feat(components): Google - AutoML - Added the Deploy model component (#4520)

components/gcp/automl/deploy_model/component.py

@@ -0,0 +1,40 @@
+from typing import NamedTuple
+from kfp.components import create_component_from_func
+
+
+def automl_deploy_model(
+    model_path: str,
+) -> NamedTuple('Outputs', [
+    ('model_path', str),
+]):
+    """Deploys a trained model.
+
+    Args:
+        model_path: The resource name of the model to export. Format: 'projects/<project>/locations/<location>/models/<model>'
+
+    Annotations:
+        author: Alexey Volkov <alexey.volkov@ark-kun.com>
+    """
+    from google.cloud import automl
+    client = automl.AutoMlClient()
+    response = client.deploy_model(
+        name=model_path,
+    )
+    print('Operation started:')
+    print(response.operation)
+    result = response.result()
+    metadata = response.metadata
+    print('Operation finished:')
+    print(metadata)
+    return (model_path, )
+
+
+if __name__ == '__main__':
+    automl_deploy_model_op = create_component_from_func(
+        automl_deploy_model,
+        output_component_file='component.yaml',
+        base_image='python:3.8',
+        packages_to_install=[
+            'google-cloud-automl==2.0.0',
+        ]
+    )

components/gcp/automl/deploy_model/component.yaml

@@ -0,0 +1,83 @@
+name: Automl deploy model
+description: |-
+  Deploys a trained model.
+
+      Args:
+          model_path: The resource name of the model to export. Format: 'projects/<project>/locations/<location>/models/<model>'
+
+      Annotations:
+          author: Alexey Volkov <alexey.volkov@ark-kun.com>
+inputs:
+- {name: model_path, type: String}
+outputs:
+- {name: model_path, type: String}
+implementation:
+  container:
+    image: python:3.8
+    command:
+    - sh
+    - -c
+    - (PIP_DISABLE_PIP_VERSION_CHECK=1 python3 -m pip install --quiet --no-warn-script-location
+      'google-cloud-automl==2.0.0' || PIP_DISABLE_PIP_VERSION_CHECK=1 python3 -m pip
+      install --quiet --no-warn-script-location 'google-cloud-automl==2.0.0' --user)
+      && "$0" "$@"
+    - python3
+    - -u
+    - -c
+    - |
+      def automl_deploy_model(
+          model_path,
+      ):
+          """Deploys a trained model.
+
+          Args:
+              model_path: The resource name of the model to export. Format: 'projects/<project>/locations/<location>/models/<model>'
+
+          Annotations:
+              author: Alexey Volkov <alexey.volkov@ark-kun.com>
+          """
+          from google.cloud import automl
+          client = automl.AutoMlClient()
+          response = client.deploy_model(
+              name=model_path,
+          )
+          print('Operation started:')
+          print(response.operation)
+          result = response.result()
+          metadata = response.metadata
+          print('Operation finished:')
+          print(metadata)
+          return (model_path, )
+
+      def _serialize_str(str_value: str) -> str:
+          if not isinstance(str_value, str):
+              raise TypeError('Value "{}" has type "{}" instead of str.'.format(str(str_value), str(type(str_value))))
+          return str_value
+
+      import argparse
+      _parser = argparse.ArgumentParser(prog='Automl deploy model', description="Deploys a trained model.\n\n    Args:\n        model_path: The resource name of the model to export. Format: 'projects/<project>/locations/<location>/models/<model>'\n\n    Annotations:\n        author: Alexey Volkov <alexey.volkov@ark-kun.com>")
+      _parser.add_argument("--model-path", dest="model_path", type=str, required=True, default=argparse.SUPPRESS)
+      _parser.add_argument("----output-paths", dest="_output_paths", type=str, nargs=1)
+      _parsed_args = vars(_parser.parse_args())
+      _output_files = _parsed_args.pop("_output_paths", [])
+
+      _outputs = automl_deploy_model(**_parsed_args)
+
+      _output_serializers = [
+          _serialize_str,
+
+      ]
+
+      import os
+      for idx, output_file in enumerate(_output_files):
+          try:
+              os.makedirs(os.path.dirname(output_file))
+          except OSError:
+              pass
+          with open(output_file, 'w') as f:
+              f.write(_output_serializers[idx](_outputs[idx]))
+    args:
+    - --model-path
+    - {inputValue: model_path}
+    - '----output-paths'
+    - {outputPath: model_path}