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automl: add natural language entity extraction ga samples [(#2676)](G…
…oogleCloudPlatform/python-docs-samples#2676) * automl: add natural language entity extraction ga samples * Update language_entity_extraction_predict_test.py * Update language_entity_extraction_predict_test.py * use centralized automl testing project and add comments that link to docs
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42 changes: 42 additions & 0 deletions
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samples/snippets/language_entity_extraction_create_dataset.py
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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def create_dataset(project_id, display_name): | ||
"""Create a dataset.""" | ||
# [START automl_language_entity_extraction_create_dataset] | ||
from google.cloud import automl | ||
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# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# display_name = "YOUR_DATASET_NAME" | ||
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client = automl.AutoMlClient() | ||
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# A resource that represents Google Cloud Platform location. | ||
project_location = client.location_path(project_id, "us-central1") | ||
metadata = automl.types.TextExtractionDatasetMetadata() | ||
dataset = automl.types.Dataset( | ||
display_name=display_name, text_extraction_dataset_metadata=metadata | ||
) | ||
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# Create a dataset with the dataset metadata in the region. | ||
response = client.create_dataset(project_location, dataset) | ||
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created_dataset = response.result() | ||
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# Display the dataset information | ||
print("Dataset name: {}".format(created_dataset.name)) | ||
print("Dataset id: {}".format(created_dataset.name.split("/")[-1])) | ||
# [END automl_language_entity_extraction_create_dataset] |
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samples/snippets/language_entity_extraction_create_dataset_test.py
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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import datetime | ||
import os | ||
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from google.cloud import automl | ||
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import language_entity_extraction_create_dataset | ||
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PROJECT_ID = os.environ["AUTOML_PROJECT_ID"] | ||
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def test_entity_extraction_create_dataset(capsys): | ||
# create dataset | ||
dataset_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S") | ||
language_entity_extraction_create_dataset.create_dataset( | ||
PROJECT_ID, dataset_name | ||
) | ||
out, _ = capsys.readouterr() | ||
assert "Dataset id: " in out | ||
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# Delete the created dataset | ||
dataset_id = out.splitlines()[1].split()[2] | ||
client = automl.AutoMlClient() | ||
dataset_full_id = client.dataset_path( | ||
PROJECT_ID, "us-central1", dataset_id | ||
) | ||
response = client.delete_dataset(dataset_full_id) | ||
response.result() |
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samples/snippets/language_entity_extraction_create_model.py
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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def create_model(project_id, dataset_id, display_name): | ||
"""Create a model.""" | ||
# [START automl_language_entity_extraction_create_model] | ||
from google.cloud import automl | ||
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# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# dataset_id = "YOUR_DATASET_ID" | ||
# display_name = "YOUR_MODEL_NAME" | ||
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client = automl.AutoMlClient() | ||
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# A resource that represents Google Cloud Platform location. | ||
project_location = client.location_path(project_id, "us-central1") | ||
# Leave model unset to use the default base model provided by Google | ||
metadata = automl.types.TextExtractionModelMetadata() | ||
model = automl.types.Model( | ||
display_name=display_name, | ||
dataset_id=dataset_id, | ||
text_extraction_model_metadata=metadata, | ||
) | ||
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# Create a model with the model metadata in the region. | ||
response = client.create_model(project_location, model) | ||
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print("Training operation name: {}".format(response.operation.name)) | ||
print("Training started...") | ||
# [END automl_language_entity_extraction_create_model] |
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samples/snippets/language_entity_extraction_create_model_test.py
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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import os | ||
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import language_entity_extraction_create_model | ||
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PROJECT_ID = os.environ["AUTOML_PROJECT_ID"] | ||
DATASET_ID = "TEN0000000000000000000" | ||
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def test_entity_extraction_create_model(capsys): | ||
# As entity extraction does not let you cancel model creation, instead try | ||
# to create a model from a nonexistent dataset, but other elements of the | ||
# request were valid. | ||
try: | ||
language_entity_extraction_create_model.create_model( | ||
PROJECT_ID, DATASET_ID, "classification_test_create_model" | ||
) | ||
out, _ = capsys.readouterr() | ||
assert "Dataset does not exist." in out | ||
except Exception as e: | ||
assert "Dataset does not exist." in e.message |
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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def predict(project_id, model_id, content): | ||
"""Predict.""" | ||
# [START automl_language_entity_extraction_predict] | ||
from google.cloud import automl | ||
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# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# model_id = "YOUR_MODEL_ID" | ||
# content = "text to predict" | ||
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prediction_client = automl.PredictionServiceClient() | ||
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# Get the full path of the model. | ||
model_full_id = prediction_client.model_path( | ||
project_id, "us-central1", model_id | ||
) | ||
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# Supported mime_types: 'text/plain', 'text/html' | ||
# https://cloud.google.com/automl/docs/reference/rpc/google.cloud.automl.v1#textsnippet | ||
text_snippet = automl.types.TextSnippet( | ||
content=content, mime_type="text/plain" | ||
) | ||
payload = automl.types.ExamplePayload(text_snippet=text_snippet) | ||
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response = prediction_client.predict(model_full_id, payload) | ||
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for annotation_payload in response.payload: | ||
print( | ||
"Text Extract Entity Types: {}".format( | ||
annotation_payload.display_name | ||
) | ||
) | ||
print( | ||
"Text Score: {}".format(annotation_payload.text_extraction.score) | ||
) | ||
text_segment = annotation_payload.text_extraction.text_segment | ||
print("Text Extract Entity Content: {}".format(text_segment.content)) | ||
print("Text Start Offset: {}".format(text_segment.start_offset)) | ||
print("Text End Offset: {}".format(text_segment.end_offset)) | ||
# [END automl_language_entity_extraction_predict] |
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samples/snippets/language_entity_extraction_predict_test.py
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# Copyright 2020 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 | ||
# | ||
# http://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. | ||
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import os | ||
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from google.cloud import automl | ||
import pytest | ||
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import language_entity_extraction_predict | ||
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PROJECT_ID = os.environ["AUTOML_PROJECT_ID"] | ||
MODEL_ID = os.environ["ENTITY_EXTRACTION_MODEL_ID"] | ||
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@pytest.fixture(scope="function") | ||
def verify_model_state(): | ||
client = automl.AutoMlClient() | ||
model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID) | ||
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model = client.get_model(model_full_id) | ||
if model.deployment_state == automl.enums.Model.DeploymentState.UNDEPLOYED: | ||
# Deploy model if it is not deployed | ||
response = client.deploy_model(model_full_id) | ||
response.result() | ||
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def test_predict(capsys, verify_model_state): | ||
verify_model_state | ||
text = ( | ||
"Constitutional mutations in the WT1 gene in patients with " | ||
"Denys-Drash syndrome." | ||
) | ||
language_entity_extraction_predict.predict(PROJECT_ID, MODEL_ID, text) | ||
out, _ = capsys.readouterr() | ||
assert "Text Extract Entity Types: " in out |