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gericdongivanmkc
gericdong
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ivanmkc
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feat: update the samples of hyperparameter tuning in the public doc (#1600)
* Update Hyperparameter tuning job samples * Update Hyperparameter tuning job samples 2 * feat: fix linting problems in the hyperparamter tuning job samples * feat: resolve conflict for the hyperparameter tuning samples * feat: fix lint problems Co-authored-by: Ivan Cheung <[email protected]>
1 parent 8539327 commit 653b759

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-0
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‎samples/model-builder/cancel_hyperparameter_tuning_job_sample.py

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# Copyright 2022 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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# [START aiplatform_sdk_cancel_hyperparameter_tuning_job_sample]
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from google.cloud import aiplatform
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def cancel_hyperparameter_tuning_job_sample(
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project: str,
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hyperparameter_tuning_job_id: str,
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location: str = "us-central1",
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):
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aiplatform.init(project=project, location=location)
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hpt_job = aiplatform.HyperparameterTuningJob.get(
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resource_name=hyperparameter_tuning_job_id,
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)
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hpt_job.cancel()
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# [END aiplatform_sdk_cancel_hyperparameter_tuning_job_sample]

‎samples/model-builder/cancel_hyperparameter_tuning_job_sample_test.py

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# Copyright 2022 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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import cancel_hyperparameter_tuning_job_sample
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import test_constants as constants
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def test_cancel_hyperparameter_tuning_job_sample(
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mock_sdk_init,
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mock_hyperparameter_tuning_job_get,
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mock_hyperparameter_tuning_job_cancel,
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):
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cancel_hyperparameter_tuning_job_sample.cancel_hyperparameter_tuning_job_sample(
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project=constants.PROJECT,
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location=constants.LOCATION,
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hyperparameter_tuning_job_id=constants.HYPERPARAMETER_TUNING_JOB_ID,
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)
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mock_sdk_init.assert_called_once_with(
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project=constants.PROJECT,
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location=constants.LOCATION,
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)
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mock_hyperparameter_tuning_job_get.assert_called_once_with(
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resource_name=constants.HYPERPARAMETER_TUNING_JOB_ID,
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)
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mock_hyperparameter_tuning_job_cancel.assert_called_once_with()

‎samples/model-builder/conftest.py

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@@ -327,6 +327,19 @@ def mock_run_custom_package_training_job(mock_custom_package_training_job):
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yield mock
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@pytest.fixture
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def mock_custom_job():
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mock = MagicMock(aiplatform.CustomJob)
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yield mock
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@pytest.fixture
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def mock_get_custom_job(mock_custom_job):
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with patch.object(aiplatform, "CustomJob") as mock:
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mock.return_value = mock_custom_job
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yield mock
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"""
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----------------------------------------------------------------------------
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Model Fixtures
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mock_get_endpoint.return_value = mock_endpoint
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yield mock_endpoint_explain
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# ----------------------------------------------------------------------------
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# Hyperparameter Tuning Job Fixtures
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# ----------------------------------------------------------------------------
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@pytest.fixture
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def mock_hyperparameter_tuning_job():
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mock = MagicMock(aiplatform.HyperparameterTuningJob)
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yield mock
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@pytest.fixture
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def mock_get_hyperparameter_tuning_job(mock_hyperparameter_tuning_job):
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with patch.object(aiplatform, "HyperparameterTuningJob") as mock:
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mock.return_value = mock_hyperparameter_tuning_job
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yield mock
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@pytest.fixture
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def mock_run_hyperparameter_tuning_job(mock_hyperparameter_tuning_job):
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with patch.object(mock_hyperparameter_tuning_job, "run") as mock:
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yield mock
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@pytest.fixture
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def mock_hyperparameter_tuning_job_get(mock_hyperparameter_tuning_job):
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with patch.object(aiplatform.HyperparameterTuningJob, "get") as mock_hyperparameter_tuning_job_get:
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mock_hyperparameter_tuning_job_get.return_value = mock_hyperparameter_tuning_job
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yield mock_hyperparameter_tuning_job_get
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@pytest.fixture
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def mock_hyperparameter_tuning_job_cancel(mock_hyperparameter_tuning_job):
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with patch.object(mock_hyperparameter_tuning_job, "cancel") as mock:
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yield mock
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@pytest.fixture
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def mock_hyperparameter_tuning_job_delete(mock_hyperparameter_tuning_job):
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with patch.object(mock_hyperparameter_tuning_job, "delete") as mock:
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yield mock
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"""
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----------------------------------------------------------------------------

‎samples/model-builder/create_hyperparameter_tuning_job_sample.py

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# Copyright 2022 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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# [START aiplatform_sdk_create_hyperparameter_tuning_job_sample]
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from google.cloud import aiplatform
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from google.cloud.aiplatform import hyperparameter_tuning as hpt
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def create_hyperparameter_tuning_job_sample(
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project: str,
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location: str,
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staging_bucket: str,
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display_name: str,
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container_uri: str,
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):
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aiplatform.init(project=project, location=location, staging_bucket=staging_bucket)
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worker_pool_specs = [
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{
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"machine_spec": {
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"machine_type": "n1-standard-4",
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"accelerator_type": "NVIDIA_TESLA_K80",
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"accelerator_count": 1,
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},
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"replica_count": 1,
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"container_spec": {
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"image_uri": container_uri,
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"command": [],
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"args": [],
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},
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}
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]
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custom_job = aiplatform.CustomJob(
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display_name='custom_job',
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worker_pool_specs=worker_pool_specs,
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)
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hpt_job = aiplatform.HyperparameterTuningJob(
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display_name=display_name,
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custom_job=custom_job,
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metric_spec={
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'loss': 'minimize',
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},
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parameter_spec={
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'lr': hpt.DoubleParameterSpec(min=0.001, max=0.1, scale='log'),
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'units': hpt.IntegerParameterSpec(min=4, max=128, scale='linear'),
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'activation': hpt.CategoricalParameterSpec(values=['relu', 'selu']),
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'batch_size': hpt.DiscreteParameterSpec(values=[128, 256], scale='linear')
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},
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max_trial_count=128,
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parallel_trial_count=8,
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labels={'my_key': 'my_value'},
66+
)
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hpt_job.run()
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print(hpt_job.resource_name)
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return hpt_job
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# [END aiplatform_sdk_create_hyperparameter_tuning_job_sample]

‎samples/model-builder/create_hyperparameter_tuning_job_sample_test.py

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# Copyright 2022 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 unittest.mock import ANY
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import create_hyperparameter_tuning_job_sample
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import test_constants as constants
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def test_create_hyperparameter_tuning_job_sample(
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mock_sdk_init,
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mock_custom_job,
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mock_get_custom_job,
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mock_get_hyperparameter_tuning_job,
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mock_run_hyperparameter_tuning_job,
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):
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create_hyperparameter_tuning_job_sample.create_hyperparameter_tuning_job_sample(
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project=constants.PROJECT,
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location=constants.LOCATION,
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staging_bucket=constants.STAGING_BUCKET,
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display_name=constants.HYPERPARAMETER_TUNING_JOB_DISPLAY_NAME,
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container_uri=constants.CONTAINER_URI,
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)
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mock_sdk_init.assert_called_once_with(
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project=constants.PROJECT,
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location=constants.LOCATION,
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staging_bucket=constants.STAGING_BUCKET,
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)
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mock_get_custom_job.assert_called_once_with(
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display_name=constants.CUSTOM_JOB_DISPLAY_NAME,
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worker_pool_specs=constants.CUSTOM_JOB_WORKER_POOL_SPECS,
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)
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mock_get_hyperparameter_tuning_job.assert_called_once_with(
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display_name=constants.HYPERPARAMETER_TUNING_JOB_DISPLAY_NAME,
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custom_job=mock_custom_job,
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metric_spec=constants.HYPERPARAMETER_TUNING_JOB_METRIC_SPEC,
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parameter_spec=ANY,
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max_trial_count=constants.HYPERPARAMETER_TUNING_JOB_MAX_TRIAL_COUNT,
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parallel_trial_count=constants.HYPERPARAMETER_TUNING_JOB_PARALLEL_TRIAL_COUNT,
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labels=constants.HYPERPARAMETER_TUNING_JOB_LABELS,
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)
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mock_run_hyperparameter_tuning_job.assert_called_once()

‎samples/model-builder/delete_hyperparameter_tuning_job_sample.py

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# Copyright 2022 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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#
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+
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# [START aiplatform_sdk_delete_hyperparameter_tuning_job_sample]
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from google.cloud import aiplatform
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def delete_hyperparameter_tuning_job_sample(
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project: str,
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hyperparameter_tuning_job_id: str,
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location: str = "us-central1",
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):
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aiplatform.init(project=project, location=location)
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hpt_job = aiplatform.HyperparameterTuningJob.get(
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resource_name=hyperparameter_tuning_job_id,
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)
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hpt_job.delete()
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# [END aiplatform_sdk_delete_hyperparameter_tuning_job_sample]

‎samples/model-builder/delete_hyperparameter_tuning_job_sample_test.py

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# Copyright 2022 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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#
7+
# 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,
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+
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import delete_hyperparameter_tuning_job_sample
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import test_constants as constants
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def test_delete_hyperparameter_tuning_job_sample(
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mock_sdk_init,
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mock_hyperparameter_tuning_job_get,
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mock_hyperparameter_tuning_job_delete,
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):
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delete_hyperparameter_tuning_job_sample.delete_hyperparameter_tuning_job_sample(
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project=constants.PROJECT,
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location=constants.LOCATION,
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hyperparameter_tuning_job_id=constants.HYPERPARAMETER_TUNING_JOB_ID,
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)
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mock_sdk_init.assert_called_once_with(
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project=constants.PROJECT,
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location=constants.LOCATION,
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)
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mock_hyperparameter_tuning_job_get.assert_called_once_with(
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resource_name=constants.HYPERPARAMETER_TUNING_JOB_ID,
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)
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mock_hyperparameter_tuning_job_delete.assert_called_once_with()

‎samples/model-builder/get_hyperparameter_tuning_job_sample.py

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# Copyright 2022 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
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#
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+
# [START aiplatform_sdk_get_hyperparameter_tuning_job_sample]
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from google.cloud import aiplatform
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18+
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def get_hyperparameter_tuning_job_sample(
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project: str,
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hyperparameter_tuning_job_id: str,
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location: str = "us-central1",
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):
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aiplatform.init(project=project, location=location)
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hpt_job = aiplatform.HyperparameterTuningJob.get(
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resource_name=hyperparameter_tuning_job_id,
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)
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return hpt_job
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# [END aiplatform_sdk_get_hyperparameter_tuning_job_sample]

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