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13 changes: 13 additions & 0 deletions samples/model-builder/conftest.py
Original file line number Diff line number Diff line change
Expand Up @@ -209,6 +209,19 @@ def mock_run_automl_image_training_job(mock_image_training_job):
yield mock


@pytest.fixture
def mock_get_automl_text_training_job(mock_text_training_job):
with patch.object(aiplatform, "AutoMLTextTrainingJob") as mock:
mock.return_value = mock_text_training_job
yield mock


@pytest.fixture
def mock_run_automl_text_training_job(mock_text_training_job):
with patch.object(mock_text_training_job, "run") as mock:
yield mock


@pytest.fixture
def mock_get_custom_training_job(mock_custom_training_job):
with patch.object(aiplatform, "CustomTrainingJob") as mock:
Expand Down
6 changes: 6 additions & 0 deletions samples/model-builder/create_batch_prediction_job_sample.py
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,9 @@
from google.cloud import aiplatform


# [START aiplatform_sdk_create_batch_prediction_job_text_classification_sample]
# [START aiplatform_sdk_create_batch_prediction_job_text_entity_extraction_sample]
# [START aiplatform_sdk_create_batch_prediction_job_text_sentiment_analysis_sample]
# [START aiplatform_sdk_create_batch_prediction_job_sample]
def create_batch_prediction_job_sample(
project: str,
Expand Down Expand Up @@ -46,4 +49,7 @@ def create_batch_prediction_job_sample(
return batch_prediction_job


# [END aiplatform_sdk_create_batch_prediction_job_text_sentiment_analysis_sample]
# [END aiplatform_sdk_create_batch_prediction_job_text_entity_extraction_sample]
# [END aiplatform_sdk_create_batch_prediction_job_text_classification_sample]
# [END aiplatform_sdk_create_batch_prediction_job_sample]
Original file line number Diff line number Diff line change
@@ -0,0 +1,64 @@
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import Optional

from google.cloud import aiplatform


# [START aiplatform_sdk_create_training_pipeline_text_classification_sample]
def create_training_pipeline_text_classification_sample(
project: str,
location: str,
display_name: str,
dataset_id: int,
model_display_name: Optional[str] = None,
Comment thread
telpirion marked this conversation as resolved.
multi_label: bool = False,
training_fraction_split: float = 0.8,
validation_fraction_split: float = 0.1,
test_fraction_split: float = 0.1,
budget_milli_node_hours: int = 8000,
disable_early_stopping: bool = False,
sync: bool = True,
):
aiplatform.init(project=project, location=location)

job = aiplatform.AutoMLTextTrainingJob(
display_name=display_name,
prediction_type="classification",
multi_label=multi_label,
)

text_dataset = aiplatform.TextDataset(dataset_id)

model = job.run(
dataset=text_dataset,
model_display_name=model_display_name,
training_fraction_split=training_fraction_split,
validation_fraction_split=validation_fraction_split,
test_fraction_split=test_fraction_split,
budget_milli_node_hours=budget_milli_node_hours,
disable_early_stopping=disable_early_stopping,
sync=sync,
)

model.wait()

print(model.display_name)
print(model.resource_name)
print(model.uri)
return model


# [END aiplatform_sdk_create_training_pipeline_text_classification_sample]
Original file line number Diff line number Diff line change
@@ -0,0 +1,60 @@
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import create_training_pipeline_text_classification_sample
import test_constants as constants


def test_create_training_pipeline_text_classification_sample(
mock_sdk_init,
mock_text_dataset,
mock_get_automl_text_training_job,
mock_run_automl_text_training_job,
mock_get_text_dataset,
):

create_training_pipeline_text_classification_sample.create_training_pipeline_text_classification_sample(
project=constants.PROJECT,
location=constants.LOCATION,
display_name=constants.DISPLAY_NAME,
dataset_id=constants.RESOURCE_ID,
model_display_name=constants.DISPLAY_NAME_2,
training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
test_fraction_split=constants.TEST_FRACTION_SPLIT,
budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
disable_early_stopping=False,
)

mock_get_text_dataset.assert_called_once_with(constants.RESOURCE_ID)

mock_sdk_init.assert_called_once_with(
project=constants.PROJECT, location=constants.LOCATION
)
mock_get_automl_text_training_job.assert_called_once_with(
display_name=constants.DISPLAY_NAME,
multi_label=False,
prediction_type="classification",
)
mock_run_automl_text_training_job.assert_called_once_with(
dataset=mock_text_dataset,
model_display_name=constants.DISPLAY_NAME_2,
training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
test_fraction_split=constants.TEST_FRACTION_SPLIT,
budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
disable_early_stopping=False,
sync=True,
)
Original file line number Diff line number Diff line change
@@ -0,0 +1,61 @@
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import Optional

from google.cloud import aiplatform


# [START aiplatform_sdk_create_training_pipeline_text_entity_extraction_sample]
def create_training_pipeline_text_entity_extraction_sample(
project: str,
location: str,
display_name: str,
dataset_id: int,
model_display_name: Optional[str] = None,
training_fraction_split: float = 0.8,
validation_fraction_split: float = 0.1,
test_fraction_split: float = 0.1,
budget_milli_node_hours: int = 8000,
disable_early_stopping: bool = False,
sync: bool = True,
):
aiplatform.init(project=project, location=location)

job = aiplatform.AutoMLTextTrainingJob(
display_name=display_name, prediction_type="extraction"
)

text_dataset = aiplatform.TextDataset(dataset_id)

model = job.run(
dataset=text_dataset,
model_display_name=model_display_name,
training_fraction_split=training_fraction_split,
validation_fraction_split=validation_fraction_split,
test_fraction_split=test_fraction_split,
budget_milli_node_hours=budget_milli_node_hours,
disable_early_stopping=disable_early_stopping,
sync=sync,
)

model.wait()

print(model.display_name)
print(model.resource_name)
print(model.uri)
return model


# [END aiplatform_sdk_create_training_pipeline_text_entity_extraction_sample]
Original file line number Diff line number Diff line change
@@ -0,0 +1,58 @@
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import create_training_pipeline_text_entity_extraction_sample
import test_constants as constants


def test_create_training_pipeline_text_clentity_extraction_sample(
mock_sdk_init,
mock_text_dataset,
mock_get_automl_text_training_job,
mock_run_automl_text_training_job,
mock_get_text_dataset,
):

create_training_pipeline_text_entity_extraction_sample.create_training_pipeline_text_entity_extraction_sample(
project=constants.PROJECT,
location=constants.LOCATION,
display_name=constants.DISPLAY_NAME,
dataset_id=constants.RESOURCE_ID,
model_display_name=constants.DISPLAY_NAME_2,
training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
test_fraction_split=constants.TEST_FRACTION_SPLIT,
budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
disable_early_stopping=False,
)

mock_get_text_dataset.assert_called_once_with(constants.RESOURCE_ID)

mock_sdk_init.assert_called_once_with(
project=constants.PROJECT, location=constants.LOCATION
)
mock_get_automl_text_training_job.assert_called_once_with(
display_name=constants.DISPLAY_NAME, prediction_type="extraction"
)
mock_run_automl_text_training_job.assert_called_once_with(
dataset=mock_text_dataset,
model_display_name=constants.DISPLAY_NAME_2,
training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
test_fraction_split=constants.TEST_FRACTION_SPLIT,
budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
disable_early_stopping=False,
sync=True,
)
Original file line number Diff line number Diff line change
@@ -0,0 +1,64 @@
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import Optional

from google.cloud import aiplatform


# [START aiplatform_sdk_create_training_pipeline_text_sentiment_analysis_sample]
def create_training_pipeline_text_sentiment_analysis_sample(
project: str,
location: str,
display_name: str,
dataset_id: int,
model_display_name: Optional[str] = None,
Comment thread
telpirion marked this conversation as resolved.
sentiment_max: int = 10,
training_fraction_split: float = 0.8,
validation_fraction_split: float = 0.1,
test_fraction_split: float = 0.1,
budget_milli_node_hours: int = 8000,
disable_early_stopping: bool = False,
sync: bool = True,
):
aiplatform.init(project=project, location=location)

job = aiplatform.AutoMLTextTrainingJob(
display_name=display_name,
prediction_type="sentiment",
sentiment_max=sentiment_max,
)

text_dataset = aiplatform.TextDataset(dataset_id)

model = job.run(
dataset=text_dataset,
model_display_name=model_display_name,
training_fraction_split=training_fraction_split,
validation_fraction_split=validation_fraction_split,
test_fraction_split=test_fraction_split,
budget_milli_node_hours=budget_milli_node_hours,
disable_early_stopping=disable_early_stopping,
sync=sync,
)

model.wait()

print(model.display_name)
print(model.resource_name)
print(model.uri)
return model


# [END aiplatform_sdk_create_training_pipeline_text_sentiment_analysis_sample]
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