docstr: Training args for Google Vertex AI Training.
docstr_tok: ["Training","args","for","Google","Vertex","AI","Training","."]
code: def _getVertexTrainingArgs(self, pipeline_name):
      """Training args for Google Vertex AI Training."""
      return {
          "project": self._GCP_PROJECT_ID,
          "job_spec": {
              "worker_pool_specs": [
                  {
                      "machine_spec": {"machine_type": "e2-standard-8"},
                      "replica_count": 1,
                      "container_spec": {
                          "image_uri": self.container_image
                      },
                  }
              ]
          },
      }
  
imports: import os
  import absl
  from googleapiclient import discovery
  from googleapiclient import errors
  import tensorflow
  from tfx import v1
  from tfx.components.pusher.component import Pusher
  from tfx.components.trainer.component import Trainer
  from tfx.dsl.components.base import executor_spec
  from tfx.dsl.components.common import importer
  from tfx.dsl.io import fileio
  from tfx.extensions.google_cloud_ai_platform import constants
  from tfx.extensions.google_cloud_ai_platform import runner
  from tfx.extensions.google_cloud_ai_platform.pusher import executor
  from tfx.extensions.google_cloud_ai_platform.trainer import executor
  from tfx.extensions.google_cloud_ai_platform.tuner import component
  from tfx.extensions.google_cloud_ai_platform.tuner import executor
  from tfx.extensions.google_cloud_big_query.pusher import executor
  from tfx.orchestration import test_utils
  from tfx.orchestration.kubeflow import test_utils
  from tfx.proto import trainer_pb2
  from tfx.proto import tuner_pb2
  from tfx.types import standard_artifacts
  from tfx.utils import path_utils
  from tfx.utils import telemetry_utils
label_desc: Use image node_id 4 for calling the KubeflowGCPIntegrationTest obj's underlying member method code with example usage: obj._getVertexTrainingArgs(pipeline_name) and returns: dict