[CLI] Clean up and improvements to diffusers CLI - #14381
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Modular pipelines: - `custom_blocks` also writes `modular_model_index.json`, so a packaged repo is loadable by `ModularPipeline.from_pretrained` (and runnable by `run`), not just importable as blocks. - Add `--cpu-offload auto`, which offloads through the pipeline's `ComponentsManager`, plus `--offload-margin` to set its `memory_reserve_margin`. - Add `--workflow` passthrough; warn and ignore it on standard pipelines. - Route `model_index.json` repos whose `_class_name` is modular to the modular path. Output saving: - Resolve every media field on the output object (`images`, `frames`, `audios`, `audio`) instead of the first match, keeping the batch dimension. Fixes video output being misrouted through the image branch and LTX2's audio being dropped. - Fix the `output_type="pt"` video transpose: `postprocess_video` returns `(B, F, C, H, W)`, not `(B, C, F, H, W)`. - Save `(B, C, samples)` waveforms as multi-channel wavs (StableAudio). - Write each video's frames to `<stem>-frames/<NNNN>.png`. Frames need no video backend, so they replace the `.pt` fallback when `export_to_video` fails. - Report frame directories as a single path so hundreds of frames don't flood the terminal; `--push-to` and the sandbox download preserve subfolder structure. - Raise on unrecognized payloads instead of dumping JSON/pickle. Remote: - Add `imageio`, `imageio-ffmpeg`, and `peft` to the default sandbox deps. - Raise sandbox `start_timeout` to 600s; the 120s default expires while a cold node pulls the pytorch base image.
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What does this PR do?
Few things that were missed in the initial implementation.
In this PR:
modular_model_index.jsonwhen saving a custom block. This allowsModularPipeline.from_pretrainedto load and run custom blocks as pipelines.workflowto Modular PipelinesFixes # (issue)
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