feat: add create_hyperparameter_tuning_job_python_package sample (#76)

samples/snippets/create_hyperparameter_tuning_job_python_package_sample.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
+#
+#     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.
+
+# [START aiplatform_create_hyperparameter_tuning_job_python_package_sample]
+from google.cloud import aiplatform
+
+
+def create_hyperparameter_tuning_job_python_package_sample(
+    project: str,
+    display_name: str,
+    executor_image_uri: str,
+    package_uri: str,
+    python_module: str,
+    location: str = "us-central1",
+    api_endpoint: str = "us-central1-aiplatform.googleapis.com",
+):
+    client_options = {"api_endpoint": api_endpoint}
+    # Initialize client that will be used to create and send requests.
+    # This client only needs to be created once, and can be reused for multiple requests.
+    client = aiplatform.gapic.JobServiceClient(client_options=client_options)
+
+    # study_spec
+    metric = {
+        "metric_id": "val_rmse",
+        "goal": aiplatform.gapic.StudySpec.MetricSpec.GoalType.MINIMIZE,
+    }
+
+    conditional_parameter_decay = {
+        "parameter_spec": {
+            "parameter_id": "decay",
+            "double_value_spec": {"min_value": 1e-07, "max_value": 1},
+            "scale_type": aiplatform.gapic.StudySpec.ParameterSpec.ScaleType.UNIT_LINEAR_SCALE,
+        },
+        "parent_discrete_values": {"values": [32, 64]},
+    }
+    conditional_parameter_learning_rate = {
+        "parameter_spec": {
+            "parameter_id": "learning_rate",
+            "double_value_spec": {"min_value": 1e-07, "max_value": 1},
+            "scale_type": aiplatform.gapic.StudySpec.ParameterSpec.ScaleType.UNIT_LINEAR_SCALE,
+        },
+        "parent_discrete_values": {"values": [4, 8, 16]},
+    }
+    parameter = {
+        "parameter_id": "batch_size",
+        "discrete_value_spec": {"values": [4, 8, 16, 32, 64, 128]},
+        "scale_type": aiplatform.gapic.StudySpec.ParameterSpec.ScaleType.UNIT_LINEAR_SCALE,
+        "conditional_parameter_specs": [
+            conditional_parameter_decay,
+            conditional_parameter_learning_rate,
+        ],
+    }
+
+    # trial_job_spec
+    machine_spec = {
+        "machine_type": "n1-standard-4",
+        "accelerator_type": aiplatform.gapic.AcceleratorType.NVIDIA_TESLA_K80,
+        "accelerator_count": 1,
+    }
+    worker_pool_spec = {
+        "machine_spec": machine_spec,
+        "replica_count": 1,
+        "python_package_spec": {
+            "executor_image_uri": executor_image_uri,
+            "package_uris": [package_uri],
+            "python_module": python_module,
+            "args": [],
+        },
+    }
+
+    # hyperparameter_tuning_job
+    hyperparameter_tuning_job = {
+        "display_name": display_name,
+        "max_trial_count": 4,
+        "parallel_trial_count": 2,
+        "study_spec": {
+            "metrics": [metric],
+            "parameters": [parameter],
+            "algorithm": aiplatform.gapic.StudySpec.Algorithm.RANDOM_SEARCH,
+        },
+        "trial_job_spec": {"worker_pool_specs": [worker_pool_spec]},
+    }
+    parent = f"projects/{project}/locations/{location}"
+    response = client.create_hyperparameter_tuning_job(
+        parent=parent, hyperparameter_tuning_job=hyperparameter_tuning_job
+    )
+    print("response:", response)
+
+
+# [END aiplatform_create_hyperparameter_tuning_job_python_package_sample]

samples/snippets/create_hyperparameter_tuning_job_python_package_sample_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.
+
+import uuid
+import pytest
+import os
+
+import helpers
+
+import create_hyperparameter_tuning_job_python_package_sample
+
+from google.cloud import aiplatform
+
+PROJECT_ID = os.getenv("BUILD_SPECIFIC_GCLOUD_PROJECT")
+
+API_ENDPOINT = "us-central1-aiplatform.googleapis.com"
+
+DISPLAY_NAME = (
+    f"temp_create_hyperparameter_tuning_job_python_package_test_{uuid.uuid4()}"
+)
+
+EXECUTOR_IMAGE_URI = "us.gcr.io/cloud-aiplatform/training/tf-gpu.2-1:latest"
+PACKAGE_URI = "gs://ucaip-test-us-central1/training/pythonpackages/trainer.tar.bz2"
+PYTHON_MODULE = "trainer.hptuning_trainer"
+
+@pytest.fixture
+def shared_state():
+    state = {}
+    yield state
+
+
+@pytest.fixture
+def job_client():
+    client_options = {"api_endpoint": API_ENDPOINT}
+    job_client = aiplatform.gapic.JobServiceClient(
+        client_options=client_options)
+    yield job_client
+
+
+@pytest.fixture(scope="function", autouse=True)
+def teardown(shared_state, job_client):
+    yield
+
+    # Cancel the created hyperparameter tuning job
+    job_client.cancel_hyperparameter_tuning_job(
+        name=shared_state["hyperparameter_tuning_job_name"]
+    )
+
+    # Waiting for hyperparameter tuning job to be in CANCELLED state
+    helpers.wait_for_job_state(
+        get_job_method=job_client.get_hyperparameter_tuning_job,
+        name=shared_state["hyperparameter_tuning_job_name"],
+    )
+
+    # Delete the created hyperparameter tuning job
+    job_client.delete_hyperparameter_tuning_job(
+        name=shared_state["hyperparameter_tuning_job_name"]
+    )
+
+
+def test_create_hyperparameter_tuning_job_python_package_sample(capsys, shared_state):
+
+    create_hyperparameter_tuning_job_python_package_sample.create_hyperparameter_tuning_job_python_package_sample(
+        project=PROJECT_ID,
+        display_name=DISPLAY_NAME,
+        executor_image_uri=EXECUTOR_IMAGE_URI,
+        package_uri=PACKAGE_URI,
+        python_module=PYTHON_MODULE,
+    )
+
+    out, _ = capsys.readouterr()
+    assert "response" in out
+
+    shared_state["hyperparameter_tuning_job_name"] = helpers.get_name(out)