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automl: video beta - move beta samples out of branch and into master (#…
…2750) * automl: video beta - move beta samples out of branch and into master * lint * update error message on batch predict Co-authored-by: Leah E. Cole <6719667+leahecole@users.noreply.github.com>
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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 batch_predict(project_id, model_id, input_uri, output_uri): | ||
"""Batch predict""" | ||
# [START automl_batch_predict_beta] | ||
from google.cloud import automl_v1beta1 as automl | ||
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# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# model_id = "YOUR_MODEL_ID" | ||
# input_uri = "gs://YOUR_BUCKET_ID/path/to/your/input/csv_or_jsonl" | ||
# output_uri = "gs://YOUR_BUCKET_ID/path/to/save/results/" | ||
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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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gcs_source = automl.types.GcsSource(input_uris=[input_uri]) | ||
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input_config = automl.types.BatchPredictInputConfig(gcs_source=gcs_source) | ||
gcs_destination = automl.types.GcsDestination(output_uri_prefix=output_uri) | ||
output_config = automl.types.BatchPredictOutputConfig( | ||
gcs_destination=gcs_destination | ||
) | ||
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response = prediction_client.batch_predict( | ||
model_full_id, input_config, output_config | ||
) | ||
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print("Waiting for operation to complete...") | ||
print( | ||
"Batch Prediction results saved to Cloud Storage bucket. {}".format( | ||
response.result() | ||
) | ||
) | ||
# [END automl_batch_predict_beta] |
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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 ladnguage governing permissions and | ||
# limitations under the License. | ||
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import datetime | ||
import os | ||
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import batch_predict | ||
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PROJECT_ID = os.environ["AUTOML_PROJECT_ID"] | ||
BUCKET_ID = "{}-lcm".format(PROJECT_ID) | ||
MODEL_ID = "TEN0000000000000000000" | ||
PREFIX = "TEST_EXPORT_OUTPUT_" + datetime.datetime.now().strftime( | ||
"%Y%m%d%H%M%S" | ||
) | ||
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def test_batch_predict(capsys): | ||
# As batch prediction can take a long time. Try to batch predict on a model | ||
# and confirm that the model was not found, but other elements of the | ||
# request were valid. | ||
try: | ||
input_uri = "gs://{}/entity-extraction/input.jsonl".format(BUCKET_ID) | ||
output_uri = "gs://{}/{}/".format(BUCKET_ID, PREFIX) | ||
batch_predict.batch_predict( | ||
PROJECT_ID, MODEL_ID, input_uri, output_uri | ||
) | ||
out, _ = capsys.readouterr() | ||
assert ( | ||
"does not exist" | ||
in out | ||
) | ||
except Exception as e: | ||
assert ( | ||
"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 create_dataset(project_id, display_name): | ||
"""Create a dataset.""" | ||
# [START automl_video_classification_create_dataset_beta] | ||
from google.cloud import automl_v1beta1 as automl | ||
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# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# display_name = "your_datasets_display_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.VideoClassificationDatasetMetadata() | ||
dataset = automl.types.Dataset( | ||
display_name=display_name, | ||
video_classification_dataset_metadata=metadata, | ||
) | ||
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# Create a dataset with the dataset metadata in the region. | ||
created_dataset = client.create_dataset(project_location, dataset) | ||
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# Display the dataset information | ||
print("Dataset name: {}".format(created_dataset.name)) | ||
# To get the dataset id, you have to parse it out of the `name` field. | ||
# As dataset Ids are required for other methods. | ||
# Name Form: | ||
# `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}` | ||
print("Dataset id: {}".format(created_dataset.name.split("/")[-1])) | ||
# [END automl_video_classification_create_dataset_beta] |
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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_v1beta1 as automl | ||
import pytest | ||
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import video_classification_create_dataset | ||
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PROJECT_ID = os.environ["AUTOML_PROJECT_ID"] | ||
pytest.DATASET_ID = None | ||
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@pytest.fixture(scope="function", autouse=True) | ||
def teardown(): | ||
yield | ||
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# Delete the created dataset | ||
client = automl.AutoMlClient() | ||
dataset_full_id = client.dataset_path( | ||
PROJECT_ID, "us-central1", pytest.DATASET_ID | ||
) | ||
response = client.delete_dataset(dataset_full_id) | ||
response.result() | ||
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def test_video_classification_create_dataset(capsys): | ||
# create dataset | ||
dataset_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S") | ||
video_classification_create_dataset.create_dataset( | ||
PROJECT_ID, dataset_name | ||
) | ||
out, _ = capsys.readouterr() | ||
assert "Dataset id: " in out | ||
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# Get the the created dataset id for deletion | ||
pytest.DATASET_ID = out.splitlines()[1].split()[2] |
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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_video_classification_create_model_beta] | ||
from google.cloud import automl_v1beta1 as automl | ||
|
||
# TODO(developer): Uncomment and set the following variables | ||
# project_id = "YOUR_PROJECT_ID" | ||
# dataset_id = "YOUR_DATASET_ID" | ||
# display_name = "your_models_display_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.VideoClassificationModelMetadata() | ||
model = automl.types.Model( | ||
display_name=display_name, | ||
dataset_id=dataset_id, | ||
video_classification_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_video_classification_create_model_beta] |
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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_v1beta1 as automl | ||
import pytest | ||
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import video_classification_create_model | ||
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PROJECT_ID = os.environ["GCLOUD_PROJECT"] | ||
DATASET_ID = "VCN510437278078730240" | ||
pytest.OPERATION_ID = None | ||
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@pytest.fixture(scope="function", autouse=True) | ||
def teardown(): | ||
yield | ||
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# Cancel the operation | ||
client = automl.AutoMlClient() | ||
client.transport._operations_client.cancel_operation(pytest.OPERATION_ID) | ||
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def test_video_classification_create_model(capsys): | ||
video_classification_create_model.create_model( | ||
PROJECT_ID, DATASET_ID, "classification_test_create_model" | ||
) | ||
out, _ = capsys.readouterr() | ||
assert "Training started" in out | ||
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# Get the the operation id for cancellation | ||
pytest.OPERATION_ID = out.split("Training operation name: ")[1].split( | ||
"\n" | ||
)[0] |