text: # 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_training_pipeline_video_object_tracking_sample]
  from google.cloud import aiplatform
  from google.cloud.aiplatform.schema import trainingjob
  
  
  def create_training_pipeline_video_object_tracking_sample(
      project: str,
      display_name: str,
      dataset_id: str,
      model_display_name: str,
      location: str = "us-central1",
      api_endpoint: str = "us-central1-aiplatform.googleapis.com",
  ):
      # The AI Platform services require regional API endpoints.
      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.PipelineServiceClient(client_options=client_options)
      training_task_inputs_object = trainingjob.definition.AutoMlVideoObjectTrackingInputs(
          model_type="CLOUD"
      )
      training_task_inputs = training_task_inputs_object.to_value()
  
      training_pipeline = {
          "display_name": display_name,
          "training_task_definition": "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_video_object_tracking_1.0.0.yaml",
          "training_task_inputs": training_task_inputs,
          "input_data_config": {"dataset_id": dataset_id},
          "model_to_upload": {"display_name": model_display_name},
      }
      parent = f"projects/{project}/locations/{location}"
      response = client.create_training_pipeline(
          parent=parent, training_pipeline=training_pipeline
      )
      print("response:", response)
  
  
  # [END aiplatform_create_training_pipeline_video_object_tracking_sample]
  