feat: Migrate sample and sample tests - Batch 3 of 5 (#13)

* chore: release 0.2.0

* Init samples and sample tests - Batch 3

* chore: release 0.2.0

* Address reviewer comments - 3 of 5

* Add two extra samples + tests

* Revert Changelog to pre-release

* Update tabular + GAPIC namespace (B3/5)

* Sync with private repo (3/5)

* Add UUID to export_model sample test

* remove unused variables

* add no-arg wrapper function to initialize user inputs

* pass environment variables for fixed resources

* refactor print statement

* add no-arg wrapper function to initialize user inputs

* add no-arg wrapper functions to all samples

* add no-arg wrapper function

Co-authored-by: release-please[bot] <55107282+release-please[bot]@users.noreply.github.com>
Co-authored-by: Bu Sun Kim <8822365+busunkim96@users.noreply.github.com>
Co-authored-by: Ariana Bray <aribray@google.com>

samples/cancel_training_pipeline_sample.py

@@ -15,6 +15,12 @@
 # [START aiplatform_cancel_training_pipeline_sample]
 from google.cloud import aiplatform
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    training_pipeline_id = "YOUR-TRAINING_PIPELINE_ID"
+    cancel_training_pipeline_sample(project, training_pipeline_id)
+
 
 def cancel_training_pipeline_sample(
     project: str, training_pipeline_id: str, location: str = "us-central1"

samples/create_batch_prediction_job_video_classification_sample.py

@@ -17,6 +17,15 @@
 from google.protobuf import json_format
 from google.protobuf.struct_pb2 import Value
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    model_name = "YOUR-MODEL-NAME"
+    gcs_source_uri = "YOUR-GCS-SOURCE-URI"
+    gcs_destination_output_uri_prefix = "YOUR-GCS-DESTINATION-OUTPUT-URI-PREFIX"
+    create_batch_prediction_job_video_classification_sample(project, display_name, model_name, gcs_source_uri, gcs_destination_output_uri_prefix)
+
 
 def create_batch_prediction_job_video_classification_sample(
     project: str,

samples/create_batch_prediction_job_video_object_tracking_sample.py

@@ -17,6 +17,15 @@
 from google.protobuf import json_format
 from google.protobuf.struct_pb2 import Value
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    model_name = "YOUR-MODEL-NAME"
+    gcs_source_uri = "YOUR-GCS-SOURCE-URI"
+    gcs_destination_output_uri_prefix = "YOUR-GCS-DESTINATION-OUTPUT-URI-PREFIX"
+    create_batch_prediction_job_video_object_tracking_sample(project, display_name, model_name, gcs_source_uri, gcs_destination_output_uri_prefix)
+
 
 def create_batch_prediction_job_video_object_tracking_sample(
     project: str,

samples/create_custom_job_sample.py

@@ -0,0 +1,64 @@
+# 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_custom_job_sample]
+from google.cloud import aiplatform
+
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    display_name = "YOUR-DISPLAY-NAME"
+    container_image_uri = "YOUR-CONTAINER-IMAGE-URI"
+    project = "YOUR-PROJECT"
+    create_custom_job_sample(display_name, container_image_uri, project)
+
+
+def create_custom_job_sample(display_name: str, container_image_uri: str, project: str):
+    client_options = {"api_endpoint": "us-central1-aiplatform.googleapis.com"}
+    # 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)
+    location = "us-central1"
+    parent = f"projects/{project}/locations/{location}"
+    )
+    custom_job = {
+        "display_name": display_name,
+        "job_spec": {
+            "worker_pool_specs": [
+                {
+                    "machine_spec": {
+                        "machine_type": "n1-standard-4",
+                        "accelerator_type": aiplatform.gapic.AcceleratorType.NVIDIA_TESLA_K80,
+                        "accelerator_count": 1,
+                    },
+                    "replica_count": 1,
+                    "container_spec": {
+                        "image_uri": container_image_uri,
+                        "command": [],
+                        "args": [],
+                    },
+                }
+            ]
+        },
+    }
+    response = client.create_custom_job(parent=parent, custom_job=custom_job)
+    print("response")
+    print(" name:", response.name)
+    print(" display_name:", response.display_name)
+    print(" state:", response.state)
+    print(" start_time:", response.start_time)
+    print(" end_time:", response.end_time)
+    print(" labels:", response.labels)
+
+
+# [END aiplatform_create_custom_job_sample]

samples/create_data_labeling_job_images_sample.py

@@ -17,6 +17,15 @@
 from google.protobuf import json_format
 from google.protobuf.struct_pb2 import Value
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    dataset = "YOUR-DATASET"
+    instruction_uri = "YOUR-INSTRUCTION-URI"
+    annotation_spec = "YOUR-ANNOTATION-SPEC"
+    create_data_labeling_job_images_sample(project, display_name, dataset, instruction_uri, annotation_spec)
+
 
 def create_data_labeling_job_images_sample(
     project: str,

samples/create_data_labeling_job_sample.py

@@ -17,6 +17,16 @@
 from google.protobuf import json_format
 from google.protobuf.struct_pb2 import Value
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    dataset_name = "YOUR-DATASET-NAME"
+    instruction_uri = "YOUR-INSTRUCTION-URI"
+    inputs_schema_uri = "YOUR-INPUTS-SCHEMA-URI"
+    annotation_spec = "YOUR-ANNOTATION-SPEC"
+    create_data_labeling_job_sample(project, display_name, dataset_name, instruction_uri, inputs_schema_uri, annotation_spec)
+
 
 def create_data_labeling_job_sample(
     project: str,

samples/create_data_labeling_job_video_sample.py

@@ -18,6 +18,16 @@
 from google.protobuf.struct_pb2 import Value
 
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    dataset = "YOUR-DATASET"
+    instruction_uri = "YOUR-INSTRUCTION-URI"
+    annotation_spec = "YOUR-ANNOTATION-SPEC"
+    create_data_labeling_job_video_sample(project, display_name, dataset, instruction_uri, annotation_spec)
+
+
 def create_data_labeling_job_video_sample(
     project: str,
     display_name: str,

samples/create_dataset_image_sample.py

@@ -15,6 +15,12 @@
 # [START aiplatform_create_dataset_image_sample]
 from google.cloud import aiplatform
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    create_dataset_image_sample(project, display_name)
+
 
 def create_dataset_image_sample(
     project: str, display_name: str, location: str = "us-central1", timeout: int = 300

samples/create_dataset_sample.py

@@ -16,12 +16,20 @@
 from google.cloud import aiplatform
 
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    metadata_schema_uri = "YOUR-METADATA-SCHEMA-URI"
+    create_dataset_sample(project, display_name, metadata_schema_uri)
+
+
 def create_dataset_sample(
     project: str,
     display_name: str,
     metadata_schema_uri: str,
     location: str = "us-central1",
-    timeout: int = 300,
+    timeout: int = 300
 ):
     client_options = {"api_endpoint": "us-central1-aiplatform.googleapis.com"}
     # Initialize client that will be used to create and send requests.

samples/create_dataset_tabular_bigquery_sample.py

@@ -18,6 +18,14 @@
 from google.protobuf.struct_pb2 import Value
 
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    bigquery_uri = "YOUR-BIGQUERY-URI"
+    create_dataset_tabular_bigquery_sample(project, display_name, bigquery_uri)
+
+
 def create_dataset_tabular_bigquery_sample(
     project: str,
     display_name: str,

samples/create_dataset_tabular_gcs_sample.py

@@ -17,6 +17,13 @@
 from google.protobuf import json_format
 from google.protobuf.struct_pb2 import Value
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    gcs_uri = "YOUR-GCS-URI"
+    create_dataset_tabular_gcs_sample(project, display_name, gcs_uri)
+
 
 def create_dataset_tabular_gcs_sample(
     project: str,

samples/create_dataset_text_sample.py

@@ -16,6 +16,13 @@
 from google.cloud import aiplatform
 
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    create_dataset_text_sample(project, display_name)
+
+
 def create_dataset_text_sample(
     project: str, display_name: str, location: str = "us-central1", timeout: int = 300
 ):

samples/create_dataset_video_sample.py

@@ -15,6 +15,12 @@
 # [START aiplatform_create_dataset_video_sample]
 from google.cloud import aiplatform
 
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT"
+    display_name = "YOUR-DISPLAY-NAME"
+    create_dataset_video_sample(project, display_name, location, timeout)
+
 
 def create_dataset_video_sample(
     project: str, display_name: str, location: str = "us-central1", timeout: int = 300

samples/create_hyperparameter_tuning_job_sample.py

@@ -0,0 +1,95 @@
+# 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_sample]
+from google.cloud import aiplatform
+
+
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    display_name = "YOUR-DISPLAY-NAME"
+    container_image_uri = "YOUR-CONTAINER-IMAGE-URI"
+    project = "YOUR-PROJECT"
+    create_hyperparameter_tuning_job_sample(display_name, container_image_uri, project)
+
+
+def create_hyperparameter_tuning_job_sample(
+    display_name: str, container_image_uri: str, project: str
+):
+    client_options = {"api_endpoint": "us-central1-aiplatform.googleapis.com"}
+    # 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)
+    location = "us-central1"
+    parent = "projects/{project}/locations/{location}".format(
+        project=project, location=location
+    )
+    hyperparameter_tuning_job = {
+        "display_name": display_name,
+        "max_trial_count": 2,
+        "parallel_trial_count": 1,
+        "max_failed_trial_count": 1,
+        "study_spec": {
+            "metrics": [
+                {
+                    "metric_id": "accuracy",
+                    "goal": aiplatform.gapic.StudySpec.MetricSpec.GoalType.MAXIMIZE,
+                }
+            ],
+            "parameters": [
+                {
+                    # Learning rate.
+                    "parameter_id": "lr",
+                    "double_value_spec": {"min_value": 0.001, "max_value": 0.1},
+                },
+            ],
+        },
+        "trial_job_spec": {
+            "worker_pool_specs": [
+                {
+                    "machine_spec": {
+                        "machine_type": "n1-standard-4",
+                        "accelerator_type": aiplatform.gapic.AcceleratorType.NVIDIA_TESLA_K80,
+                        "accelerator_count": 1,
+                    },
+                    "replica_count": 1,
+                    "container_spec": {
+                        "image_uri": container_image_uri,
+                        "command": [],
+                        "args": [],
+                    },
+                }
+            ]
+        },
+    }
+    response = client.create_hyperparameter_tuning_job(
+        parent=parent, hyperparameter_tuning_job=hyperparameter_tuning_job
+    )
+    print("response")
+    print(" name:", response.name)
+    print(" display_name:", response.display_name)
+    print(" max_trial_count:", response.max_trial_count)
+    print(" parallel_trial_count:", response.parallel_trial_count)
+    print(" max_failed_trial_count:", response.max_failed_trial_count)
+    print(" state:", response.state)
+    print(" start_time:", response.start_time)
+    print(" end_time:", response.end_time)
+    print(" labels:", response.labels)
+    study_spec = response.study_spec
+    trial_job_spec = response.trial_job_spec
+    trials = response.trials
+    error = response.error
+
+
+# [END aiplatform_create_hyperparameter_tuning_job_sample]

samples/export_model_sample.py

@@ -0,0 +1,47 @@
+# 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_export_model_sample]
+from google.cloud import aiplatform
+
+def run_sample():
+    # TODO(dev): replace these variables to run the code
+    project = "YOUR-PROJECT-ID"
+    model_id = "YOUR-MODEL-ID"
+    gcs_destination_output_uri_prefix = "YOUR-GCS-URI-PREFIX"
+    export_model_sample(gcs_destination_output_uri_prefix, project, model_id)
+
+
+def export_model_sample(
+    project: str,
+    model_id: str,
+    gcs_destination_output_uri_prefix: str,
+    location: str = "us-central1",
+    timeout: int = 300,
+):
+    client_options = {"api_endpoint": "us-central1-aiplatform.googleapis.com"}
+    # 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.ModelServiceClient(client_options=client_options)
+    output_config = {
+        "artifact_destination": {"output_uri_prefix": gcs_destination_output_uri_prefix}
+    }
+    name = client.model_path(project=project, location=location, model=model_id)
+    response = client.export_model(name=name, output_config=output_config)
+    print("Long running operation:", response.operation.name)
+    export_model_response = response.result(timeout=timeout)
+    print("export_model_response:", export_model_response)
+
+
+# [END aiplatform_export_model_sample]