++++ test/espnet3/utils/test_stages.py | 7 +- 18 files changed, 584 insertions(+), 230 deletions(-) diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index 87021da03c82..ee56f10443aa 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -11,9 +11,9 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:conf/training.yaml,exp_dir} +exp_dir: ${load_yaml:training.yaml,exp_dir} inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} +dataset_dir: ${load_yaml:training.yaml,dataset_dir} # Test split definitions are required for inference. # `dataset.test[*].name` becomes the output subdirectory name under @@ -34,6 +34,7 @@ dataset_dir: ${load_yaml:conf/training.yaml,dataset_dir} dataset: _target_: espnet3.components.data.data_organizer.DataOrganizer test: + preprocessor: ########################################################## # PARALLELIZATION SETTING # diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 747f6ec7048c..4bebf4a7061a 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -13,7 +13,7 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:conf/training.yaml,exp_dir} +exp_dir: ${load_yaml:training.yaml,exp_dir} inference_dir: ${exp_dir}/inference diff --git a/egs3/TEMPLATE/asr/conf/training.yaml b/egs3/TEMPLATE/asr/conf/training.yaml index 7bf3243e72ac..e7b89ce80b37 100644 --- a/egs3/TEMPLATE/asr/conf/training.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -81,16 +81,6 @@ dataset: # - a path to a text file, or # - an iterable of training strings tokenizer: - save_path: ${exp_dir}/tokenizer - vocab_size: 500 - model_type: bpe - # Optional explicit output file for tokenizer training text. - # If unset, `${tokenizer.save_path}/train.txt` is used. - train_file: - text_builder: - func: src.tokenizer.build_text - dataset_dir: ${dataset_dir} - split: train ########################################################## # PARALLELIZATION SETTING # @@ -116,7 +106,7 @@ model: dataloader: collate_fn: _target_: espnet2.train.collate_fn.CommonCollateFn - + int_pad_value: -1 # Training dataloader / iterator settings. train: multiple_iterator: false diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index abf3ba860862..5c86a2a73165 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -5,20 +5,16 @@ import argparse import logging -import sys -from importlib import resources from pathlib import Path -from typing import Any, Callable, List, Sequence, Tuple, Type - -from omegaconf import OmegaConf - -from espnet3.utils.config_utils import load_config_with_defaults -from espnet3.utils.logging_utils import ( - configure_logging, - log_env_metadata, - log_run_metadata, +from typing import List, Sequence + +from espnet3.utils.config_utils import load_and_merge_config +from espnet3.utils.logging_utils import configure_logging +from espnet3.utils.stages_utils import ( + parse_cli_and_stage_args, + resolve_stages, + run_stages, ) -from espnet3.utils.stages_utils import resolve_stages, run_stages # Default stage list (can be extended/overridden by callers) DEFAULT_STAGES: List[str] = [ @@ -31,8 +27,6 @@ ] # Type alias for a System class -SystemCls = Type[Any] -AddArgsFn = Callable[[argparse.ArgumentParser], None] logger = logging.getLogger(__name__) @@ -82,118 +76,9 @@ def build_parser( ) return parser - -def parse_cli_and_stage_args( - parser: argparse.ArgumentParser, - stages: Sequence[str], -) -> Tuple[argparse.Namespace, List[str]]: - args = parser.parse_args() - stages_to_run = resolve_stages(args.stages, stages) - - return args, stages_to_run - - -def _resolve_template_config_filename(config_arg_name: str) -> str: - """Resolve template YAML filename from a CLI config argument key. - - Args: - config_arg_name: Internal config argument key name - (``train_config``, ``infer_config``, or ``measure_config``). - - Returns: - str: Template config filename under ``egs3.TEMPLATE.asr/conf``. - - Raises: - ValueError: If an unknown config argument name is provided. - - Examples: - >>> _resolve_template_config_filename("train_config") - 'training.yaml' - >>> _resolve_template_config_filename("infer_config") - 'inference.yaml' - - Todo: - If new config are added to CLI options, extend this mapping. - """ - # Stage/method names use verbs, while config filenames use noun forms. - if config_arg_name == "train_config": - return "training.yaml" - if config_arg_name == "infer_config": - return "inference.yaml" - if config_arg_name == "measure_config": - return "metrics.yaml" - raise ValueError(f"Unknown config argument name: {config_arg_name}") - - -def _load_template_defaults(config_arg_name: str): - """Load packaged TEMPLATE defaults by config kind. - - Args: - config_arg_name: Internal config argument key name - (``train_config``, ``infer_config``, or ``measure_config``). - - Returns: - DictConfig: Loaded template default config. - - Examples: - >>> cfg = _load_template_defaults("train_config") - >>> "dataset" in cfg - True - >>> cfg = _load_template_defaults("infer_config") - >>> cfg.get("provider", {}).get("_target_") is not None - True - - Note: - Uses ``importlib.resources`` to avoid hard-coded file system paths, so - it also works after ``pip install`` as package data. - - """ - filename = _resolve_template_config_filename(config_arg_name) - package = "egs3.TEMPLATE.asr" - resource = resources.files(package).joinpath("conf", filename) - with resources.as_file(resource) as path: - return load_config_with_defaults(str(path)) - return OmegaConf.create({}) - - -def _load_and_merge_config(config_path: Path | None, config_arg_name: str): - """Load user config and merge with TEMPLATE defaults. - - Args: - config_path: Path to the user-provided YAML config. If ``None``, - this function returns ``None``. - config_arg_name: Internal config argument key name used to select - the corresponding TEMPLATE default config. - - Returns: - DictConfig | None: Merged config if ``config_path`` is provided, - otherwise ``None``. - - Examples: - >>> cfg = _load_and_merge_config( - ... Path("egs3/mini_an4/asr/conf/inference.yaml"), - ... "infer_config", - ... ) - >>> cfg.provider._target_ - 'espnet3.systems.base.inference_provider.InferenceProvider' - >>> _load_and_merge_config(None, "measure_config") is None - True - - Note: - Merge order is ``template_defaults -> user_config``. User config wins - on key conflicts, so recipe-specific overrides remain explicit. - - """ - if config_path is None: - return None - user_cfg = load_config_with_defaults(config_path) - default_cfg = _load_template_defaults(config_arg_name) - return OmegaConf.merge(default_cfg, user_cfg) - - def main( args, - system_cls: SystemCls, + system_cls, stages: Sequence[str] = DEFAULT_STAGES, ) -> None: stages_to_run = resolve_stages(args.stages, stages) @@ -201,9 +86,21 @@ def main( # ----------------------------------------- # Load configs # ----------------------------------------- - train_config = _load_and_merge_config(args.train_config, "train_config") - infer_config = _load_and_merge_config(args.infer_config, "infer_config") - measure_config = _load_and_merge_config(args.measure_config, "measure_config") + train_config = load_and_merge_config( + args.train_config, + "train_config", + template_package=__package__, + ) + infer_config = load_and_merge_config( + args.infer_config, + "infer_config", + template_package=__package__, + ) + measure_config = load_and_merge_config( + args.measure_config, + "measure_config", + template_package=__package__, + ) logger = configure_logging() @@ -247,51 +144,9 @@ def main( run_stages( system=system, stages_to_run=stages_to_run, - dry_run=args.dry_run, + args=args, log=logger, - on_stage_start=lambda stage, log: _log_stage_metadata( - log, - args=args, - train_config=train_config, - infer_config=infer_config, - measure_config=measure_config, - ), - ) - - -def _log_stage_metadata( - logger, - args: argparse.Namespace, - train_config, - infer_config, - measure_config, -) -> None: - log_run_metadata( - logger, - argv=sys.argv, - configs={ - "Training": Path(args.train_config) if args.train_config else None, - "Inference": Path(args.infer_config) if args.infer_config else None, - "Metrics": Path(args.measure_config) if args.measure_config else None, - }, - write_requirements=args.write_requirements, ) - log_env_metadata(logger) - if train_config is not None: - logger.info( - "Training config content:\n%s", - OmegaConf.to_yaml(train_config, resolve=True), - ) - if infer_config is not None: - logger.info( - "Inference config content:\n%s", - OmegaConf.to_yaml(infer_config, resolve=True), - ) - if measure_config is not None: - logger.info( - "Metrics config content:\n%s", - OmegaConf.to_yaml(measure_config, resolve=True), - ) if __name__ == "__main__": diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 55be843517bb..012b55a1ff2a 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -1,5 +1,9 @@ # Mini AN4 ASR inference config for ESPnet3 integration tests. +exp_dir: ${load_yaml:training.yaml,exp_dir} +inference_dir: ${exp_dir}/inference +dataset_dir: ${load_yaml:training.yaml,dataset_dir} + dataset: test: - name: test diff --git a/egs3/mini_an4/asr/conf/metrics.yaml b/egs3/mini_an4/asr/conf/metrics.yaml index fc3062e20ac5..c6d0a5d35d4c 100644 --- a/egs3/mini_an4/asr/conf/metrics.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -1,11 +1,7 @@ # Mini AN4 ASR scoring config for ESPnet3 integration tests. -dataset: - test: - - name: test - dataset: - _target_: src.dataset.MiniAN4Dataset - manifest_path: ${dataset_dir}/manifest/test.tsv +exp_dir: ${load_yaml:training.yaml,exp_dir} +inference_dir: ${exp_dir}/inference metrics: - metric: diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml index 7a6e5a0c1d50..b5a17aedc41b 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml @@ -24,7 +24,6 @@ dataset: manifest_path: ${dataset_dir}/manifest/train_dev.tsv preprocessor: _target_: espnet2.train.preprocessor.CommonPreprocessor - _convert_: all fs: 16000 train: true data_aug_effects: # no need to set the "sample_rate" argument for each effect here diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index d1036b9b768b..a9db610023af 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -24,7 +24,6 @@ dataset: manifest_path: ${dataset_dir}/manifest/train_dev.tsv preprocessor: _target_: espnet2.train.preprocessor.CommonPreprocessor - _convert_: all fs: 16000 train: true data_aug_effects: # no need to set the "sample_rate" argument for each effect here @@ -54,7 +53,7 @@ optimizer: lr: 0.001 weight_decay: 0.0 -scheduler: +override scheduler: _target_: torch.optim.lr_scheduler.ReduceLROnPlateau mode: min factor: 0.5 diff --git a/egs3/mini_an4/asr/run.py b/egs3/mini_an4/asr/run.py index 4518f36ef3c7..46470cc0db75 100644 --- a/egs3/mini_an4/asr/run.py +++ b/egs3/mini_an4/asr/run.py @@ -9,7 +9,6 @@ if __name__ == "__main__": parser = build_parser( stages=DEFAULT_STAGES, - add_arguments=None, ) args, _ = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) diff --git a/espnet3/components/data/data_organizer.py b/espnet3/components/data/data_organizer.py index 281c68e709f0..344c43802b0a 100644 --- a/espnet3/components/data/data_organizer.py +++ b/espnet3/components/data/data_organizer.py @@ -181,10 +181,12 @@ def build_dataset_list(config_list): dataset = config.dataset if isinstance(dataset, (dict, DictConfig)): dataset = instantiate(dataset) - if hasattr(config, "transform"): + + if hasattr(config, "transform") and config.transform is not None: transform = config.transform else: transform = do_nothing + if isinstance(transform, (dict, DictConfig)): transform = instantiate(transform) @@ -226,11 +228,21 @@ def build_dataset_list(config_list): self.test_sets = {} if test is not None: for config in test: + if isinstance(config, dict): + config = DatasetConfig(**config) + dataset = config.dataset - if hasattr(config, "transform"): + if isinstance(dataset, (dict, DictConfig)): + dataset = instantiate(dataset) + + if hasattr(config, "transform") and config.transform is not None: transform = config.transform else: transform = do_nothing + + if isinstance(transform, (dict, DictConfig)): + transform = instantiate(transform) + self.test_sets[config.name] = DatasetWithTransform( dataset, transform, diff --git a/espnet3/systems/base/inference_provider.py b/espnet3/systems/base/inference_provider.py index 82a6e84e2dfe..3834e51b6c03 100644 --- a/espnet3/systems/base/inference_provider.py +++ b/espnet3/systems/base/inference_provider.py @@ -7,7 +7,7 @@ import torch from hydra.utils import instantiate -from omegaconf import DictConfig +from omegaconf import DictConfig, OmegaConf from espnet3.parallel.env_provider import EnvironmentProvider from espnet3.utils.logging_utils import log_instance_dict @@ -157,7 +157,13 @@ def build_dataset(config: DictConfig): - Rely on fields already present in ``config`` instead of reading global state whenever possible. """ - organizer = instantiate(config.dataset) + if isinstance(config, dict): + config = OmegaConf.create(config) + organizer = instantiate(config.dataset) + + if isinstance(config, DictConfig): + organizer = instantiate(config.dataset) + test_set = config.test_set logger.info("Building dataset for test set: %s", test_set) return organizer.test[test_set] @@ -193,6 +199,9 @@ def build_model(config: DictConfig): - Do not perform training/optimization here, this is for inference setup only. """ + if isinstance(config, dict): + config = OmegaConf.create(config) + device = "cuda" if torch.cuda.is_available() else "cpu" if device == "cuda": device_id = os.getenv("CUDA_VISIBLE_DEVICES", "0").split(",")[0].strip() diff --git a/espnet3/utils/config_utils.py b/espnet3/utils/config_utils.py index e00d40b9ab10..678d365f71ab 100644 --- a/espnet3/utils/config_utils.py +++ b/espnet3/utils/config_utils.py @@ -1,10 +1,16 @@ """Configuration helpers and OmegaConf resolvers for ESPnet3.""" import logging +import re +from importlib import resources from pathlib import Path from omegaconf import DictConfig, ListConfig, OmegaConf +_RELATIVE_RESOLVER_PATTERN = re.compile( + r"\$\{(?Pload_line|load_yaml):(?P[^,}]+)" +) + def load_line(path): """Load lines from a text file and return as a list of strings. @@ -45,8 +51,9 @@ def load_yaml(path, key=None): Returns: Any: The selected value or the full config if key is None. """ + cfg_path = Path(path) try: - cfg = OmegaConf.load(path) + cfg = _load_yaml_for_resolver(cfg_path) except FileNotFoundError: logging.error(f"File not found: {path}") raise @@ -63,6 +70,19 @@ def load_yaml(path, key=None): return value +def _load_yaml_for_resolver(path: Path): + config_arg_name = _resolve_template_config_arg_name(path.name) + if config_arg_name is not None: + template_package = _infer_template_package_from_config_path(path) + if template_package is not None: + return load_and_merge_config( + path, + config_arg_name, + template_package=template_package, + ) + return OmegaConf.load(path) + + OMEGACONF_ESPNET3_RESOLVER = { "load_line": load_line, "load_yaml": load_yaml, @@ -72,7 +92,11 @@ def load_yaml(path, key=None): logging.info(f"Registered ESPnet-3 OmegaConf Resolver: {name}") -def _process_dict_config_entry(entry: DictConfig, base_path: Path) -> list: +def _process_dict_config_entry( + entry: DictConfig, + base_path: Path, + resolve: bool = True, +) -> list: results = [] for key, val in entry.items(): # Skip null entries (can be used for disabling config entries) @@ -83,15 +107,17 @@ def _process_dict_config_entry(entry: DictConfig, base_path: Path) -> list: # or use as-is if path includes '/' composed = f"{key}/{val}" if "/" not in val else val config_path = _build_config_path(base_path, composed) - results.append({key: load_config_with_defaults(str(config_path))}) + results.append( + {key: load_config_with_defaults(str(config_path), resolve=resolve)} + ) return results -def load_config_with_defaults(path: str) -> OmegaConf: +def load_config_with_defaults(path: str, resolve: bool = True) -> OmegaConf: """Load an YAML config with recursive `_self_` merging via Hydra-style `defaults`. This function recursively loads and merges dependent YAML files specified - in the `defaults` key of the given config. It mimics Hydra’s composition mechanism + in the `defaults` key of the given config. It mimics Hydra's composition mechanism without using Hydra's runtime, which makes it suitable for standalone YAML handling (e.g., for distributed training or script-based training setups). @@ -114,12 +140,14 @@ def load_config_with_defaults(path: str) -> OmegaConf: Args: path (str): Path to the main YAML config file. + resolve (bool): Whether to resolve interpolations after merging. Returns: OmegaConf.DictConfig: Fully resolved and merged configuration object. """ base_path = Path(path).parent main_config = OmegaConf.load(path) + _normalize_relative_resolver_paths(main_config, base_path) config_self = main_config.copy() if "defaults" not in main_config: @@ -135,10 +163,14 @@ def load_config_with_defaults(path: str) -> OmegaConf: self_merged = True else: config_path = _build_config_path(base_path, entry) - merged_configs.append(load_config_with_defaults(str(config_path))) + merged_configs.append( + load_config_with_defaults(str(config_path), resolve=resolve) + ) elif isinstance(entry, DictConfig): - merged_configs.extend(_process_dict_config_entry(entry, base_path)) + merged_configs.extend( + _process_dict_config_entry(entry, base_path, resolve=resolve) + ) elif entry == "_self_": merged_configs.append(config_self) @@ -148,7 +180,9 @@ def load_config_with_defaults(path: str) -> OmegaConf: merged_configs.append(config_self) final_config = OmegaConf.merge(*merged_configs) - OmegaConf.resolve(final_config) + + if resolve: + OmegaConf.resolve(final_config) if "defaults" in final_config: del final_config["defaults"] @@ -157,6 +191,36 @@ def load_config_with_defaults(path: str) -> OmegaConf: return final_config +def load_template_defaults(config_arg_name: str, template_package: str): + """Load packaged TEMPLATE defaults by config kind.""" + filename = _resolve_template_config_filename(config_arg_name) + resource = resources.files(template_package).joinpath("conf", filename) + with resources.as_file(resource) as path: + return load_config_with_defaults(str(path), resolve=False) + + +def load_and_merge_config( + config_path: Path | None, + config_arg_name: str, + template_package: str | None = None, +): + """Load user config and merge it with TEMPLATE defaults.""" + if config_path is None: + return None + if template_package is None: + template_package = _infer_template_package_from_config_path(config_path) + if template_package is None: + raise ValueError( + "template_package is required when it cannot be inferred from config_path" + ) + default_cfg = load_template_defaults(config_arg_name, template_package) + user_cfg = load_config_with_defaults(str(config_path), resolve=False) + merged_cfg = OmegaConf.merge(default_cfg, user_cfg) + OmegaConf.resolve(merged_cfg) + _ensure_target_convert_all(merged_cfg) + return merged_cfg + + def _ensure_target_convert_all(cfg) -> None: if isinstance(cfg, DictConfig): if "_target_" in cfg: @@ -168,6 +232,65 @@ def _ensure_target_convert_all(cfg) -> None: _ensure_target_convert_all(value) +def _normalize_relative_resolver_paths(cfg, base_path: Path) -> None: + if isinstance(cfg, DictConfig): + for key in list(cfg.keys()): + value = cfg._get_node(key) + if isinstance(value, (DictConfig, ListConfig)): + _normalize_relative_resolver_paths(value, base_path) + else: + raw_value = value._value() + if isinstance(raw_value, str): + cfg[key] = _rewrite_relative_resolver_paths(raw_value, base_path) + elif isinstance(cfg, ListConfig): + for idx in range(len(cfg)): + value = cfg._get_node(idx) + if isinstance(value, (DictConfig, ListConfig)): + _normalize_relative_resolver_paths(value, base_path) + else: + raw_value = value._value() + if isinstance(raw_value, str): + cfg[idx] = _rewrite_relative_resolver_paths(raw_value, base_path) + + +def _rewrite_relative_resolver_paths(value: str, base_path: Path) -> str: + def replace(match: re.Match) -> str: + resolver = match.group("resolver") + raw_path = match.group("path").strip() + + quote = "" + normalized_path = raw_path + if ( + len(raw_path) >= 2 + and raw_path[0] == raw_path[-1] + and raw_path[0] + in ( + "'", + '"', + ) + ): + quote = raw_path[0] + normalized_path = raw_path[1:-1].strip() + + # Leave dynamic or already-absolute paths untouched. + if "${" in normalized_path or Path(normalized_path).is_absolute(): + return match.group(0) + + base_relative_path = base_path / normalized_path + workspace_relative_path = Path(normalized_path) + if normalized_path.startswith(("./", "../")) or base_relative_path.exists(): + resolved_path = base_relative_path.absolute().as_posix() + elif workspace_relative_path.exists(): + resolved_path = workspace_relative_path.absolute().as_posix() + else: + resolved_path = base_relative_path.absolute().as_posix() + if quote: + resolved_path = f"{quote}{resolved_path}{quote}" + return f"${{{resolver}:{resolved_path}" + + return _RELATIVE_RESOLVER_PATTERN.sub(replace, value) + + def _build_config_path(base_path: Path, entry: str) -> Path: entry_path = Path(entry) if entry_path.suffix and entry_path.suffix != ".yaml": @@ -178,3 +301,42 @@ def _build_config_path(base_path: Path, entry: str) -> Path: if not entry_path.suffix: entry += ".yaml" return base_path / entry + + +def _resolve_template_config_filename(config_arg_name: str) -> str: + if config_arg_name == "train_config": + return "training.yaml" + if config_arg_name == "infer_config": + return "inference.yaml" + if config_arg_name == "measure_config": + return "metrics.yaml" + raise ValueError(f"Unknown config argument name: {config_arg_name}") + + +def _resolve_template_config_arg_name(filename: str) -> str | None: + if filename == "training.yaml": + return "train_config" + if filename == "inference.yaml": + return "infer_config" + if filename == "metrics.yaml": + return "measure_config" + return None + + +def _infer_template_package_from_config_path(config_path: Path) -> str | None: + parts = config_path.resolve().parts + try: + egs3_index = parts.index("egs3") + except ValueError: + return None + + conf_index = None + for index in range(egs3_index + 1, len(parts)): + if parts[index] == "conf": + conf_index = index + break + if conf_index is None or conf_index - egs3_index < 3: + return None + + task_name = parts[conf_index - 1] + return f"egs3.TEMPLATE.{task_name}" diff --git a/espnet3/utils/logging_utils.py b/espnet3/utils/logging_utils.py index 797e6a6389db..979b75568a33 100644 --- a/espnet3/utils/logging_utils.py +++ b/espnet3/utils/logging_utils.py @@ -2,6 +2,7 @@ from __future__ import annotations +import argparse import contextvars import logging import os @@ -14,9 +15,10 @@ from datetime import datetime from pathlib import Path from shutil import which -from typing import Mapping +from typing import Any, Mapping import torch +from omegaconf import OmegaConf LOG_FORMAT = ( "[%(hostname)s] %(asctime)s (%(filename)s:%(lineno)d) " @@ -52,6 +54,96 @@ def log_stage(name: str): _LOG_STAGE.reset(token) +def log_stage_metadata( + logger: logging.Logger, + system: Any, + args: argparse.Namespace | None, +) -> None: + """Write per-stage metadata into the active stage log. + + This helper records the invocation context that is useful when auditing a + stage log after the fact: CLI command line, selected config file paths, + environment metadata, and the resolved in-memory configs attached to the + system object. + + Args: + logger (logging.Logger): Logger that should receive the metadata + entries. In practice this is the stage logger configured immediately + before a stage starts. + system (Any): Instantiated system object. When present, the attributes + ``train_config``, ``infer_config``, and ``measure_config`` are read + and dumped as resolved YAML for reproducibility. + args (argparse.Namespace | None): Parsed CLI namespace. The function + reads ``train_config``, ``infer_config``, ``measure_config``, and + ``write_requirements`` from this namespace when available. + + Returns: + None: This function is logging-only and does not return a value. + + Examples: + >>> from argparse import Namespace + >>> class DummySystem: + ... train_config = {"exp_dir": "./exp/train"} + ... infer_config = None + ... measure_config = None + >>> log_stage_metadata( + ... logging.getLogger("espnet3"), + ... system=DummySystem(), + ... args=Namespace( + ... train_config="conf/training.yaml", + ... infer_config=None, + ... measure_config=None, + ... write_requirements=False, + ... ), + ... ) + + """ + train_config = getattr(system, "train_config", None) + infer_config = getattr(system, "infer_config", None) + measure_config = getattr(system, "measure_config", None) + + log_run_metadata( + logger, + argv=sys.argv, + configs={ + "Training": ( + Path(args.train_config) + if args is not None and getattr(args, "train_config", None) + else None + ), + "Inference": ( + Path(args.infer_config) + if args is not None and getattr(args, "infer_config", None) + else None + ), + "Metrics": ( + Path(args.measure_config) + if args is not None and getattr(args, "measure_config", None) + else None + ), + }, + write_requirements=bool( + getattr(args, "write_requirements", False) if args is not None else False + ), + ) + log_env_metadata(logger) + if train_config is not None: + logger.info( + "Training config content:\n%s", + OmegaConf.to_yaml(train_config, resolve=True), + ) + if infer_config is not None: + logger.info( + "Inference config content:\n%s", + OmegaConf.to_yaml(infer_config, resolve=True), + ) + if measure_config is not None: + logger.info( + "Metrics config content:\n%s", + OmegaConf.to_yaml(measure_config, resolve=True), + ) + + def set_log_format( log_format: str | None = None, date_format: str | None = None, diff --git a/espnet3/utils/stages_utils.py b/espnet3/utils/stages_utils.py index 39fb63fba03e..41329e9f3a2d 100644 --- a/espnet3/utils/stages_utils.py +++ b/espnet3/utils/stages_utils.py @@ -2,13 +2,18 @@ from __future__ import annotations +import argparse import logging import os import time from pathlib import Path -from typing import Any, Iterable, List, Sequence +from typing import Any, Iterable, List, Sequence, Tuple -from espnet3.utils.logging_utils import log_stage, set_stage_log_handler +from espnet3.utils.logging_utils import ( + log_stage, + log_stage_metadata, + set_stage_log_handler, +) logger = logging.getLogger(__name__) @@ -64,23 +69,64 @@ def resolve_stages( return [s for s in stages if s in requested_set] +def parse_cli_and_stage_args( + parser: argparse.ArgumentParser, + stages: Sequence[str], +) -> Tuple[argparse.Namespace, List[str]]: + """Parse CLI arguments and expand the requested stage selection. + + This helper is a thin wrapper around ``ArgumentParser.parse_args()`` plus + :func:`resolve_stages`. It keeps the runner entrypoints concise and ensures + the `"all"` shorthand is expanded consistently across recipes. + + Args: + parser (argparse.ArgumentParser): Parser configured by the recipe + entrypoint. It is expected to define a ``--stages`` argument whose + value is compatible with ``resolve_stages(...)``. + stages (Sequence[str]): Ordered list of stage names supported by the + current runner, for example ``["create_dataset", "train", "infer"]``. + + Returns: + Tuple[argparse.Namespace, List[str]]: A pair containing: + - the parsed CLI namespace returned by ``parser.parse_args()`` + - the resolved list of stages to execute, preserving the canonical + order from ``stages`` + + Examples: + >>> parser = argparse.ArgumentParser() + >>> parser.add_argument("--stages", nargs="+", default=["all"]) + >>> # If argv is: ["--stages", "infer", "train"] + >>> args, stages_to_run = parse_cli_and_stage_args( + ... parser, + ... ["create_dataset", "train", "infer"], + ... ) + >>> stages_to_run + ['train', 'infer'] + + Notes: + The returned stage order is not the same as CLI input order when they + differ. The canonical order defined by ``stages`` always wins so stage + execution remains deterministic. + """ + args = parser.parse_args() + stages_to_run = resolve_stages(args.stages, stages) + return args, stages_to_run + + def run_stages( system: Any, stages_to_run: Iterable[str], - dry_run: bool = False, + args: argparse.Namespace | None = None, log: logging.Logger | None = None, - on_stage_start: callable | None = None, ) -> None: """Invoke stage methods on ``system`` in order with logging and timing. Args: system: Object providing stage methods named in ``stages_to_run``. stages_to_run: Iterable of stage method names to execute. - dry_run: If True, log intended stages without executing them. + args: Parsed CLI arguments. ``dry_run`` and ``write_requirements`` are + read from here when present. log: Optional logger instance; defaults to module logger. - on_stage_start: Optional hook invoked after stage logging is configured. - This can be used to emit per-stage metadata (configs, environment, - requirements snapshots, etc.) into the newly attached log file. Raises: AttributeError: If a named stage method is missing on ``system``. @@ -88,6 +134,7 @@ def run_stages( Exception: Re-raises any exception from a stage method. """ log = log or logger + dry_run = bool(getattr(args, "dry_run", False)) for stage in stages_to_run: fn = getattr(system, stage, None) if fn is None: @@ -129,8 +176,7 @@ def run_stages( Path(log_dir) if log_dir else None, filename=filename, ) - if on_stage_start is not None: - on_stage_start(stage, log) + log_stage_metadata(log, system=system, args=args) start = time.perf_counter() log.info("=== [START] stage: %s ===", stage) diff --git a/espnet3/utils/task_utils.py b/espnet3/utils/task_utils.py index 4bc22e4c478f..e7be586c40ad 100644 --- a/espnet3/utils/task_utils.py +++ b/espnet3/utils/task_utils.py @@ -5,12 +5,12 @@ from pathlib import Path from typing import Dict, Union -import yaml from hydra.utils import get_class from omegaconf import DictConfig, OmegaConf from typeguard import typechecked from espnet2.train.abs_espnet_model import AbsESPnetModel +from espnet2.utils.yaml_no_alias_safe_dump import yaml_no_alias_safe_dump def get_task_class(task_path: str): @@ -89,8 +89,11 @@ def save_espnet_config( default_config[k] = list(v) # Save the config to the output directory - output_dir = Path(output_dir) - output_dir.mkdir(parents=True, exist_ok=True) - output_path = output_dir / "config.yaml" + output_path = Path(output_dir) + if output_path.suffix: + output_path.parent.mkdir(parents=True, exist_ok=True) + else: + output_path.mkdir(parents=True, exist_ok=True) + output_path = output_path / "config.yaml" with open(output_path, "w", encoding="utf-8") as f: - yaml.dump(default_config, f) + f.write(yaml_no_alias_safe_dump(default_config, indent=4, sort_keys=False)) diff --git a/test/egs3/TEMPLATE/asr/test_run.py b/test/egs3/TEMPLATE/asr/test_run.py index 5ff88d2259c8..bd6f85059896 100644 --- a/test/egs3/TEMPLATE/asr/test_run.py +++ b/test/egs3/TEMPLATE/asr/test_run.py @@ -2,9 +2,9 @@ import pytest -from egs3.TEMPLATE.asr.run import ( - _load_and_merge_config, - _load_template_defaults, +from egs3.TEMPLATE.asr.run import _load_and_merge_config +from espnet3.utils.config_utils import ( + load_template_defaults, _resolve_template_config_filename, ) @@ -21,7 +21,7 @@ def test_resolve_template_config_filename_invalid() -> None: def test_load_template_defaults_train_contains_expected_targets() -> None: - cfg = _load_template_defaults("train_config") + cfg = load_template_defaults("train_config", "egs3.TEMPLATE.asr") assert ( cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" @@ -31,7 +31,7 @@ def test_load_template_defaults_train_contains_expected_targets() -> None: def test_load_template_defaults_infer_contains_expected_targets() -> None: - cfg = _load_template_defaults("infer_config") + cfg = load_template_defaults("infer_config", "egs3.TEMPLATE.asr") assert ( cfg.provider._target_ == "espnet3.systems.base.inference_provider.InferenceProvider" @@ -55,7 +55,11 @@ def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) encoding="utf-8", ) - cfg = _load_and_merge_config(user, "train_config") + cfg = _load_and_merge_config( + user, + "train_config", + template_package="egs3.TEMPLATE.asr", + ) assert cfg is not None # user config should override template default target @@ -69,4 +73,8 @@ def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) def test_load_and_merge_config_none_path_returns_none() -> None: - assert _load_and_merge_config(None, "measure_config") is None + assert _load_and_merge_config( + None, + "measure_config", + template_package="egs3.TEMPLATE.asr", + ) is None diff --git a/test/espnet3/utils/test_config.py b/test/espnet3/utils/test_config.py index b9dad35dbe15..79eb1b60a5f0 100644 --- a/test/espnet3/utils/test_config.py +++ b/test/espnet3/utils/test_config.py @@ -7,8 +7,10 @@ from espnet3.utils.config_utils import ( _build_config_path, _ensure_target_convert_all, + load_and_merge_config, load_config_with_defaults, load_line, + load_template_defaults, load_yaml, ) @@ -248,6 +250,28 @@ def test_defaults_removed_after_merge(write_yaml): assert "defaults" not in cfg +def test_load_yaml_relative_path_survives_merge(write_yaml): + write_yaml( + "conf/training.yaml", + """ +exp_dir: ./exp/train_debug +dataset_dir: ./data/mini_an4 +""", + ) + path = write_yaml( + "conf/inference.yaml", + """ +exp_dir: ${load_yaml:training.yaml,exp_dir} +dataset_dir: ${load_yaml:training.yaml,dataset_dir} +""", + ) + cfg = load_config_with_defaults(str(path)) + merged = OmegaConf.merge(OmegaConf.create({"provider": {"name": "dummy"}}), cfg) + + assert merged.exp_dir == "./exp/train_debug" + assert merged.dataset_dir == "./data/mini_an4" + + def test_missing_file_raises(tmp_path): """Test that loading a config with a missing file in `defaults` @@ -316,6 +340,156 @@ def test_load_yaml_missing_key_raises(write_yaml): load_yaml(str(path), "missing.key") +def test_load_yaml_training_config_merges_template_before_select( + write_yaml, monkeypatch +): + template = write_yaml( + "template.yaml", + """ +data_dir: ./data +dataset_dir: ${data_dir}/default +""", + ) + training = write_yaml( + "training.yaml", + """ +dataset_dir: ${data_dir}/mini_an4 +""", + ) + + monkeypatch.setattr( + "espnet3.utils.config_utils.load_template_defaults", + lambda _, __: load_config_with_defaults(str(template), resolve=False), + ) + monkeypatch.setattr( + "espnet3.utils.config_utils._infer_template_package_from_config_path", + lambda _: "dummy.package", + ) + + assert load_yaml(str(training), "dataset_dir") == "./data/mini_an4" + + +def test_load_template_defaults_train(): + cfg = load_template_defaults("train_config", "egs3.TEMPLATE.asr") + assert "dataset" in cfg + assert "exp_dir" in cfg + + +def test_load_and_merge_config_none(): + assert load_and_merge_config(None, "measure_config") is None + + +def test_load_and_merge_config_resolves_user_reference_to_template_value( + write_yaml, monkeypatch +): + template = write_yaml( + "template.yaml", + """ +exp_dir: ./exp/from_template +inference_dir: ${exp_dir}/inference +""", + ) + user = write_yaml( + "user.yaml", + """ +custom_dir: ${exp_dir}/custom +""", + ) + + monkeypatch.setattr( + "espnet3.utils.config_utils.load_template_defaults", + lambda _, __: load_config_with_defaults(str(template), resolve=False), + ) + + cfg = load_and_merge_config(user, "train_config", template_package="dummy.package") + + assert cfg.exp_dir == "./exp/from_template" + assert cfg.inference_dir == "./exp/from_template/inference" + assert cfg.custom_dir == "./exp/from_template/custom" + + +def test_load_and_merge_config_resolves_template_reference_to_user_override( + write_yaml, monkeypatch +): + template = write_yaml( + "template.yaml", + """ +exp_dir: ./exp/from_template +custom_dir: ${exp_dir}/custom +""", + ) + user = write_yaml( + "user.yaml", + """ +exp_dir: ./exp/from_user +""", + ) + + monkeypatch.setattr( + "espnet3.utils.config_utils.load_template_defaults", + lambda _, __: load_config_with_defaults(str(template), resolve=False), + ) + + cfg = load_and_merge_config(user, "train_config", template_package="dummy.package") + + assert cfg.exp_dir == "./exp/from_user" + assert cfg.custom_dir == "./exp/from_user/custom" + + +def test_load_and_merge_infer_config_can_read_training_yaml_with_template_values( + write_yaml, monkeypatch +): + template_infer = write_yaml( + "template_inference.yaml", + """ +exp_dir: ${load_yaml:training.yaml,exp_dir} +dataset_dir: ${load_yaml:training.yaml,dataset_dir} +""", + ) + template_train = write_yaml( + "template_training.yaml", + """ +data_dir: ./data +exp_dir: ./exp/default +dataset_dir: ${data_dir}/default +""", + ) + write_yaml( + "training.yaml", + """ +exp_dir: ./exp/train_debug +dataset_dir: ${data_dir}/mini_an4 +""", + ) + inference = write_yaml("inference.yaml", "custom_dir: ${dataset_dir}/manifest\n") + + def fake_load_template_defaults(config_arg_name, template_package): + if config_arg_name == "train_config": + return load_config_with_defaults(str(template_train), resolve=False) + if config_arg_name == "infer_config": + return load_config_with_defaults(str(template_infer), resolve=False) + raise AssertionError(config_arg_name) + + monkeypatch.setattr( + "espnet3.utils.config_utils.load_template_defaults", + fake_load_template_defaults, + ) + monkeypatch.setattr( + "espnet3.utils.config_utils._infer_template_package_from_config_path", + lambda _: "dummy.package", + ) + + cfg = load_and_merge_config( + inference, + "infer_config", + template_package="dummy.package", + ) + + assert cfg.exp_dir == "./exp/train_debug" + assert cfg.dataset_dir == "./data/mini_an4" + assert cfg.custom_dir == "./data/mini_an4/manifest" + + def test_ensure_target_convert_all_nested(): cfg = OmegaConf.create( { diff --git a/test/espnet3/utils/test_stages.py b/test/espnet3/utils/test_stages.py index b8f75420aa16..764790327722 100644 --- a/test/espnet3/utils/test_stages.py +++ b/test/espnet3/utils/test_stages.py @@ -1,3 +1,4 @@ +import argparse import logging import pytest @@ -31,7 +32,11 @@ def test_resolve_stages_subset_preserves_stage_order(): def test_run_stages_dry_run_skips_execution(caplog): system = DummySystem() with caplog.at_level(logging.INFO): - run_stages(system, ["stage_a", "stage_b"], dry_run=True) + run_stages( + system, + ["stage_a", "stage_b"], + args=argparse.Namespace(dry_run=True), + ) assert system.calls == [] assert "[DRY RUN] would run stage: stage_a" in caplog.text From 7e1a0a290c541d71a544e32495546086cd9ec750 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 12 Mar 2026 20:48:08 +0000 Subject: [PATCH 56/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- egs3/TEMPLATE/asr/run.py | 1 + .../asr/conf/training_asr_rnn_data_aug.yaml | 2 +- test/egs3/TEMPLATE/asr/test_run.py | 24 +++++++++---------- 3 files changed, 14 insertions(+), 13 deletions(-) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 5c86a2a73165..dcd1d14ab585 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -76,6 +76,7 @@ def build_parser( ) return parser + def main( args, system_cls, diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index a9db610023af..0f8837500052 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -71,7 +71,7 @@ trainer: max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - + strategy: auto diff --git a/test/egs3/TEMPLATE/asr/test_run.py b/test/egs3/TEMPLATE/asr/test_run.py index bd6f85059896..eea7f77bf529 100644 --- a/test/egs3/TEMPLATE/asr/test_run.py +++ b/test/egs3/TEMPLATE/asr/test_run.py @@ -4,8 +4,8 @@ from egs3.TEMPLATE.asr.run import _load_and_merge_config from espnet3.utils.config_utils import ( - load_template_defaults, _resolve_template_config_filename, + load_template_defaults, ) @@ -23,8 +23,7 @@ def test_resolve_template_config_filename_invalid() -> None: def test_load_template_defaults_train_contains_expected_targets() -> None: cfg = load_template_defaults("train_config", "egs3.TEMPLATE.asr") assert ( - cfg.dataset._target_ - == "espnet3.components.data.data_organizer.DataOrganizer" + cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" ) assert cfg.optimizer._target_ == "torch.optim.Adam" assert cfg.scheduler._target_ == "espnet2.schedulers.warmup_lr.WarmupLR" @@ -37,8 +36,7 @@ def test_load_template_defaults_infer_contains_expected_targets() -> None: == "espnet3.systems.base.inference_provider.InferenceProvider" ) assert ( - cfg.runner._target_ - == "espnet3.systems.base.inference_runner.InferenceRunner" + cfg.runner._target_ == "espnet3.systems.base.inference_runner.InferenceRunner" ) @@ -67,14 +65,16 @@ def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) assert cfg.optimizer.lr == 0.1 # template defaults should still be present assert ( - cfg.dataset._target_ - == "espnet3.components.data.data_organizer.DataOrganizer" + cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" ) def test_load_and_merge_config_none_path_returns_none() -> None: - assert _load_and_merge_config( - None, - "measure_config", - template_package="egs3.TEMPLATE.asr", - ) is None + assert ( + _load_and_merge_config( + None, + "measure_config", + template_package="egs3.TEMPLATE.asr", + ) + is None + ) From a2600acdfcd4c6feb83df6e1884cdd3848129e18 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 12 Mar 2026 17:19:31 -0400 Subject: [PATCH 57/67] Add comments on config, reflect review --- egs3/TEMPLATE/asr/conf/training.yaml | 80 ++++++------- egs3/TEMPLATE/asr/run.py | 2 +- egs3/mini_an4/asr/conf/inference.yaml | 12 ++ .../asr/conf/inference_transducer.yaml | 16 ++- egs3/mini_an4/asr/conf/metrics.yaml | 14 ++- egs3/mini_an4/asr/conf/training_asr_rnn.yaml | 112 ++++++++++++------ .../asr/conf/training_asr_rnn_data_aug.yaml | 107 +++++++++++------ .../asr/conf/training_asr_streaming.yaml | 105 ++++++++++------ .../asr/conf/training_asr_transducer.yaml | 102 ++++++++++------ .../asr/conf/training_asr_transformer.yaml | 93 ++++++++++----- egs3/mini_an4/asr/conf/training_lm_rnn.yaml | 96 ++++++++++----- ...raining_transducer_asr_conformer_rnnt.yaml | 92 +++++++++----- 12 files changed, 548 insertions(+), 283 deletions(-) diff --git a/egs3/TEMPLATE/asr/conf/training.yaml b/egs3/TEMPLATE/asr/conf/training.yaml index e7b89ce80b37..942acf067480 100644 --- a/egs3/TEMPLATE/asr/conf/training.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -82,14 +82,6 @@ dataset: # - an iterable of training strings tokenizer: -########################################################## -# PARALLELIZATION SETTING # -########################################################## -# Parallel backend used by collect_stats/train. -parallel: - env: local - n_workers: 1 - ########################################################## # MODEL SETTING # ########################################################## @@ -100,6 +92,46 @@ parallel: # If `task` is not set, this block is instantiated directly via Hydra. model: +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + _target_: torch.optim.Adam + lr: 0.002 + weight_decay: 0.000001 + +scheduler: + _target_: espnet2.schedulers.warmup_lr.WarmupLR + warmup_steps: 15000 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Checkpoint selection criteria passed to ESPnet3 callbacks. +# Each item is: +# - monitor key +# - number of best checkpoints to keep +# - direction (`min` or `max`) +best_model_criterion: + - - valid/loss + - 3 + - min + +# Optional random seed used by collect_stats/train. +seed: + +# Extra model initialization mode forwarded to ESPnet's initializer. +# Example: xavier_uniform +init: + +########################################################## +# PARALLELIZATION SETTING # +########################################################## +# Parallel backend used by collect_stats/train. +parallel: + env: local + n_workers: 1 + ########################################################## # DATALOADER SETTING # ########################################################## @@ -139,38 +171,6 @@ dataloader: batch_size: ${dataloader.train.iter_factory.batches.batch_size} batch_bins: ${dataloader.train.iter_factory.batches.batch_bins} -########################################################## -# OPTIMIZER & SCHEDULER SETTING # -########################################################## -optimizer: - _target_: torch.optim.Adam - lr: 0.002 - weight_decay: 0.000001 - -scheduler: - _target_: espnet2.schedulers.warmup_lr.WarmupLR - warmup_steps: 15000 - -########################################################## -# OTHER TRAINING SETTING # -########################################################## -# Checkpoint selection criteria passed to ESPnet3 callbacks. -# Each item is: -# - monitor key -# - number of best checkpoints to keep -# - direction (`min` or `max`) -best_model_criterion: - - - valid/loss - - 3 - - min - -# Optional random seed used by collect_stats/train. -seed: - -# Extra model initialization mode forwarded to ESPnet's initializer. -# Example: xavier_uniform -init: - ########################################################## # TRAINER SETTING # ########################################################## diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 5c86a2a73165..9fa69194ee16 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -151,7 +151,7 @@ def main( if __name__ == "__main__": parser = build_parser(stages=DEFAULT_STAGES) - args, stages_to_run = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) + args, _ = parse_cli_and_stage_args(parser, stages=DEFAULT_STAGES) # Here you should replace `YourSystemClass` with the actual system class # you want to use for your experiment. diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 012b55a1ff2a..aa1bf9a8346b 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -1,5 +1,14 @@ +########################################################## +# Inference SETTING # +########################################################## +# Quick usage: +# python run.py --stages infer --infer_config conf/inference.yaml +# # Mini AN4 ASR inference config for ESPnet3 integration tests. +########################################################## +# PATHS AND INPUTS # +########################################################## exp_dir: ${load_yaml:training.yaml,exp_dir} inference_dir: ${exp_dir}/inference dataset_dir: ${load_yaml:training.yaml,dataset_dir} @@ -11,6 +20,9 @@ dataset: _target_: src.dataset.MiniAN4Dataset manifest_path: ${dataset_dir}/manifest/test.tsv +########################################################## +# MODEL AND OUTPUT # +########################################################## model: _target_: espnet2.bin.asr_inference.Speech2Text asr_train_config: ${exp_dir}/config.yaml diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml index 04d65a45e935..e3dd24f48d49 100644 --- a/egs3/mini_an4/asr/conf/inference_transducer.yaml +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -1,4 +1,16 @@ +########################################################## +# Inference SETTING # +########################################################## +# Quick usage: +# python run.py --stages infer --infer_config conf/inference.yaml +# # Mini AN4 ASR inference config for ESPnet3 integration tests. +########################################################## +# PATHS AND INPUTS # +########################################################## +exp_dir: ${load_yaml:training.yaml,exp_dir} +inference_dir: ${exp_dir}/inference +dataset_dir: ${load_yaml:training.yaml,dataset_dir} dataset: test: @@ -7,7 +19,9 @@ dataset: _target_: src.dataset.MiniAN4Dataset manifest_path: ${dataset_dir}/manifest/test.tsv - +########################################################## +# MODEL AND OUTPUT # +########################################################## model: _target_: espnet2.bin.asr_transducer_inference.Speech2Text asr_train_config: ${exp_dir}/config.yaml diff --git a/egs3/mini_an4/asr/conf/metrics.yaml b/egs3/mini_an4/asr/conf/metrics.yaml index c6d0a5d35d4c..97148d7ccfe1 100644 --- a/egs3/mini_an4/asr/conf/metrics.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -1,8 +1,20 @@ -# Mini AN4 ASR scoring config for ESPnet3 integration tests. +########################################################## +# METRIC SCORING SETTING # +########################################################## +# Quick usage: +# python run.py --stages measure --measure_config conf/metrics.yaml +# +# Mini AN4 ASR metrics config for ESPnet3 integration tests. +########################################################## +# PATHS AND INPUTS # +########################################################## exp_dir: ${load_yaml:training.yaml,exp_dir} inference_dir: ${exp_dir}/inference +########################################################## +# METRIC DEFINITION # +########################################################## metrics: - metric: _target_: espnet3.systems.asr.metrics.wer.WER diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml index b5a17aedc41b..86feb9407570 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml @@ -1,16 +1,30 @@ -# This is a debug config for CI +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. # Mini AN4 ASR training config for ESPnet3 integration tests. +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_asr_rnn_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## +# Reuse the downloaded mini_an4 archive to create local manifests. create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Use the tiny train/dev split prepared for CI-sized ASR runs. dataset: train: - name: train_nodev @@ -26,7 +40,8 @@ dataset: _target_: espnet2.train.preprocessor.CommonPreprocessor fs: 16000 train: true - data_aug_effects: # no need to set the "sample_rate" argument for each effect here + # Keep the same augmentation pipeline as the data-aug reference config. + data_aug_effects: - [0.1, "contrast", {"enhancement_amount": 75.0}] - [0.1, "highpass", {"cutoff_freq": 5000, "Q": 0.707}] - [0.1, "equalization", {"center_freq": 1000, "gain": 0, "Q": 0.707}] @@ -40,42 +55,10 @@ dataset: token_list: ${tokenizer.save_path}/tokens.txt bpemodel: ${tokenizer.save_path}/bpe.model - -dataloader: - train: - multiple_iterator: false - num_shards: 1 - iter_factory: - batches: - type: sorted - batch_size: 2 - -optimizer: - _target_: torch.optim.AdamW - lr: 0.001 - weight_decay: 0.0 - -scheduler: - _target_: torch.optim.lr_scheduler.ReduceLROnPlateau - mode: min - factor: 0.5 - patience: 1 - -val_scheduler_criterion: valid/loss - -best_model_criterion: - - - valid/loss - - 1 - - min - -trainer: - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## +# Build a small BPE model from the training transcript text. tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -85,7 +68,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Small VGG-RNN encoder/decoder stack for a fast debug run. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -113,3 +99,51 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + _target_: torch.optim.AdamW + lr: 0.001 + weight_decay: 0.0 + +scheduler: + _target_: torch.optim.lr_scheduler.ReduceLROnPlateau + mode: min + factor: 0.5 + patience: 1 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# ReduceLROnPlateau tracks validation loss for LR updates. +val_scheduler_criterion: valid/loss + +best_model_criterion: + - - valid/loss + - 1 + - min + +########################################################## +# DATALOADER SETTING # +########################################################## +# Keep batches tiny so the config stays lightweight in CI. +dataloader: + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + batches: + type: sorted + batch_size: 2 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index a9db610023af..6330aabe6b2e 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -1,16 +1,32 @@ +########################################################## +# TRAINING SETTING # +########################################################## +# Quick usage: +# python run.py --stages create_dataset --train_config conf/training.yaml +# python run.py --stages train --train_config conf/training.yaml +# # This is a debug config for CI # Mini AN4 ASR training config for ESPnet3 integration tests. +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_asr_rnn_data_aug_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## dataset: train: - name: train_nodev @@ -40,41 +56,9 @@ dataset: token_list: ${tokenizer.save_path}/tokens.txt bpemodel: ${tokenizer.save_path}/bpe.model - -dataloader: - train: - iter_factory: - batches: - type: sorted - batch_size: 2 - -optimizer: - _target_: torch.optim.AdamW - lr: 0.001 - weight_decay: 0.0 - -override scheduler: - _target_: torch.optim.lr_scheduler.ReduceLROnPlateau - mode: min - factor: 0.5 - patience: 1 - -val_scheduler_criterion: valid/loss - -best_model_criterion: - - - valid/acc - - 1 - - max - -trainer: - log_every_n_steps: 1 - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -83,8 +67,10 @@ tokenizer: text_builder: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - - + +########################################################## +# MODEL SETTING # +########################################################## model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -112,3 +98,50 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + _target_: torch.optim.AdamW + lr: 0.001 + weight_decay: 0.0 + +override scheduler: + _target_: torch.optim.lr_scheduler.ReduceLROnPlateau + mode: min + factor: 0.5 + patience: 1 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +val_scheduler_criterion: valid/loss + +best_model_criterion: + - - valid/acc + - 1 + - max + +########################################################## +# DATALOADER SETTING # +########################################################## +dataloader: + train: + iter_factory: + batches: + type: sorted + batch_size: 2 + +########################################################## +# TRAINER SETTING # +########################################################## +# These settings map to `lightning.Trainer(...)`. +trainer: + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto + diff --git a/egs3/mini_an4/asr/conf/training_asr_streaming.yaml b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml index 378ee56de9ef..1f7fd31deaba 100644 --- a/egs3/mini_an4/asr/conf/training_asr_streaming.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_streaming.yaml @@ -1,20 +1,29 @@ -# This is a debug config for CI -# Mini AN4 ASR training config for ESPnet3 integration tests. - - -init: xavier_uniform - - +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. +# Mini AN4 streaming ASR training config for ESPnet3 integration tests. + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_asr_streaming_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Standard mini_an4 train/dev manifests plus BPE preprocessing. dataset: train: - name: train_nodev @@ -34,35 +43,9 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -dataloader: - train: - multiple_iterator: false - num_shards: 1 - iter_factory: - batches: - type: unsorted - batch_size: 2 - -optimizer: - lr: 0.005 - -scheduler: - warmup_steps: 100 - -best_model_criterion: - - - valid/loss - - 1 - - min - -trainer: - log_every_n_steps: 1 - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -72,7 +55,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Contextual block encoder keeps this config focused on streaming behavior. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -101,6 +87,7 @@ model: ctc_weight: 0.3 lsm_weight: 0.1 length_normalized_loss: false + # Streaming config disables feature extraction during stats collection. extract_feats_in_collect_stats: false frontend: default @@ -108,3 +95,47 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + lr: 0.005 + +scheduler: + warmup_steps: 100 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Use Xavier init because the model is transformer-based. +init: xavier_uniform + +best_model_criterion: + - - valid/loss + - 1 + - min + +########################################################## +# DATALOADER SETTING # +########################################################## +# Unsorted mini-batches keep the streaming example simple. +dataloader: + train: + multiple_iterator: false + num_shards: 1 + iter_factory: + batches: + type: unsorted + batch_size: 2 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_transducer.yaml b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml index 9014fa178199..10e379609c68 100644 --- a/egs3/mini_an4/asr/conf/training_asr_transducer.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transducer.yaml @@ -1,19 +1,29 @@ -# This is a debug config for CI -# Mini AN4 ASR training config for ESPnet3 integration tests. - -init: xavier_uniform - - +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. +# Mini AN4 transducer ASR training config for ESPnet3 integration tests. + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_asr_transducer_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Share the same tiny manifests across the ASR debug configs. dataset: train: - name: train_nodev @@ -33,33 +43,9 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -dataloader: - train: - iter_factory: - batches: - type: unsorted - batch_size: 2 - -optimizer: - lr: 0.005 - -scheduler: - warmup_steps: 100 - -best_model_criterion: - - - valid/loss - - 1 - - min - -trainer: - log_every_n_steps: 1 - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -69,7 +55,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Transformer encoder plus RNNT-style decoder/joint network. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -89,8 +78,8 @@ model: decoder: transducer decoder_conf: rnn_type: lstm - num_layers: 1 # Decoder Layers - hidden_size: 4 # Decoder dim + num_layers: 1 # Decoder layers in the prediction network. + hidden_size: 4 # Decoder hidden dimension. dropout: 0.1 dropout_embed: 0.2 @@ -111,3 +100,44 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + lr: 0.005 + +scheduler: + warmup_steps: 100 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Xavier init is the default debug choice for this transformer setup. +init: xavier_uniform + +best_model_criterion: + - - valid/loss + - 1 + - min + +########################################################## +# DATALOADER SETTING # +########################################################## +dataloader: + train: + iter_factory: + batches: + type: unsorted + batch_size: 2 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_asr_transformer.yaml b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml index 168e9bd6b1e9..2e41e9dbcd84 100644 --- a/egs3/mini_an4/asr/conf/training_asr_transformer.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_transformer.yaml @@ -1,16 +1,29 @@ -# This is a debug config for CI -init: xavier_uniform - +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. +# Mini AN4 transformer ASR training config for ESPnet3 integration tests. + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_asr_transformer_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Minimal train/dev split for transformer smoke tests. dataset: train: - name: train_nodev @@ -30,32 +43,9 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -dataloader: - train: - iter_factory: - batches: - type: unsorted - batch_size: 2 - -optimizer: - lr: 0.005 - -scheduler: - warmup_steps: 100 - -best_model_criterion: - - - valid/loss - - 10 - - min - -trainer: - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -65,7 +55,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Tiny transformer encoder/decoder pair to keep CI fast. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -106,3 +99,43 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + lr: 0.005 + +scheduler: + warmup_steps: 100 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Xavier init is used to stabilize this transformer baseline. +init: xavier_uniform + +best_model_criterion: + - - valid/loss + - 10 + - min + +########################################################## +# DATALOADER SETTING # +########################################################## +dataloader: + train: + iter_factory: + batches: + type: unsorted + batch_size: 2 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_lm_rnn.yaml b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml index 6634cef11bcd..573337f5107f 100644 --- a/egs3/mini_an4/asr/conf/training_lm_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_lm_rnn.yaml @@ -1,16 +1,29 @@ -# This is a debug config for CI -init: xavier_uniform - +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. +# Mini AN4 LM-RNN training config for ESPnet3 integration tests. + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## task: espnet3.systems.asr.task.ASRTask exp_tag: train_lm_rnn_debug dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Reuse the ASR manifests and tokenize the transcript text for LM training. dataset: train: - name: train_nodev @@ -30,33 +43,9 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -dataloader: - train: - iter_factory: - batches: - type: sorted - batch_size: 32 - -optimizer: - lr: 0.005 - -scheduler: - warmup_steps: 30000 - -best_model_criterion: - - - valid/acc - - 10 - - max - -trainer: - log_every_n_steps: 1 - max_epochs: 100 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -66,7 +55,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Tiny recurrent LM for debug-only language-model coverage. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -89,3 +81,45 @@ model: n_fft: 512 win_length: 400 hop_length: 160 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + lr: 0.005 + +scheduler: + warmup_steps: 30000 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +# Xavier init is kept to match the other debug baselines. +init: xavier_uniform + +best_model_criterion: + - - valid/acc + - 10 + - max + +########################################################## +# DATALOADER SETTING # +########################################################## +# Larger batches are fine here because the LM input is text-only. +dataloader: + train: + iter_factory: + batches: + type: sorted + batch_size: 32 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + log_every_n_steps: 1 + max_epochs: 100 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto diff --git a/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml index 208f8b34bb3a..d35027a259c2 100644 --- a/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml +++ b/egs3/mini_an4/asr/conf/training_transducer_asr_conformer_rnnt.yaml @@ -1,5 +1,12 @@ -# This is a debug config for CI - +########################################################## +# TRAINING SETTING # +########################################################## +# This is a debug config for CI. +# Mini AN4 conformer-RNNT training config for ESPnet3 integration tests. + +########################################################## +# SYSTEM AND PATH SETTING # +########################################################## num_device: 1 num_nodes: 1 task: espnet3.systems.asr.transducer_task.ASRTransducerTask @@ -12,11 +19,18 @@ stats_dir: ${recipe_dir}/exp/stats inference_dir: ${exp_dir}/inference dataset_dir: ${data_dir}/mini_an4 +########################################################## +# DATASET CREATION SETTING # +########################################################## create_dataset: func: src.creating_dataset.create_dataset dataset_dir: ${dataset_dir} archive_path: ${recipe_dir}/../../egs2/mini_an4/asr1/downloads.tar.gz +########################################################## +# DATASET DEFINITION # +########################################################## +# Use the same manifest layout as the other mini_an4 debug configs. dataset: train: - name: train_nodev @@ -36,33 +50,9 @@ dataset: bpemodel: ${tokenizer.save_path}/bpe.model text_cleaner: -dataloader: - train: - iter_factory: - batches: - type: sorted - batch_size: 32 - -optimizer: - lr: 0.005 - -scheduler: - warmup_steps: 30000 - -best_model_criterion: - - - valid/loss - - 10 - - min - -trainer: - log_every_n_steps: 1 - max_epochs: 1 - limit_train_batches: 1 - limit_val_batches: 1 - - strategy: auto - - +########################################################## +# TOKENIZER SETTING # +########################################################## tokenizer: vocab_size: 30 character_coverage: 1.0 @@ -72,7 +62,10 @@ tokenizer: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - +########################################################## +# MODEL SETTING # +########################################################## +# Compact conformer encoder and RNNT decoder for task-specific coverage. model: vocab_size: ${tokenizer.vocab_size} token_list: ${tokenizer.save_path}/tokens.txt @@ -92,3 +85,42 @@ model: joint_network_conf: joint_space_size: 4 + +########################################################## +# OPTIMIZER & SCHEDULER SETTING # +########################################################## +optimizer: + lr: 0.005 + +scheduler: + warmup_steps: 30000 + +########################################################## +# OTHER TRAINING SETTING # +########################################################## +best_model_criterion: + - - valid/loss + - 10 + - min + +########################################################## +# DATALOADER SETTING # +########################################################## +# Sorted batches reduce padding for the transducer example. +dataloader: + train: + iter_factory: + batches: + type: sorted + batch_size: 32 + +########################################################## +# TRAINER SETTING # +########################################################## +trainer: + log_every_n_steps: 1 + max_epochs: 1 + limit_train_batches: 1 + limit_val_batches: 1 + + strategy: auto From 8e2c24542a9bb1bdeedf15f9897aeb7a0006f443 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Thu, 12 Mar 2026 17:19:44 -0400 Subject: [PATCH 58/67] Bug fixed --- espnet3/systems/base/inference.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/espnet3/systems/base/inference.py b/espnet3/systems/base/inference.py index f05e3a140204..600ede0fca55 100644 --- a/espnet3/systems/base/inference.py +++ b/espnet3/systems/base/inference.py @@ -150,7 +150,13 @@ def infer(config: DictConfig): raise TypeError( f"{type(runner).__name__} must provide inference runner attributes" ) - dataset_length = len(provider.build_dataset(config)) + dataset = provider.build_dataset(config) + dataset_length = len(dataset) + if dataset_length == 0: + raise RuntimeError( + f"Test dataset '{test_name}' is empty. " + "Please check the dataset manifest and preprocessing outputs." + ) logger.info("===> Processing %d samples..", dataset_length) out = runner(list(range(dataset_length))) if out is None: From a9c220eb47736fb0aadf462c20308a4d6288e843 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 12 Mar 2026 21:22:34 +0000 Subject: [PATCH 59/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index 6330aabe6b2e..9cf7782ad57c 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -67,7 +67,7 @@ tokenizer: text_builder: func: src.tokenizer.gather_training_text manifest_path: ${dataset_dir}/manifest/train_nodev.tsv - + ########################################################## # MODEL SETTING # ########################################################## @@ -142,6 +142,5 @@ trainer: max_epochs: 1 limit_train_batches: 1 limit_val_batches: 1 - - strategy: auto + strategy: auto From 4a97bf01ba120cfb38be26a50065a03a4d64b825 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 04:45:39 -0400 Subject: [PATCH 60/67] Fixed readme --- egs3/TEMPLATE/asr/readme.md | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md index 42b4ee41b1e2..355d117955d2 100644 --- a/egs3/TEMPLATE/asr/readme.md +++ b/egs3/TEMPLATE/asr/readme.md @@ -1,8 +1,4 @@ -# LibriSpeech 100h ESPnet3 recipe - -This recipe follows the [lightning-hydra-template]( -https://github.com/ashleve/lightning-hydra-template -) layout and uses the latest `espnet3` package utilities. +# ESPnet3 ASR recipe ## Quick start From 6a0e12350aca53b5ddff5fa33046a9089ed23ea1 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 04:48:15 -0400 Subject: [PATCH 61/67] train_config -> training_config, infer_config -> inference_config, measure_config -> metrics_config --- egs3/TEMPLATE/asr/conf/inference.yaml | 2 +- egs3/TEMPLATE/asr/conf/metrics.yaml | 2 +- egs3/TEMPLATE/asr/conf/training.yaml | 4 +- egs3/TEMPLATE/asr/readme.md | 8 +- egs3/TEMPLATE/asr/run.py | 36 +++---- egs3/mini_an4/asr/conf/inference.yaml | 4 +- .../asr/conf/inference_transducer.yaml | 4 +- egs3/mini_an4/asr/conf/metrics.yaml | 2 +- .../asr/conf/training_asr_rnn_data_aug.yaml | 4 +- espnet3/components/data/data_organizer.py | 2 +- espnet3/systems/asr/system.py | 46 ++++---- espnet3/systems/base/inference.py | 12 +-- espnet3/systems/base/inference_provider.py | 8 +- espnet3/systems/base/metric.py | 30 +++--- espnet3/systems/base/system.py | 100 +++++++++--------- espnet3/utils/config_utils.py | 12 +-- espnet3/utils/logging_utils.py | 46 ++++---- espnet3/utils/stages_utils.py | 8 +- logs/stage_a.log | 7 ++ logs/stage_a1.log | 5 + test/egs3/TEMPLATE/asr/test_run.py | 14 +-- .../espnet3/systems/asr/test_asr_inference.py | 2 +- test/espnet3/systems/asr/test_system.py | 6 +- test/espnet3/systems/base/test_base_system.py | 6 +- test/espnet3/systems/base/test_inference.py | 8 +- test/espnet3/systems/base/test_metric.py | 2 +- test/espnet3/utils/test_config.py | 16 +-- 27 files changed, 204 insertions(+), 192 deletions(-) create mode 100644 logs/stage_a.log create mode 100644 logs/stage_a1.log diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index ee56f10443aa..aa0f72f0d016 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -2,7 +2,7 @@ # Inference SETTING # ########################################################## # Quick usage: -# python run.py --stages infer --infer_config conf/inference.yaml +# python run.py --stages infer --inference_config conf/inference.yaml # # Outputs: # - `${inference_dir}//*.scp` diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 4bebf4a7061a..9f45f0c2ab6a 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -2,7 +2,7 @@ # METRIC SCORING SETTING # ########################################################## # Quick usage: -# python run.py --stages measure --measure_config conf/metrics.yaml +# python run.py --stages measure --metrics_config conf/metrics.yaml # # Assumptions: # - `conf/inference.yaml` has already produced `/*.scp` files. diff --git a/egs3/TEMPLATE/asr/conf/training.yaml b/egs3/TEMPLATE/asr/conf/training.yaml index 942acf067480..58df01d71b12 100644 --- a/egs3/TEMPLATE/asr/conf/training.yaml +++ b/egs3/TEMPLATE/asr/conf/training.yaml @@ -2,8 +2,8 @@ # TRAINING SETTING # ########################################################## # Quick usage: -# python run.py --stages create_dataset --train_config conf/training.yaml -# python run.py --stages train --train_config conf/training.yaml +# python run.py --stages create_dataset --training_config conf/training.yaml +# python run.py --stages train --training_config conf/training.yaml # # Main stages and what this config is used for: # - `create_dataset`: uses `create_dataset` diff --git a/egs3/TEMPLATE/asr/readme.md b/egs3/TEMPLATE/asr/readme.md index 355d117955d2..95c9732cc405 100644 --- a/egs3/TEMPLATE/asr/readme.md +++ b/egs3/TEMPLATE/asr/readme.md @@ -6,14 +6,14 @@ # 0) Edit configs to set paths (e.g., conf/training.yaml: dataset_dir, create_dataset.func) # 1) Convert LibriSpeech to Hugging Face format (run once) -python run.py --stages create_dataset --train_config conf/training.yaml +python run.py --stages create_dataset --training_config conf/training.yaml # 2) Train with the default Branchformer configuration -python run.py --stages train --train_config conf/training.yaml +python run.py --stages train --training_config conf/training.yaml # 3) Decode -python run.py --stages infer --infer_config conf/inference.yaml +python run.py --stages infer --inference_config conf/inference.yaml # 4) Score -python run.py --stages measure --measure_config conf/metrics.yaml +python run.py --stages measure --metrics_config conf/metrics.yaml ``` diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 94a10ff9b806..599e78602752 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -44,7 +44,7 @@ def build_parser( help="Which stages to run. Multiple values allowed.", ) parser.add_argument( - "--train_config", + "--training_config", default=None, type=Path, help=( @@ -53,13 +53,13 @@ def build_parser( ), ) parser.add_argument( - "--infer_config", + "--inference_config", default=None, type=Path, help="Hydra config for infer stage.", ) parser.add_argument( - "--measure_config", + "--metrics_config", default=None, type=Path, help="Hydra config for measure stage.", @@ -87,19 +87,19 @@ def main( # ----------------------------------------- # Load configs # ----------------------------------------- - train_config = load_and_merge_config( - args.train_config, - "train_config", + training_config = load_and_merge_config( + args.training_config, + "training_config", template_package=__package__, ) - infer_config = load_and_merge_config( - args.infer_config, - "infer_config", + inference_config = load_and_merge_config( + args.inference_config, + "inference_config", template_package=__package__, ) - measure_config = load_and_merge_config( - args.measure_config, - "measure_config", + metrics_config = load_and_merge_config( + args.metrics_config, + "metrics_config", template_package=__package__, ) @@ -109,9 +109,9 @@ def main( # Instantiate system # ----------------------------------------- system = system_cls( - train_config=train_config, - infer_config=infer_config, - measure_config=measure_config, + training_config=training_config, + inference_config=inference_config, + metrics_config=metrics_config, ) # ----------------------------------------- @@ -129,8 +129,8 @@ def main( "train", } required_configs = {} - required_configs.update({stage: train_config for stage in pretrain_stages}) - required_configs.update({"infer": infer_config, "measure": measure_config}) + required_configs.update({stage: training_config for stage in pretrain_stages}) + required_configs.update({"infer": inference_config, "measure": metrics_config}) missing = [ s for s in stages_to_run @@ -140,7 +140,7 @@ def main( missing_str = ", ".join(missing) raise ValueError( f"Config not provided for stage(s): {missing_str}. " - "Use --train_config/--infer_config/--measure_config." + "Use --training_config/--inference_config/--metrics_config." ) run_stages( system=system, diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index aa1bf9a8346b..2621049a9303 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -2,7 +2,7 @@ # Inference SETTING # ########################################################## # Quick usage: -# python run.py --stages infer --infer_config conf/inference.yaml +# python run.py --stages infer --inference_config conf/inference.yaml # # Mini AN4 ASR inference config for ESPnet3 integration tests. @@ -25,7 +25,7 @@ dataset: ########################################################## model: _target_: espnet2.bin.asr_inference.Speech2Text - asr_train_config: ${exp_dir}/config.yaml + asr_training_config: ${exp_dir}/config.yaml asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 ctc_weight: 0.3 diff --git a/egs3/mini_an4/asr/conf/inference_transducer.yaml b/egs3/mini_an4/asr/conf/inference_transducer.yaml index e3dd24f48d49..61a2a9afb486 100644 --- a/egs3/mini_an4/asr/conf/inference_transducer.yaml +++ b/egs3/mini_an4/asr/conf/inference_transducer.yaml @@ -2,7 +2,7 @@ # Inference SETTING # ########################################################## # Quick usage: -# python run.py --stages infer --infer_config conf/inference.yaml +# python run.py --stages infer --inference_config conf/inference.yaml # # Mini AN4 ASR inference config for ESPnet3 integration tests. ########################################################## @@ -24,7 +24,7 @@ dataset: ########################################################## model: _target_: espnet2.bin.asr_transducer_inference.Speech2Text - asr_train_config: ${exp_dir}/config.yaml + asr_training_config: ${exp_dir}/config.yaml asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 diff --git a/egs3/mini_an4/asr/conf/metrics.yaml b/egs3/mini_an4/asr/conf/metrics.yaml index 97148d7ccfe1..328894f260d9 100644 --- a/egs3/mini_an4/asr/conf/metrics.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -2,7 +2,7 @@ # METRIC SCORING SETTING # ########################################################## # Quick usage: -# python run.py --stages measure --measure_config conf/metrics.yaml +# python run.py --stages measure --metrics_config conf/metrics.yaml # # Mini AN4 ASR metrics config for ESPnet3 integration tests. diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml index 9cf7782ad57c..f15df91a87b7 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn_data_aug.yaml @@ -2,8 +2,8 @@ # TRAINING SETTING # ########################################################## # Quick usage: -# python run.py --stages create_dataset --train_config conf/training.yaml -# python run.py --stages train --train_config conf/training.yaml +# python run.py --stages create_dataset --training_config conf/training.yaml +# python run.py --stages train --training_config conf/training.yaml # # This is a debug config for CI # Mini AN4 ASR training config for ESPnet3 integration tests. diff --git a/espnet3/components/data/data_organizer.py b/espnet3/components/data/data_organizer.py index 344c43802b0a..7f1550103aa2 100644 --- a/espnet3/components/data/data_organizer.py +++ b/espnet3/components/data/data_organizer.py @@ -143,7 +143,7 @@ class DataOrganizer: Example (training + validation): >>> organizer = DataOrganizer( - ... train=train_configs, + ... train=training_configs, ... valid=valid_configs, ... preprocessor=MyPreprocessor() ... ) diff --git a/espnet3/systems/asr/system.py b/espnet3/systems/asr/system.py index bf0ce98fb82d..d3215376ba12 100644 --- a/espnet3/systems/asr/system.py +++ b/espnet3/systems/asr/system.py @@ -44,23 +44,23 @@ class ASRSystem(BaseSystem): Additional stage log paths: | Stage | Path reference | |--- |--- | - | train_tokenizer | train_config.tokenizer.save_path | + | train_tokenizer | training_config.tokenizer.save_path | """ def __init__( self, - train_config=None, - infer_config=None, - measure_config=None, + training_config=None, + inference_config=None, + metrics_config=None, **kwargs, ) -> None: """Initialize the ASR system with ASR-specific stage mappings.""" super().__init__( - train_config=train_config, - infer_config=infer_config, - measure_config=measure_config, + training_config=training_config, + inference_config=inference_config, + metrics_config=metrics_config, stage_log_mapping={ - "train_tokenizer": "train_config.tokenizer.save_path", + "train_tokenizer": "training_config.tokenizer.save_path", }, **kwargs, ) @@ -68,7 +68,7 @@ def __init__( def create_dataset(self, *args, **kwargs): """Create datasets using the configured helper function. - The callable is resolved from ``train_config.create_dataset.func`` and + The callable is resolved from ``training_config.create_dataset.func`` and invoked with the remaining configuration values. Raises: @@ -77,10 +77,10 @@ def create_dataset(self, *args, **kwargs): self._reject_stage_args("create_dataset", args, kwargs) logger.info("ASRSystem.create_dataset(): starting dataset creation process") start = time.perf_counter() - config = getattr(self.train_config, "create_dataset", None) + config = getattr(self.training_config, "create_dataset", None) if config is None or not getattr(config, "func", None): raise RuntimeError( - "train_config.create_dataset.func must be set to run create_dataset" + "training_config.create_dataset.func must be set to run create_dataset" ) fn = load_function(config.func) extra = {k: v for k, v in config.items() if k != "func"} @@ -100,14 +100,14 @@ def train(self, *args, **kwargs): training before delegating to the base training routine. Raises: - RuntimeError: If ``train_config.dataset_dir`` is not set. + RuntimeError: If ``training_config.dataset_dir`` is not set. """ self._reject_stage_args("train", args, kwargs) logger.info("ASRSystem.train(): starting training process") - dataset_dir = getattr(self.train_config, "dataset_dir", None) + dataset_dir = getattr(self.training_config, "dataset_dir", None) if dataset_dir is None: - raise RuntimeError("train_config.dataset_dir must be set for training.") + raise RuntimeError("training_config.dataset_dir must be set for training.") # Train tokenizer if not trained previously if not self._has_tokenizer(): @@ -117,7 +117,7 @@ def train(self, *args, **kwargs): return super().train() def _has_tokenizer(self) -> bool: - tokenizer_config = self.train_config.tokenizer + tokenizer_config = self.training_config.tokenizer output_path = Path(tokenizer_config.save_path) model = output_path / f"{tokenizer_config.model_type}.model" vocab = output_path / f"{tokenizer_config.model_type}.vocab" @@ -126,7 +126,7 @@ def _has_tokenizer(self) -> bool: def train_tokenizer(self, *args, **kwargs): """Train a SentencePiece tokenizer based on configured text. - The text builder configured in ``train_config.tokenizer.text_builder`` + The text builder configured in ``training_config.tokenizer.text_builder`` is used to generate training text, which is then saved and consumed by the SentencePiece trainer. @@ -139,7 +139,7 @@ def train_tokenizer(self, *args, **kwargs): logger.info("Tokenizer already exists. Skipping train_tokenizer().") return start = time.perf_counter() - tokenizer_config = getattr(self.train_config, "tokenizer", None) + tokenizer_config = getattr(self.training_config, "tokenizer", None) builder_config = ( getattr(tokenizer_config, "text_builder", None) if tokenizer_config @@ -147,7 +147,7 @@ def train_tokenizer(self, *args, **kwargs): ) if builder_config is None or not getattr(builder_config, "func", None): raise RuntimeError( - "train_config.tokenizer.text_builder.func must be set to build " + "training_config.tokenizer.text_builder.func must be set to build " "tokenizer text." ) builder = load_function(builder_config.func) @@ -172,7 +172,7 @@ def train_tokenizer(self, *args, **kwargs): raise RuntimeError( "Tokenizer text_builder returned no text. Check dataset preparation." ) - output_path = Path(self.train_config.tokenizer.save_path) + output_path = Path(self.training_config.tokenizer.save_path) output_path.mkdir(parents=True, exist_ok=True) train_text_path = getattr(tokenizer_config, "train_file", None) if train_text_path: @@ -188,15 +188,15 @@ def train_tokenizer(self, *args, **kwargs): with open(train_text_path, "w", encoding="utf-8") as f: f.write("\n".join(texts)) - logger.info(f"Training tokenizer: {self.train_config.tokenizer.model_type}") - logger.info(f"Tokenizer output: {self.train_config.tokenizer.save_path}") + logger.info(f"Training tokenizer: {self.training_config.tokenizer.model_type}") + logger.info(f"Tokenizer output: {self.training_config.tokenizer.save_path}") # Example placeholder: train_sentencepiece( train_text_path, output_path, - self.train_config.tokenizer.vocab_size, - model_type=self.train_config.tokenizer.model_type, + self.training_config.tokenizer.vocab_size, + model_type=self.training_config.tokenizer.model_type, ) logger.info( "Tokenizer training completed in %.2fs", time.perf_counter() - start diff --git a/espnet3/systems/base/inference.py b/espnet3/systems/base/inference.py index 600ede0fca55..6f98fb2a23df 100644 --- a/espnet3/systems/base/inference.py +++ b/espnet3/systems/base/inference.py @@ -95,10 +95,10 @@ def infer(config: DictConfig): input_key = getattr(config, "input_key", None) if input_key is None: - raise RuntimeError("infer_config.input_key must be set.") + raise RuntimeError("inference_config.input_key must be set.") if isinstance(input_key, (list, tuple)) and not input_key: - raise RuntimeError("infer_config.input_key must not be empty.") + raise RuntimeError("inference_config.input_key must not be empty.") output_keys = getattr(config, "output_keys", None) if output_keys is not None: @@ -107,14 +107,14 @@ def infer(config: DictConfig): elif not isinstance(output_keys, (list, tuple)): output_keys = list(output_keys) if not output_keys: - raise RuntimeError("infer_config.output_keys must not be empty.") + raise RuntimeError("inference_config.output_keys must not be empty.") idx_key = getattr(config, "idx_key", "utt_id") batch_size = getattr(config, "batch_size", None) provider_config = getattr(config, "provider", None) if provider_config is None: - raise RuntimeError("infer_config.provider must be set.") + raise RuntimeError("inference_config.provider must be set.") raw_params = getattr(provider_config, "params", {}) or {} if OmegaConf.is_config(raw_params): provider_params = OmegaConf.to_container(raw_params, resolve=True) @@ -127,7 +127,7 @@ def infer(config: DictConfig): provider = instantiate( provider_config, - infer_config=config, + inference_config=config, params=provider_params, _recursive_=False, ) @@ -135,7 +135,7 @@ def infer(config: DictConfig): hyp_keys = output_keys if output_keys is not None else [] runner_config = getattr(config, "runner", None) if runner_config is None: - raise RuntimeError("infer_config.runner must be set.") + raise RuntimeError("inference_config.runner must be set.") runner_kwargs = { "provider": provider, diff --git a/espnet3/systems/base/inference_provider.py b/espnet3/systems/base/inference_provider.py index 3834e51b6c03..5a45776de29e 100644 --- a/espnet3/systems/base/inference_provider.py +++ b/espnet3/systems/base/inference_provider.py @@ -30,14 +30,14 @@ class InferenceProvider(EnvironmentProvider, ABC): pickle-safe for Dask. Args: - infer_config (DictConfig): Hydra configuration used to build dataset/model. + inference_config (DictConfig): Hydra configuration used to build dataset/model. params (Dict[str, Any] | None): Optional additional key-value pairs that will be merged into the returned environment (e.g., device, tokenizer, beam size). Notes: - Subclasses must implement ``build_dataset`` and ``build_model``. - - ``self.infer_config.update(self.params)`` allows lightweight overrides + - ``self.inference_config.update(self.params)`` allows lightweight overrides (e.g., runtime overrides) but avoid mutating deep structures unless intended. """ @@ -45,10 +45,10 @@ class InferenceProvider(EnvironmentProvider, ABC): # TODO(Masao) Add detailed description on Runner/Provider in the document. def __init__( - self, infer_config: DictConfig = None, params: Dict[str, Any] | None = None + self, inference_config: DictConfig = None, params: Dict[str, Any] | None = None ): """Initialize InferenceProvider object.""" - super().__init__(infer_config) + super().__init__(inference_config) self.params = params or {} self.config.update(self.params) diff --git a/espnet3/systems/base/metric.py b/espnet3/systems/base/metric.py index 7ac5acbfe528..b91b4528f556 100644 --- a/espnet3/systems/base/metric.py +++ b/espnet3/systems/base/metric.py @@ -14,16 +14,16 @@ logger = logging.getLogger(__name__) -def _resolve_test_sets(measure_config: DictConfig) -> list[str]: +def _resolve_test_sets(metrics_config: DictConfig) -> list[str]: """Resolve metric target test sets from config or inference outputs. This helper decides which test-set names should be scored by the measurement stage. Resolution order: - 1. If ``measure_config.dataset.test`` is defined, use its ``name`` + 1. If ``metrics_config.dataset.test`` is defined, use its ``name`` fields as-is. - 2. Otherwise, scan ``measure_config.inference_dir`` and treat every + 2. Otherwise, scan ``metrics_config.inference_dir`` and treat every subdirectory as a test set. For example, if ``inference_dir`` contains: @@ -37,7 +37,7 @@ def _resolve_test_sets(measure_config: DictConfig) -> list[str]: then this function returns ``["test-clean", "test-other"]``. Args: - measure_config: Measurement config containing either + metrics_config: Measurement config containing either ``dataset.test`` entries or an ``inference_dir`` path. Returns: @@ -47,12 +47,12 @@ def _resolve_test_sets(measure_config: DictConfig) -> list[str]: ValueError: If neither ``dataset.test`` nor any subdirectories under ``inference_dir`` are available. """ - dataset = getattr(measure_config, "dataset", None) + dataset = getattr(metrics_config, "dataset", None) test_config = getattr(dataset, "test", None) if dataset is not None else None if test_config: return [t.name for t in test_config] - inference_dir = Path(measure_config.inference_dir) + inference_dir = Path(metrics_config.inference_dir) test_sets = sorted( entry.name for entry in inference_dir.iterdir() @@ -60,7 +60,7 @@ def _resolve_test_sets(measure_config: DictConfig) -> list[str]: ) if not test_sets: raise ValueError( - "No test sets found. Specify `measure_config.dataset.test` or place " + "No test sets found. Specify `metrics_config.dataset.test` or place " f"test-set subdirectories under inference_dir: {inference_dir}" ) logger.info( @@ -70,20 +70,20 @@ def _resolve_test_sets(measure_config: DictConfig) -> list[str]: return test_sets -def measure(measure_config: DictConfig): +def measure(metrics_config: DictConfig): """Compute metrics for each test set and write a metrics JSON file. Args: - measure_config: Omegaconf configuration with inference and metric settings. + metrics_config: Omegaconf configuration with inference and metric settings. Returns: Nested dict keyed by metric class path and test set name. """ - test_sets = _resolve_test_sets(measure_config) + test_sets = _resolve_test_sets(metrics_config) results = {} - assert hasattr(measure_config, "metrics"), "Please specify `metrics`!" + assert hasattr(metrics_config, "metrics"), "Please specify `metrics`!" - for idx, metric_config in enumerate(measure_config.metrics): + for idx, metric_config in enumerate(metrics_config.metrics): metric = instantiate(metric_config.metric) if not isinstance(metric, AbsMetric): raise TypeError(f"{type(metric)} is not a valid AbsMetric instance") @@ -108,15 +108,15 @@ def measure(measure_config: DictConfig): ) inputs = [ref_key, hyp_key] data = load_scp_fields( - inference_dir=Path(measure_config.inference_dir), + inference_dir=Path(metrics_config.inference_dir), test_name=test_name, inputs=inputs, file_suffix=".scp", ) - metric_result = metric(data, test_name, measure_config.inference_dir) + metric_result = metric(data, test_name, metrics_config.inference_dir) results[get_class_path(metric)].update({test_name: metric_result}) - out_path = Path(measure_config.inference_dir) / "metrics.json" + out_path = Path(metrics_config.inference_dir) / "metrics.json" with open(out_path, "w", encoding="utf-8") as f: json.dump(results, f, indent=2, ensure_ascii=False) diff --git a/espnet3/systems/base/system.py b/espnet3/systems/base/system.py index 18f4ffc1a046..5ca0e73bee1c 100644 --- a/espnet3/systems/base/system.py +++ b/espnet3/systems/base/system.py @@ -30,39 +30,39 @@ class BaseSystem: All behavior is config-driven. Args: - train_config (DictConfig | None): Training configuration. - infer_config (DictConfig | None): Inference configuration. - measure_config (DictConfig | None): Measurement configuration. + training_config (DictConfig | None): Training configuration. + inference_config (DictConfig | None): Inference configuration. + metrics_config (DictConfig | None): Measurement configuration. stage_log_mapping (dict | None): Optional overrides for stage log path resolution. Keys are stage names; values are dotted attribute - paths (e.g., ``"train_config.exp_dir"``) or lists/tuples of such + paths (e.g., ``"training_config.exp_dir"``) or lists/tuples of such paths (first non-empty value wins). Stage log mapping (base defaults): | Stage | Path reference | |--- |--- | - | create_dataset | train_config.recipe_dir | - | collect_stats | train_config.stats_dir | - | train | train_config.exp_dir | - | infer | infer_config.inference_dir | - | measure | measure_config.inference_dir | - | pack_model | train_config.exp_dir | - | upload_model | train_config.exp_dir | + | create_dataset | training_config.recipe_dir | + | collect_stats | training_config.stats_dir | + | train | training_config.exp_dir | + | infer | inference_config.inference_dir | + | measure | metrics_config.inference_dir | + | pack_model | training_config.exp_dir | + | upload_model | training_config.exp_dir | Any stage missing from the mapping (or resolving to ``None``) falls back - to the default log directory: ``train_config.exp_dir`` when available, + to the default log directory: ``training_config.exp_dir`` when available, otherwise ``/logs``. Examples: Override a subset of stage log paths: ```python system = BaseSystem( - train_config=train_cfg, - infer_config=infer_cfg, - measure_config=measure_cfg, + training_config=train_cfg, + inference_config=infer_cfg, + metrics_config=measure_cfg, stage_log_mapping={ - "infer": "train_config.exp_dir", - "measure": "train_config.exp_dir", + "infer": "training_config.exp_dir", + "measure": "training_config.exp_dir", }, ) ``` @@ -70,18 +70,18 @@ class BaseSystem: def __init__( self, - train_config: DictConfig | None = None, - infer_config: DictConfig | None = None, - measure_config: DictConfig | None = None, + training_config: DictConfig | None = None, + inference_config: DictConfig | None = None, + metrics_config: DictConfig | None = None, stage_log_mapping: dict | None = None, ) -> None: """Initialize the system with optional stage configs.""" - self.train_config = train_config - self.infer_config = infer_config - self.measure_config = measure_config + self.training_config = training_config + self.inference_config = inference_config + self.metrics_config = metrics_config - if train_config is not None: - self.exp_dir = Path(train_config.exp_dir) + if training_config is not None: + self.exp_dir = Path(training_config.exp_dir) self.exp_dir.mkdir(parents=True, exist_ok=True) else: self.exp_dir = None @@ -92,13 +92,13 @@ def __init__( default_dir = Path.cwd() / "logs" base_mapping = { - "create_dataset": "train_config.recipe_dir", - "collect_stats": "train_config.stats_dir", - "train": "train_config.exp_dir", - "infer": "infer_config.inference_dir", - "measure": "measure_config.inference_dir", - "pack_model": "train_config.exp_dir", - "upload_model": "train_config.exp_dir", + "create_dataset": "training_config.recipe_dir", + "collect_stats": "training_config.stats_dir", + "train": "training_config.exp_dir", + "infer": "inference_config.inference_dir", + "measure": "metrics_config.inference_dir", + "pack_model": "training_config.exp_dir", + "upload_model": "training_config.exp_dir", } mapping = dict(base_mapping) if stage_log_mapping: @@ -112,12 +112,12 @@ def __init__( self.stage_log_dirs[stage] = Path(resolved) logger.info( - "Initialized %s with train_config=%s infer_config=%s " - "measure_config=%s exp_dir=%s", + "Initialized %s with training_config=%s inference_config=%s " + "metrics_config=%s exp_dir=%s", self.__class__.__name__, - train_config is not None, - infer_config is not None, - measure_config is not None, + training_config is not None, + inference_config is not None, + metrics_config is not None, self.exp_dir, ) @@ -126,7 +126,7 @@ def _resolve_stage_log_ref( ) -> str | None: """Resolve stage log mapping references to concrete values. - Supports dotted attribute paths like ``train_config.exp_dir`` and + Supports dotted attribute paths like ``training_config.exp_dir`` and fallbacks via list/tuple entries (first non-empty value wins). """ target = self @@ -170,43 +170,43 @@ def collect_stats(self, *args, **kwargs): self._reject_stage_args("collect_stats", args, kwargs) logger.info( "Collecting stats | exp_dir=%s stats_dir=%s", - getattr(self.train_config, "exp_dir", None), - getattr(self.train_config, "stats_dir", None), + getattr(self.training_config, "exp_dir", None), + getattr(self.training_config, "stats_dir", None), ) - return collect_stats(self.train_config) + return collect_stats(self.training_config) def train(self, *args, **kwargs): """Train the system model.""" self._reject_stage_args("train", args, kwargs) model_target = None - if self.train_config is not None and hasattr(self.train_config, "model"): - model_config = self.train_config.model + if self.training_config is not None and hasattr(self.training_config, "model"): + model_config = self.training_config.model if isinstance(model_config, DictConfig): model_target = model_config.get("_target_") logger.info( "Training start | exp_dir=%s model=%s", - getattr(self.train_config, "exp_dir", None), + getattr(self.training_config, "exp_dir", None), model_target or "", ) - return train(self.train_config) + return train(self.training_config) def infer(self, *args, **kwargs): """Run inference on the configured datasets.""" self._reject_stage_args("infer", args, kwargs) logger.info( "Inference start | inference_dir=%s", - getattr(self.infer_config, "inference_dir", None), + getattr(self.inference_config, "inference_dir", None), ) - return infer(self.infer_config) + return infer(self.inference_config) def measure(self, *args, **kwargs): """Compute evaluation metrics from hypothesis/reference outputs.""" self._reject_stage_args("measure", args, kwargs) logger.info( - "Metrics start | measure_config=%s", - self.measure_config is not None, + "Metrics start | metrics_config=%s", + self.metrics_config is not None, ) - result = measure(self.measure_config) + result = measure(self.metrics_config) logger.info("results: %s", result) return result diff --git a/espnet3/utils/config_utils.py b/espnet3/utils/config_utils.py index 678d365f71ab..7b183fc73ab3 100644 --- a/espnet3/utils/config_utils.py +++ b/espnet3/utils/config_utils.py @@ -304,22 +304,22 @@ def _build_config_path(base_path: Path, entry: str) -> Path: def _resolve_template_config_filename(config_arg_name: str) -> str: - if config_arg_name == "train_config": + if config_arg_name == "training_config": return "training.yaml" - if config_arg_name == "infer_config": + if config_arg_name == "inference_config": return "inference.yaml" - if config_arg_name == "measure_config": + if config_arg_name == "metrics_config": return "metrics.yaml" raise ValueError(f"Unknown config argument name: {config_arg_name}") def _resolve_template_config_arg_name(filename: str) -> str | None: if filename == "training.yaml": - return "train_config" + return "training_config" if filename == "inference.yaml": - return "infer_config" + return "inference_config" if filename == "metrics.yaml": - return "measure_config" + return "metrics_config" return None diff --git a/espnet3/utils/logging_utils.py b/espnet3/utils/logging_utils.py index 979b75568a33..56d134dfe612 100644 --- a/espnet3/utils/logging_utils.py +++ b/espnet3/utils/logging_utils.py @@ -71,10 +71,10 @@ def log_stage_metadata( entries. In practice this is the stage logger configured immediately before a stage starts. system (Any): Instantiated system object. When present, the attributes - ``train_config``, ``infer_config``, and ``measure_config`` are read + ``training_config``, ``inference_config``, and ``metrics_config`` are read and dumped as resolved YAML for reproducibility. args (argparse.Namespace | None): Parsed CLI namespace. The function - reads ``train_config``, ``infer_config``, ``measure_config``, and + reads ``training_config``, ``inference_config``, ``metrics_config``, and ``write_requirements`` from this namespace when available. Returns: @@ -83,42 +83,42 @@ def log_stage_metadata( Examples: >>> from argparse import Namespace >>> class DummySystem: - ... train_config = {"exp_dir": "./exp/train"} - ... infer_config = None - ... measure_config = None + ... training_config = {"exp_dir": "./exp/train"} + ... inference_config = None + ... metrics_config = None >>> log_stage_metadata( ... logging.getLogger("espnet3"), ... system=DummySystem(), ... args=Namespace( - ... train_config="conf/training.yaml", - ... infer_config=None, - ... measure_config=None, + ... training_config="conf/training.yaml", + ... inference_config=None, + ... metrics_config=None, ... write_requirements=False, ... ), ... ) """ - train_config = getattr(system, "train_config", None) - infer_config = getattr(system, "infer_config", None) - measure_config = getattr(system, "measure_config", None) + training_config = getattr(system, "training_config", None) + inference_config = getattr(system, "inference_config", None) + metrics_config = getattr(system, "metrics_config", None) log_run_metadata( logger, argv=sys.argv, configs={ "Training": ( - Path(args.train_config) - if args is not None and getattr(args, "train_config", None) + Path(args.training_config) + if args is not None and getattr(args, "training_config", None) else None ), "Inference": ( - Path(args.infer_config) - if args is not None and getattr(args, "infer_config", None) + Path(args.inference_config) + if args is not None and getattr(args, "inference_config", None) else None ), "Metrics": ( - Path(args.measure_config) - if args is not None and getattr(args, "measure_config", None) + Path(args.metrics_config) + if args is not None and getattr(args, "metrics_config", None) else None ), }, @@ -127,20 +127,20 @@ def log_stage_metadata( ), ) log_env_metadata(logger) - if train_config is not None: + if training_config is not None: logger.info( "Training config content:\n%s", - OmegaConf.to_yaml(train_config, resolve=True), + OmegaConf.to_yaml(training_config, resolve=True), ) - if infer_config is not None: + if inference_config is not None: logger.info( "Inference config content:\n%s", - OmegaConf.to_yaml(infer_config, resolve=True), + OmegaConf.to_yaml(inference_config, resolve=True), ) - if measure_config is not None: + if metrics_config is not None: logger.info( "Metrics config content:\n%s", - OmegaConf.to_yaml(measure_config, resolve=True), + OmegaConf.to_yaml(metrics_config, resolve=True), ) diff --git a/espnet3/utils/stages_utils.py b/espnet3/utils/stages_utils.py index 41329e9f3a2d..acf4716e2aae 100644 --- a/espnet3/utils/stages_utils.py +++ b/espnet3/utils/stages_utils.py @@ -45,11 +45,11 @@ def _get_process_rank() -> int: def _get_stage_log_mode(system: Any) -> str: - """Return normalized stage_log_mode from train_config, defaulting to rank0.""" + """Return normalized stage_log_mode from training_config, defaulting to rank0.""" mode = "rank0" - train_config = getattr(system, "train_config", None) - if train_config is not None: - mode = getattr(train_config, "stage_log_mode", mode) + training_config = getattr(system, "training_config", None) + if training_config is not None: + mode = getattr(training_config, "stage_log_mode", mode) return str(mode).lower() diff --git a/logs/stage_a.log b/logs/stage_a.log new file mode 100644 index 000000000000..2bcc517d7e53 --- /dev/null +++ b/logs/stage_a.log @@ -0,0 +1,7 @@ +[MSI] 2026-03-12 16:47:21 EDT (stages_utils.py:193) ERROR: [stage_a] Stage 'stage_a' failed after 0.00s +Traceback (most recent call last): + File "/mnt/c/Users/might/Documents/git/espnets/espnet3/espnet3/utils/stages_utils.py", line 184, in run_stages + fn() + File "/mnt/c/Users/might/Documents/git/espnets/espnet3/test/espnet3/utils/test_stages.py", line 68, in stage_a + raise ValueError("boom") +ValueError: boom diff --git a/logs/stage_a1.log b/logs/stage_a1.log new file mode 100644 index 000000000000..e271a9983156 --- /dev/null +++ b/logs/stage_a1.log @@ -0,0 +1,5 @@ +[MSI] 2026-03-12 16:47:09 EDT (stages_utils.py:186) ERROR: [stage_a] Stage 'stage_a' failed (bad arguments) +Traceback (most recent call last): + File "/mnt/c/Users/might/Documents/git/espnets/espnet3/espnet3/utils/stages_utils.py", line 184, in run_stages + fn() +TypeError: test_run_stages_typeerror_wrapped..BadSystem.stage_a() missing 1 required positional argument: 'arg' diff --git a/test/egs3/TEMPLATE/asr/test_run.py b/test/egs3/TEMPLATE/asr/test_run.py index eea7f77bf529..1c666ca5ca7a 100644 --- a/test/egs3/TEMPLATE/asr/test_run.py +++ b/test/egs3/TEMPLATE/asr/test_run.py @@ -10,9 +10,9 @@ def test_resolve_template_config_filename() -> None: - assert _resolve_template_config_filename("train_config") == "training.yaml" - assert _resolve_template_config_filename("infer_config") == "inference.yaml" - assert _resolve_template_config_filename("measure_config") == "metrics.yaml" + assert _resolve_template_config_filename("training_config") == "training.yaml" + assert _resolve_template_config_filename("inference_config") == "inference.yaml" + assert _resolve_template_config_filename("metrics_config") == "metrics.yaml" def test_resolve_template_config_filename_invalid() -> None: @@ -21,7 +21,7 @@ def test_resolve_template_config_filename_invalid() -> None: def test_load_template_defaults_train_contains_expected_targets() -> None: - cfg = load_template_defaults("train_config", "egs3.TEMPLATE.asr") + cfg = load_template_defaults("training_config", "egs3.TEMPLATE.asr") assert ( cfg.dataset._target_ == "espnet3.components.data.data_organizer.DataOrganizer" ) @@ -30,7 +30,7 @@ def test_load_template_defaults_train_contains_expected_targets() -> None: def test_load_template_defaults_infer_contains_expected_targets() -> None: - cfg = load_template_defaults("infer_config", "egs3.TEMPLATE.asr") + cfg = load_template_defaults("inference_config", "egs3.TEMPLATE.asr") assert ( cfg.provider._target_ == "espnet3.systems.base.inference_provider.InferenceProvider" @@ -55,7 +55,7 @@ def test_load_and_merge_config_user_overrides_template_defaults(tmp_path: Path) cfg = _load_and_merge_config( user, - "train_config", + "training_config", template_package="egs3.TEMPLATE.asr", ) @@ -73,7 +73,7 @@ def test_load_and_merge_config_none_path_returns_none() -> None: assert ( _load_and_merge_config( None, - "measure_config", + "metrics_config", template_package="egs3.TEMPLATE.asr", ) is None diff --git a/test/espnet3/systems/asr/test_asr_inference.py b/test/espnet3/systems/asr/test_asr_inference.py index fda0360d6fc3..fea68014da8c 100644 --- a/test/espnet3/systems/asr/test_asr_inference.py +++ b/test/espnet3/systems/asr/test_asr_inference.py @@ -222,7 +222,7 @@ def test_inference_requires_provider_config(): "parallel": {"env": "local", "n_workers": 1}, } ) - with pytest.raises(RuntimeError, match="infer_config.provider must be set"): + with pytest.raises(RuntimeError, match="inference_config.provider must be set"): infer(cfg) diff --git a/test/espnet3/systems/asr/test_system.py b/test/espnet3/systems/asr/test_system.py index 9c09b401b070..9a76270349b0 100644 --- a/test/espnet3/systems/asr/test_system.py +++ b/test/espnet3/systems/asr/test_system.py @@ -17,7 +17,7 @@ def test_asr_system_create_dataset_invokes_helper(tmp_path, monkeypatch): "create_dataset": {"func": "dummy.dataset", "foo": "bar"}, } ) - system = ASRSystem(train_config=train_cfg) + system = ASRSystem(training_config=train_cfg) calls = {} def fake_fn(**kwargs): @@ -42,7 +42,7 @@ def test_asr_system_train_runs_tokenizer_then_train(tmp_path, monkeypatch): }, } ) - system = ASRSystem(train_config=train_cfg) + system = ASRSystem(training_config=train_cfg) calls = {} def fake_train_tokenizer(self): @@ -73,7 +73,7 @@ def test_asr_system_train_tokenizer_trains_sentencepiece(tmp_path, monkeypatch): }, } ) - system = ASRSystem(train_config=train_cfg) + system = ASRSystem(training_config=train_cfg) calls = {} def fake_builder(foo): diff --git a/test/espnet3/systems/base/test_base_system.py b/test/espnet3/systems/base/test_base_system.py index 24b9103d8697..910f1b75f78c 100644 --- a/test/espnet3/systems/base/test_base_system.py +++ b/test/espnet3/systems/base/test_base_system.py @@ -40,9 +40,9 @@ def fake_metric(cfg): monkeypatch.setattr(sysmod, "measure", fake_metric) system = BaseSystem( - train_config=train_cfg, - infer_config=infer_cfg, - measure_config=measure_cfg, + training_config=train_cfg, + inference_config=infer_cfg, + metrics_config=measure_cfg, ) assert system.exp_dir.is_dir() diff --git a/test/espnet3/systems/base/test_inference.py b/test/espnet3/systems/base/test_inference.py index c5892217bd3f..f2fd2029ad75 100644 --- a/test/espnet3/systems/base/test_inference.py +++ b/test/espnet3/systems/base/test_inference.py @@ -13,8 +13,8 @@ def dummy_output_fn(*, data, model_output, idx): class DummyProvider(InferenceProvider): - def __init__(self, infer_config, params): - super().__init__(infer_config) + def __init__(self, inference_config, params): + super().__init__(inference_config) self.params = params def build_dataset(self, _config): @@ -42,8 +42,8 @@ def __call__(self, indices): class CaptureProvider(InferenceRunner): last_params = None - def __init__(self, infer_config, *, params): - super().__init__(infer_config) + def __init__(self, inference_config, *, params): + super().__init__(inference_config) CaptureProvider.last_params = params def build_dataset(self, _config): diff --git a/test/espnet3/systems/base/test_metric.py b/test/espnet3/systems/base/test_metric.py index 8a79a714d4b3..0c1d3c3f4da0 100644 --- a/test/espnet3/systems/base/test_metric.py +++ b/test/espnet3/systems/base/test_metric.py @@ -106,7 +106,7 @@ def test_metric_discovers_test_sets_from_inference_dir(tmp_path): assert results[expected_key]["test_b"] == {"count": 1} -def test_resolve_test_sets_prefers_measure_config_dataset_over_inference_dir(tmp_path): +def test_resolve_test_sets_prefers_metrics_config_dataset_over_inference_dir(tmp_path): inference_dir = tmp_path / "infer" for test_name in ("from_dir_a", "from_dir_b"): (inference_dir / test_name).mkdir(parents=True) diff --git a/test/espnet3/utils/test_config.py b/test/espnet3/utils/test_config.py index 79eb1b60a5f0..b89fba7e8fa3 100644 --- a/test/espnet3/utils/test_config.py +++ b/test/espnet3/utils/test_config.py @@ -370,13 +370,13 @@ def test_load_yaml_training_config_merges_template_before_select( def test_load_template_defaults_train(): - cfg = load_template_defaults("train_config", "egs3.TEMPLATE.asr") + cfg = load_template_defaults("training_config", "egs3.TEMPLATE.asr") assert "dataset" in cfg assert "exp_dir" in cfg def test_load_and_merge_config_none(): - assert load_and_merge_config(None, "measure_config") is None + assert load_and_merge_config(None, "metrics_config") is None def test_load_and_merge_config_resolves_user_reference_to_template_value( @@ -401,7 +401,7 @@ def test_load_and_merge_config_resolves_user_reference_to_template_value( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "train_config", template_package="dummy.package") + cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") assert cfg.exp_dir == "./exp/from_template" assert cfg.inference_dir == "./exp/from_template/inference" @@ -430,13 +430,13 @@ def test_load_and_merge_config_resolves_template_reference_to_user_override( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "train_config", template_package="dummy.package") + cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") assert cfg.exp_dir == "./exp/from_user" assert cfg.custom_dir == "./exp/from_user/custom" -def test_load_and_merge_infer_config_can_read_training_yaml_with_template_values( +def test_load_and_merge_inference_config_can_read_training_yaml_with_template_values( write_yaml, monkeypatch ): template_infer = write_yaml( @@ -464,9 +464,9 @@ def test_load_and_merge_infer_config_can_read_training_yaml_with_template_values inference = write_yaml("inference.yaml", "custom_dir: ${dataset_dir}/manifest\n") def fake_load_template_defaults(config_arg_name, template_package): - if config_arg_name == "train_config": + if config_arg_name == "training_config": return load_config_with_defaults(str(template_train), resolve=False) - if config_arg_name == "infer_config": + if config_arg_name == "inference_config": return load_config_with_defaults(str(template_infer), resolve=False) raise AssertionError(config_arg_name) @@ -481,7 +481,7 @@ def fake_load_template_defaults(config_arg_name, template_package): cfg = load_and_merge_config( inference, - "infer_config", + "inference_config", template_package="dummy.package", ) From f3419d4b396e14199272b245cb63dd4627fb2eda Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 05:15:47 -0400 Subject: [PATCH 62/67] Moved recipe-specific code to run.py --- egs3/TEMPLATE/asr/run.py | 10 +++++--- espnet3/utils/config_utils.py | 47 ++++++----------------------------- 2 files changed, 14 insertions(+), 43 deletions(-) diff --git a/egs3/TEMPLATE/asr/run.py b/egs3/TEMPLATE/asr/run.py index 599e78602752..f707dd6eb593 100644 --- a/egs3/TEMPLATE/asr/run.py +++ b/egs3/TEMPLATE/asr/run.py @@ -26,7 +26,6 @@ "measure", ] -# Type alias for a System class logger = logging.getLogger(__name__) @@ -87,19 +86,22 @@ def main( # ----------------------------------------- # Load configs # ----------------------------------------- + # Keep template_package explicit so the recipe declares which TEMPLATE + # package provides the default configs, instead of relying on path-based + # inference from the user-supplied config location. training_config = load_and_merge_config( args.training_config, - "training_config", + template_config_path="conf/training.yaml", template_package=__package__, ) inference_config = load_and_merge_config( args.inference_config, - "inference_config", + template_config_path="conf/inference.yaml", template_package=__package__, ) metrics_config = load_and_merge_config( args.metrics_config, - "metrics_config", + template_config_path="conf/metrics.yaml", template_package=__package__, ) diff --git a/espnet3/utils/config_utils.py b/espnet3/utils/config_utils.py index 7b183fc73ab3..41a1f0d69182 100644 --- a/espnet3/utils/config_utils.py +++ b/espnet3/utils/config_utils.py @@ -53,7 +53,7 @@ def load_yaml(path, key=None): """ cfg_path = Path(path) try: - cfg = _load_yaml_for_resolver(cfg_path) + cfg = OmegaConf.load(cfg_path) except FileNotFoundError: logging.error(f"File not found: {path}") raise @@ -70,19 +70,6 @@ def load_yaml(path, key=None): return value -def _load_yaml_for_resolver(path: Path): - config_arg_name = _resolve_template_config_arg_name(path.name) - if config_arg_name is not None: - template_package = _infer_template_package_from_config_path(path) - if template_package is not None: - return load_and_merge_config( - path, - config_arg_name, - template_package=template_package, - ) - return OmegaConf.load(path) - - OMEGACONF_ESPNET3_RESOLVER = { "load_line": load_line, "load_yaml": load_yaml, @@ -191,17 +178,19 @@ def load_config_with_defaults(path: str, resolve: bool = True) -> OmegaConf: return final_config -def load_template_defaults(config_arg_name: str, template_package: str): +def load_template_defaults( + template_config_path: str, + template_package: str, +): """Load packaged TEMPLATE defaults by config kind.""" - filename = _resolve_template_config_filename(config_arg_name) - resource = resources.files(template_package).joinpath("conf", filename) + resource = resources.files(template_package).joinpath(*Path(template_config_path).parts) with resources.as_file(resource) as path: return load_config_with_defaults(str(path), resolve=False) def load_and_merge_config( config_path: Path | None, - config_arg_name: str, + template_config_path: str, template_package: str | None = None, ): """Load user config and merge it with TEMPLATE defaults.""" @@ -213,7 +202,7 @@ def load_and_merge_config( raise ValueError( "template_package is required when it cannot be inferred from config_path" ) - default_cfg = load_template_defaults(config_arg_name, template_package) + default_cfg = load_template_defaults(template_config_path, template_package) user_cfg = load_config_with_defaults(str(config_path), resolve=False) merged_cfg = OmegaConf.merge(default_cfg, user_cfg) OmegaConf.resolve(merged_cfg) @@ -303,26 +292,6 @@ def _build_config_path(base_path: Path, entry: str) -> Path: return base_path / entry -def _resolve_template_config_filename(config_arg_name: str) -> str: - if config_arg_name == "training_config": - return "training.yaml" - if config_arg_name == "inference_config": - return "inference.yaml" - if config_arg_name == "metrics_config": - return "metrics.yaml" - raise ValueError(f"Unknown config argument name: {config_arg_name}") - - -def _resolve_template_config_arg_name(filename: str) -> str | None: - if filename == "training.yaml": - return "training_config" - if filename == "inference.yaml": - return "inference_config" - if filename == "metrics.yaml": - return "metrics_config" - return None - - def _infer_template_package_from_config_path(config_path: Path) -> str | None: parts = config_path.resolve().parts try: From e8fb69a9f6467ad0b62b85cd713f8f081d494147 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 05:36:08 -0400 Subject: [PATCH 63/67] Fixed CI bug --- .github/workflows/ci_on_ubuntu.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/ci_on_ubuntu.yml b/.github/workflows/ci_on_ubuntu.yml index 2e6f7e63a1fe..c91541f84c46 100644 --- a/.github/workflows/ci_on_ubuntu.yml +++ b/.github/workflows/ci_on_ubuntu.yml @@ -281,7 +281,7 @@ jobs: test_integration_espnet3: runs-on: ubuntu-latest - needs: setup_environment + needs: process_labels if: | github.event.pull_request.draft == false strategy: From 9bd60782afb9c3f321317254cdb8a12bac0ad0a5 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 05:37:09 -0400 Subject: [PATCH 64/67] Fixed CI bug in integration test --- ci/test_integration_espnet3.sh | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index be73c57ee983..1fc5645e972e 100755 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -19,17 +19,17 @@ cd ./egs3/mini_an4/asr gen_dummy_coverage echo "==== [ESPnet3] ASR ====" source ./path.sh -run_with_train_config() { - local train_config=$1 +run_with_training_config() { + local training_config=$1 local runner=$2 - local infer_config=$3 + local inference_config=$3 - ln -sfn "${train_config}" conf/training.yaml + ln -sfn "${training_config}" conf/training.yaml ${python} "${runner}" \ --stages create_dataset train_tokenizer collect_stats train infer measure \ - --train_config conf/training.yaml \ - --infer_config "${infer_config}" \ - --measure_config conf/measure.yaml + --training_config conf/training.yaml \ + --inference_config "${inference_config}" \ + --metrics_config conf/measure.yaml rm -rf exp data } @@ -41,12 +41,12 @@ debug_configs=( training_asr_transducer.yaml ) -for train_config in "${debug_configs[@]}"; do - run_with_train_config "${train_config}" run.py conf/inference.yaml +for training_config in "${debug_configs[@]}"; do + run_with_training_config "${training_config}" run.py conf/inference.yaml done # We need seprate inference config for transducer task -run_with_train_config \ +run_with_training_config \ training_transducer_asr_conformer_rnnt.yaml \ run.py \ conf/inference_transducer.yaml From dc2af8b6dcd30007de372dbfd21550d868a8d184 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 13 Mar 2026 09:41:39 +0000 Subject: [PATCH 65/67] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- espnet3/utils/config_utils.py | 4 +++- test/espnet3/utils/test_config.py | 8 ++++++-- 2 files changed, 9 insertions(+), 3 deletions(-) diff --git a/espnet3/utils/config_utils.py b/espnet3/utils/config_utils.py index 41a1f0d69182..3f789c9526fa 100644 --- a/espnet3/utils/config_utils.py +++ b/espnet3/utils/config_utils.py @@ -183,7 +183,9 @@ def load_template_defaults( template_package: str, ): """Load packaged TEMPLATE defaults by config kind.""" - resource = resources.files(template_package).joinpath(*Path(template_config_path).parts) + resource = resources.files(template_package).joinpath( + *Path(template_config_path).parts + ) with resources.as_file(resource) as path: return load_config_with_defaults(str(path), resolve=False) diff --git a/test/espnet3/utils/test_config.py b/test/espnet3/utils/test_config.py index b89fba7e8fa3..98097f815a1c 100644 --- a/test/espnet3/utils/test_config.py +++ b/test/espnet3/utils/test_config.py @@ -401,7 +401,9 @@ def test_load_and_merge_config_resolves_user_reference_to_template_value( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") + cfg = load_and_merge_config( + user, "training_config", template_package="dummy.package" + ) assert cfg.exp_dir == "./exp/from_template" assert cfg.inference_dir == "./exp/from_template/inference" @@ -430,7 +432,9 @@ def test_load_and_merge_config_resolves_template_reference_to_user_override( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") + cfg = load_and_merge_config( + user, "training_config", template_package="dummy.package" + ) assert cfg.exp_dir == "./exp/from_user" assert cfg.custom_dir == "./exp/from_user/custom" From 0f5813542bc482ba334bf132dd334e8390315e5b Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 06:37:14 -0400 Subject: [PATCH 66/67] Fixed CI issue --- .github/workflows/ci_on_ubuntu.yml | 24 +++---- ci/test_integration_espnet3.sh | 2 +- egs3/TEMPLATE/asr/conf/inference.yaml | 7 +- egs3/TEMPLATE/asr/conf/metrics.yaml | 4 +- egs3/mini_an4/asr/conf/inference.yaml | 6 +- egs3/mini_an4/asr/conf/metrics.yaml | 2 +- test/espnet3/utils/test_config.py | 97 +++------------------------ 7 files changed, 34 insertions(+), 108 deletions(-) diff --git a/.github/workflows/ci_on_ubuntu.yml b/.github/workflows/ci_on_ubuntu.yml index c91541f84c46..b60e61871d68 100644 --- a/.github/workflows/ci_on_ubuntu.yml +++ b/.github/workflows/ci_on_ubuntu.yml @@ -300,29 +300,25 @@ jobs: with: path: ~/.cache/pip key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ matrix.pytorch-version }}-${{ hashFiles('**/pyproject.toml') }}-${{ hashFiles('**/Makefile') }} - - uses: actions/cache@v5 + - name: Make environment + uses: ./.github/actions/prepare-environment with: - path: tools - key: ${{ runner.os }}-tools-${{ github.run_id }}-${{ matrix.python-version }}-${{ matrix.pytorch-version }}-${{ hashFiles('**/pyproject.toml') }}-${{ hashFiles('**/Makefile') }} - - name: Install System Dependencies - uses: ./.github/actions/install-system-dependencies - - name: test espnet3 integration - run: ./ci/test_integration_espnet3.sh ${{ matrix.config-task }} + os-version: ubuntu + python-version: ${{ matrix.python-version }} + pytorch-version: ${{ matrix.pytorch-version }} + chainer-version: ${{ matrix.chainer-version }} + use-conda: ${{ matrix.use-conda }} + - name: test python + run: ./ci/test_integration_espnet3.sh - uses: codecov/codecov-action@v5 with: - flags: test_python_espnet3 + flags: test_integration_espnet3 - name: coverage erase continue-on-error: true run: | source tools/activate_python.sh coverage erase - - name: test espnet3 integration - run: ./ci/test_integration_espnet3.sh - - uses: codecov/codecov-action@v5 - with: - flags: test_integration_espnet3 - test_import: runs-on: ubuntu-latest needs: process_labels diff --git a/ci/test_integration_espnet3.sh b/ci/test_integration_espnet3.sh index 1fc5645e972e..bba7fc3e52b7 100755 --- a/ci/test_integration_espnet3.sh +++ b/ci/test_integration_espnet3.sh @@ -29,7 +29,7 @@ run_with_training_config() { --stages create_dataset train_tokenizer collect_stats train infer measure \ --training_config conf/training.yaml \ --inference_config "${inference_config}" \ - --metrics_config conf/measure.yaml + --metrics_config conf/metrics.yaml rm -rf exp data } diff --git a/egs3/TEMPLATE/asr/conf/inference.yaml b/egs3/TEMPLATE/asr/conf/inference.yaml index aa0f72f0d016..a7dfe10b96ba 100644 --- a/egs3/TEMPLATE/asr/conf/inference.yaml +++ b/egs3/TEMPLATE/asr/conf/inference.yaml @@ -11,9 +11,12 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:training.yaml,exp_dir} +recipe_dir: . +exp_tag: +exp_dir: ${recipe_dir}/exp/${exp_tag} +data_dir: ${recipe_dir}/data inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:training.yaml,dataset_dir} + # Test split definitions are required for inference. # `dataset.test[*].name` becomes the output subdirectory name under diff --git a/egs3/TEMPLATE/asr/conf/metrics.yaml b/egs3/TEMPLATE/asr/conf/metrics.yaml index 9f45f0c2ab6a..8cd057412b82 100644 --- a/egs3/TEMPLATE/asr/conf/metrics.yaml +++ b/egs3/TEMPLATE/asr/conf/metrics.yaml @@ -13,7 +13,9 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:training.yaml,exp_dir} +recipe_dir: . +exp_tag: +exp_dir: ${recipe_dir}/exp/${exp_tag} inference_dir: ${exp_dir}/inference diff --git a/egs3/mini_an4/asr/conf/inference.yaml b/egs3/mini_an4/asr/conf/inference.yaml index 2621049a9303..96e0f31f927a 100644 --- a/egs3/mini_an4/asr/conf/inference.yaml +++ b/egs3/mini_an4/asr/conf/inference.yaml @@ -9,9 +9,9 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:training.yaml,exp_dir} +exp_tag: ${load_yaml:training.yaml,exp_tag} inference_dir: ${exp_dir}/inference -dataset_dir: ${load_yaml:training.yaml,dataset_dir} +dataset_dir: ${data_dir}/mini_an4 dataset: test: @@ -25,7 +25,7 @@ dataset: ########################################################## model: _target_: espnet2.bin.asr_inference.Speech2Text - asr_training_config: ${exp_dir}/config.yaml + asr_train_config: ${exp_dir}/config.yaml asr_model_file: ${exp_dir}/last.ckpt beam_size: 1 ctc_weight: 0.3 diff --git a/egs3/mini_an4/asr/conf/metrics.yaml b/egs3/mini_an4/asr/conf/metrics.yaml index 328894f260d9..6ef8f210590f 100644 --- a/egs3/mini_an4/asr/conf/metrics.yaml +++ b/egs3/mini_an4/asr/conf/metrics.yaml @@ -9,7 +9,7 @@ ########################################################## # PATHS AND INPUTS # ########################################################## -exp_dir: ${load_yaml:training.yaml,exp_dir} +exp_tag: ${load_yaml:training.yaml,exp_tag} inference_dir: ${exp_dir}/inference ########################################################## diff --git a/test/espnet3/utils/test_config.py b/test/espnet3/utils/test_config.py index b89fba7e8fa3..45f1f70fed92 100644 --- a/test/espnet3/utils/test_config.py +++ b/test/espnet3/utils/test_config.py @@ -340,43 +340,14 @@ def test_load_yaml_missing_key_raises(write_yaml): load_yaml(str(path), "missing.key") -def test_load_yaml_training_config_merges_template_before_select( - write_yaml, monkeypatch -): - template = write_yaml( - "template.yaml", - """ -data_dir: ./data -dataset_dir: ${data_dir}/default -""", - ) - training = write_yaml( - "training.yaml", - """ -dataset_dir: ${data_dir}/mini_an4 -""", - ) - - monkeypatch.setattr( - "espnet3.utils.config_utils.load_template_defaults", - lambda _, __: load_config_with_defaults(str(template), resolve=False), - ) - monkeypatch.setattr( - "espnet3.utils.config_utils._infer_template_package_from_config_path", - lambda _: "dummy.package", - ) - - assert load_yaml(str(training), "dataset_dir") == "./data/mini_an4" - - def test_load_template_defaults_train(): - cfg = load_template_defaults("training_config", "egs3.TEMPLATE.asr") + cfg = load_template_defaults("conf/training.yaml", "egs3.TEMPLATE.asr") assert "dataset" in cfg assert "exp_dir" in cfg def test_load_and_merge_config_none(): - assert load_and_merge_config(None, "metrics_config") is None + assert load_and_merge_config(None, "conf/metrics.yaml") is None def test_load_and_merge_config_resolves_user_reference_to_template_value( @@ -401,7 +372,11 @@ def test_load_and_merge_config_resolves_user_reference_to_template_value( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") + cfg = load_and_merge_config( + user, + "conf/training.yaml", + template_package="dummy.package", + ) assert cfg.exp_dir == "./exp/from_template" assert cfg.inference_dir == "./exp/from_template/inference" @@ -430,64 +405,14 @@ def test_load_and_merge_config_resolves_template_reference_to_user_override( lambda _, __: load_config_with_defaults(str(template), resolve=False), ) - cfg = load_and_merge_config(user, "training_config", template_package="dummy.package") - - assert cfg.exp_dir == "./exp/from_user" - assert cfg.custom_dir == "./exp/from_user/custom" - - -def test_load_and_merge_inference_config_can_read_training_yaml_with_template_values( - write_yaml, monkeypatch -): - template_infer = write_yaml( - "template_inference.yaml", - """ -exp_dir: ${load_yaml:training.yaml,exp_dir} -dataset_dir: ${load_yaml:training.yaml,dataset_dir} -""", - ) - template_train = write_yaml( - "template_training.yaml", - """ -data_dir: ./data -exp_dir: ./exp/default -dataset_dir: ${data_dir}/default -""", - ) - write_yaml( - "training.yaml", - """ -exp_dir: ./exp/train_debug -dataset_dir: ${data_dir}/mini_an4 -""", - ) - inference = write_yaml("inference.yaml", "custom_dir: ${dataset_dir}/manifest\n") - - def fake_load_template_defaults(config_arg_name, template_package): - if config_arg_name == "training_config": - return load_config_with_defaults(str(template_train), resolve=False) - if config_arg_name == "inference_config": - return load_config_with_defaults(str(template_infer), resolve=False) - raise AssertionError(config_arg_name) - - monkeypatch.setattr( - "espnet3.utils.config_utils.load_template_defaults", - fake_load_template_defaults, - ) - monkeypatch.setattr( - "espnet3.utils.config_utils._infer_template_package_from_config_path", - lambda _: "dummy.package", - ) - cfg = load_and_merge_config( - inference, - "inference_config", + user, + "conf/training.yaml", template_package="dummy.package", ) - assert cfg.exp_dir == "./exp/train_debug" - assert cfg.dataset_dir == "./data/mini_an4" - assert cfg.custom_dir == "./data/mini_an4/manifest" + assert cfg.exp_dir == "./exp/from_user" + assert cfg.custom_dir == "./exp/from_user/custom" def test_ensure_target_convert_all_nested(): From aff537e0a48a158cd3b14eb6fdc2225115b86756 Mon Sep 17 00:00:00 2001 From: Masao-Someki Date: Fri, 13 Mar 2026 07:31:58 -0400 Subject: [PATCH 67/67] Fixed CI issue --- egs3/mini_an4/asr/conf/training_asr_rnn.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml index 86feb9407570..9f6de38ec692 100644 --- a/egs3/mini_an4/asr/conf/training_asr_rnn.yaml +++ b/egs3/mini_an4/asr/conf/training_asr_rnn.yaml @@ -108,7 +108,7 @@ optimizer: lr: 0.001 weight_decay: 0.0 -scheduler: +override scheduler: _target_: torch.optim.lr_scheduler.ReduceLROnPlateau mode: min factor: 0.5