samples: adds batch prediction, training job for text with SDK use ca…

…ses (#383)

* samples: adds batch prediction, training job for text SDK use cases

samples/model-builder/conftest.py

@@ -221,6 +221,19 @@ 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:

samples/model-builder/create_batch_prediction_job_sample.py

@@ -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,
@@ -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]

samples/model-builder/create_training_pipeline_text_classification_sample.py

@@ -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,
+    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]

samples/model-builder/create_training_pipeline_text_classification_sample_test.py

@@ -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,
+    )

samples/model-builder/create_training_pipeline_text_entity_extraction_sample.py

@@ -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]

samples/model-builder/create_training_pipeline_text_entity_extraction_sample_test.py

@@ -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,
+    )

samples/model-builder/create_training_pipeline_text_sentiment_analysis_sample.py

@@ -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,
+    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]