docstr: Training args for Google CAIP Training.
docstr_tok: ["Training","args","for","Google","CAIP","Training","."]
code: def _getCaipTrainingArgs(self, pipeline_name):
      """Training args for Google CAIP Training."""
      return {
          "project": self._GCP_PROJECT_ID,
          "region": self._GCP_REGION,
          "jobDir": os.path.join(
              self._pipeline_root(pipeline_name), "tmp"
          ),
          "masterConfig": {
              "imageUri": 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 2 for calling the KubeflowGCPIntegrationTest obj's underlying member method code with example usage: obj._getCaipTrainingArgs(pipeline_name) and returns: dict