code: def _create_train_job(
      tf_version,
      horovod=False,
      ps=False,
      py_version="py2",
      smdataparallel=False,
  ):
      conf = {
          "image_uri": _image_uri(tf_version, py_version),
          "input_mode": "File",
          "input_config": [
              {
                  "ChannelName": "training",
                  "DataSource": {
                      "S3DataSource": {
                          "S3DataDistributionType": "FullyReplicated",
                          "S3DataType": "S3Prefix",
                      }
                  },
              }
          ],
          "role": ROLE,
          "job_name": JOB_NAME,
          "output_config": {
              "S3OutputPath": "s3://{}/".format(BUCKET_NAME)
          },
          "resource_config": {
              "InstanceType": "ml.c4.4xlarge",
              "InstanceCount": 1,
              "VolumeSizeInGB": 30,
          },
          "hyperparameters": _hyperparameters(horovod, smdataparallel),
          "stop_condition": {"MaxRuntimeInSeconds": 24 * 60 * 60},
          "retry_strategy": None,
          "tags": None,
          "vpc_config": None,
          "metric_definitions": None,
          "environment": None,
          "experiment_config": None,
          "profiler_config": {
              "DisableProfiler": False,
              "S3OutputPath": "s3://{}/".format(BUCKET_NAME),
          },
      }
  
      if not ps:
          conf["debugger_hook_config"] = {
              "CollectionConfigurations": [],
              "S3OutputPath": "s3://{}/".format(BUCKET_NAME),
          }
  
      return conf
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  from mock import patch, Mock, MagicMock
  from packaging import version
  import pytest
  from sagemaker.estimator import _TrainingJob
  from sagemaker.session_settings import SessionSettings
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.workflow.parameters import ParameterString, ParameterBoolean
  from tests.unit import DATA_DIR
label_desc: Use image node_id 4 for calling a global function with example usage: _create_train_job(tf_version, horovod, ps, py_version, smdataparallel) and returns: conf