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samples: adds batch prediction, training job for text with SDK use cases (googleapis#383)
* samples: adds batch prediction, training job for text SDK use cases
1 parent 1b09988 commit 569d4cd

8 files changed

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‎samples/model-builder/conftest.py‎

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@@ -221,6 +221,19 @@ def mock_run_automl_image_training_job(mock_image_training_job):
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yield mock
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@pytest.fixture
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def mock_get_automl_text_training_job(mock_text_training_job):
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with patch.object(aiplatform, "AutoMLTextTrainingJob") as mock:
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mock.return_value = mock_text_training_job
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yield mock
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@pytest.fixture
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def mock_run_automl_text_training_job(mock_text_training_job):
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with patch.object(mock_text_training_job, "run") as mock:
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yield mock
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@pytest.fixture
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def mock_get_custom_training_job(mock_custom_training_job):
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with patch.object(aiplatform, "CustomTrainingJob") as mock:

‎samples/model-builder/create_batch_prediction_job_sample.py‎

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@@ -17,6 +17,9 @@
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from google.cloud import aiplatform
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# [START aiplatform_sdk_create_batch_prediction_job_text_classification_sample]
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# [START aiplatform_sdk_create_batch_prediction_job_text_entity_extraction_sample]
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# [START aiplatform_sdk_create_batch_prediction_job_text_sentiment_analysis_sample]
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# [START aiplatform_sdk_create_batch_prediction_job_sample]
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def create_batch_prediction_job_sample(
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project: str,
@@ -46,4 +49,7 @@ def create_batch_prediction_job_sample(
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return batch_prediction_job
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# [END aiplatform_sdk_create_batch_prediction_job_text_sentiment_analysis_sample]
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# [END aiplatform_sdk_create_batch_prediction_job_text_entity_extraction_sample]
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# [END aiplatform_sdk_create_batch_prediction_job_text_classification_sample]
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# [END aiplatform_sdk_create_batch_prediction_job_sample]

‎samples/model-builder/create_training_pipeline_text_classification_sample.py‎

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@@ -0,0 +1,64 @@
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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Optional
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from google.cloud import aiplatform
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# [START aiplatform_sdk_create_training_pipeline_text_classification_sample]
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def create_training_pipeline_text_classification_sample(
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project: str,
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location: str,
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display_name: str,
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dataset_id: int,
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model_display_name: Optional[str] = None,
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multi_label: bool = False,
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training_fraction_split: float = 0.8,
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validation_fraction_split: float = 0.1,
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test_fraction_split: float = 0.1,
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budget_milli_node_hours: int = 8000,
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disable_early_stopping: bool = False,
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sync: bool = True,
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):
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aiplatform.init(project=project, location=location)
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job = aiplatform.AutoMLTextTrainingJob(
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display_name=display_name,
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prediction_type="classification",
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multi_label=multi_label,
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)
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text_dataset = aiplatform.TextDataset(dataset_id)
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model = job.run(
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dataset=text_dataset,
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model_display_name=model_display_name,
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training_fraction_split=training_fraction_split,
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validation_fraction_split=validation_fraction_split,
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test_fraction_split=test_fraction_split,
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budget_milli_node_hours=budget_milli_node_hours,
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disable_early_stopping=disable_early_stopping,
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sync=sync,
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)
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model.wait()
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print(model.display_name)
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print(model.resource_name)
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print(model.uri)
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return model
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# [END aiplatform_sdk_create_training_pipeline_text_classification_sample]

‎samples/model-builder/create_training_pipeline_text_classification_sample_test.py‎

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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
13+
# limitations under the License.
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import create_training_pipeline_text_classification_sample
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import test_constants as constants
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def test_create_training_pipeline_text_classification_sample(
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mock_sdk_init,
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mock_text_dataset,
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mock_get_automl_text_training_job,
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mock_run_automl_text_training_job,
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mock_get_text_dataset,
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):
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create_training_pipeline_text_classification_sample.create_training_pipeline_text_classification_sample(
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project=constants.PROJECT,
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location=constants.LOCATION,
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display_name=constants.DISPLAY_NAME,
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dataset_id=constants.RESOURCE_ID,
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model_display_name=constants.DISPLAY_NAME_2,
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training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
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validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
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test_fraction_split=constants.TEST_FRACTION_SPLIT,
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budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
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disable_early_stopping=False,
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)
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mock_get_text_dataset.assert_called_once_with(constants.RESOURCE_ID)
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mock_sdk_init.assert_called_once_with(
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project=constants.PROJECT, location=constants.LOCATION
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)
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mock_get_automl_text_training_job.assert_called_once_with(
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display_name=constants.DISPLAY_NAME,
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multi_label=False,
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prediction_type="classification",
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)
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mock_run_automl_text_training_job.assert_called_once_with(
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dataset=mock_text_dataset,
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model_display_name=constants.DISPLAY_NAME_2,
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training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
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validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
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test_fraction_split=constants.TEST_FRACTION_SPLIT,
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budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
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disable_early_stopping=False,
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sync=True,
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)

‎samples/model-builder/create_training_pipeline_text_entity_extraction_sample.py‎

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@@ -0,0 +1,61 @@
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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
4+
# you may not use this file except in compliance with the License.
5+
# You may obtain a copy of the License at
6+
#
7+
# https://www.apache.org/licenses/LICENSE-2.0
8+
#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
15+
from typing import Optional
16+
17+
from google.cloud import aiplatform
18+
19+
20+
# [START aiplatform_sdk_create_training_pipeline_text_entity_extraction_sample]
21+
def create_training_pipeline_text_entity_extraction_sample(
22+
project: str,
23+
location: str,
24+
display_name: str,
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dataset_id: int,
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model_display_name: Optional[str] = None,
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training_fraction_split: float = 0.8,
28+
validation_fraction_split: float = 0.1,
29+
test_fraction_split: float = 0.1,
30+
budget_milli_node_hours: int = 8000,
31+
disable_early_stopping: bool = False,
32+
sync: bool = True,
33+
):
34+
aiplatform.init(project=project, location=location)
35+
36+
job = aiplatform.AutoMLTextTrainingJob(
37+
display_name=display_name, prediction_type="extraction"
38+
)
39+
40+
text_dataset = aiplatform.TextDataset(dataset_id)
41+
42+
model = job.run(
43+
dataset=text_dataset,
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model_display_name=model_display_name,
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training_fraction_split=training_fraction_split,
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validation_fraction_split=validation_fraction_split,
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test_fraction_split=test_fraction_split,
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budget_milli_node_hours=budget_milli_node_hours,
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disable_early_stopping=disable_early_stopping,
50+
sync=sync,
51+
)
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model.wait()
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55+
print(model.display_name)
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print(model.resource_name)
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print(model.uri)
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return model
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# [END aiplatform_sdk_create_training_pipeline_text_entity_extraction_sample]

‎samples/model-builder/create_training_pipeline_text_entity_extraction_sample_test.py‎

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# Copyright 2021 Google LLC
2+
#
3+
# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
5+
# You may obtain a copy of the License at
6+
#
7+
# https://www.apache.org/licenses/LICENSE-2.0
8+
#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
15+
16+
import create_training_pipeline_text_entity_extraction_sample
17+
import test_constants as constants
18+
19+
20+
def test_create_training_pipeline_text_clentity_extraction_sample(
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mock_sdk_init,
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mock_text_dataset,
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mock_get_automl_text_training_job,
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mock_run_automl_text_training_job,
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mock_get_text_dataset,
26+
):
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28+
create_training_pipeline_text_entity_extraction_sample.create_training_pipeline_text_entity_extraction_sample(
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project=constants.PROJECT,
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location=constants.LOCATION,
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display_name=constants.DISPLAY_NAME,
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dataset_id=constants.RESOURCE_ID,
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model_display_name=constants.DISPLAY_NAME_2,
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training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
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validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
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test_fraction_split=constants.TEST_FRACTION_SPLIT,
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budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
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disable_early_stopping=False,
39+
)
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mock_get_text_dataset.assert_called_once_with(constants.RESOURCE_ID)
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43+
mock_sdk_init.assert_called_once_with(
44+
project=constants.PROJECT, location=constants.LOCATION
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)
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mock_get_automl_text_training_job.assert_called_once_with(
47+
display_name=constants.DISPLAY_NAME, prediction_type="extraction"
48+
)
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mock_run_automl_text_training_job.assert_called_once_with(
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dataset=mock_text_dataset,
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model_display_name=constants.DISPLAY_NAME_2,
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training_fraction_split=constants.TRAINING_FRACTION_SPLIT,
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validation_fraction_split=constants.VALIDATION_FRACTION_SPLIT,
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test_fraction_split=constants.TEST_FRACTION_SPLIT,
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budget_milli_node_hours=constants.BUDGET_MILLI_NODE_HOURS_8000,
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disable_early_stopping=False,
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sync=True,
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)

‎samples/model-builder/create_training_pipeline_text_sentiment_analysis_sample.py‎

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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
5+
# You may obtain a copy of the License at
6+
#
7+
# https://www.apache.org/licenses/LICENSE-2.0
8+
#
9+
# Unless required by applicable law or agreed to in writing, software
10+
# distributed under the License is distributed on an "AS IS" BASIS,
11+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12+
# See the License for the specific language governing permissions and
13+
# limitations under the License.
14+
15+
from typing import Optional
16+
17+
from google.cloud import aiplatform
18+
19+
20+
# [START aiplatform_sdk_create_training_pipeline_text_sentiment_analysis_sample]
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def create_training_pipeline_text_sentiment_analysis_sample(
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project: str,
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location: str,
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display_name: str,
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dataset_id: int,
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model_display_name: Optional[str] = None,
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sentiment_max: int = 10,
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training_fraction_split: float = 0.8,
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validation_fraction_split: float = 0.1,
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test_fraction_split: float = 0.1,
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budget_milli_node_hours: int = 8000,
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disable_early_stopping: bool = False,
33+
sync: bool = True,
34+
):
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aiplatform.init(project=project, location=location)
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job = aiplatform.AutoMLTextTrainingJob(
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display_name=display_name,
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prediction_type="sentiment",
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sentiment_max=sentiment_max,
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)
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text_dataset = aiplatform.TextDataset(dataset_id)
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model = job.run(
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dataset=text_dataset,
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model_display_name=model_display_name,
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training_fraction_split=training_fraction_split,
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validation_fraction_split=validation_fraction_split,
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test_fraction_split=test_fraction_split,
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budget_milli_node_hours=budget_milli_node_hours,
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disable_early_stopping=disable_early_stopping,
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sync=sync,
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)
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model.wait()
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print(model.display_name)
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print(model.resource_name)
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print(model.uri)
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return model
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# [END aiplatform_sdk_create_training_pipeline_text_sentiment_analysis_sample]

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