dags/solutions_team/configs/tensorflow/solutionsteam_tf_nightly_supported_config.py [192:220]:
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    tpu_version: TpuVersion,
    tpu_cores: int,
    tpu_zone: str,
    time_out_in_min: int,
    bottom_mlp: List[int],
    embedding_dim: int,
    train_steps: int,
    extraFlags: str = "",
    project_name: str = Project.CLOUD_ML_AUTO_SOLUTIONS.value,
    runtime_version: str = RuntimeVersion.TPU_VM_TF_NIGHTLY.value,
    is_pod: bool = False,
    is_pjrt: bool = True,
    criteo_dir: str = gcs_bucket.CRITEO_DIR,
    network: str = "default",
    subnetwork: str = "default",
    global_batch_size=16384,
):
  job_gcp_config = gcp_config.GCPConfig(
      project_name=project_name,
      zone=tpu_zone,
      dataset_name=metric_config.DatasetOption.XLML_DATASET,
  )

  # Add default_var to pass DAG check
  # TODO(ranran): replace Variable.get() to XCOM when it applies
  test_name = "tf_dlrm_criteo"
  benchmark_id = f"{test_name}-v{tpu_version.value}-{tpu_cores}"
  tpu_name = Variable.get(benchmark_id, default_var=None) if is_pod else "local"
  is_v5p = tpu_version == TpuVersion.V5P
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dags/solutions_team/configs/tensorflow/solutionsteam_tf_nightly_supported_config.py [364:392]:
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    tpu_version: TpuVersion,
    tpu_cores: int,
    tpu_zone: str,
    time_out_in_min: int,
    bottom_mlp: List[int],
    embedding_dim: int,
    train_steps: int,
    extraFlags: str = "",
    project_name: str = Project.CLOUD_ML_AUTO_SOLUTIONS.value,
    runtime_version: str = RuntimeVersion.TPU_VM_TF_NIGHTLY.value,
    is_pod: bool = False,
    is_pjrt: bool = True,
    criteo_dir: str = gcs_bucket.CRITEO_DIR,
    network: str = "default",
    subnetwork: str = "default",
    global_batch_size=16384,
):
  job_gcp_config = gcp_config.GCPConfig(
      project_name=project_name,
      zone=tpu_zone,
      dataset_name=metric_config.DatasetOption.XLML_DATASET,
  )

  # Add default_var to pass DAG check
  # TODO(ranran): replace Variable.get() to XCOM when it applies
  test_name = "tf_dlrm_criteo"
  benchmark_id = f"{test_name}-v{tpu_version.value}-{tpu_cores}"
  tpu_name = Variable.get(benchmark_id, default_var=None) if is_pod else "local"
  is_v5p = tpu_version == TpuVersion.V5P
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