code: def _create_train_job(version, py_version):
      return {
          "image_uri": _get_full_cpu_image_uri(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": {
              "sagemaker_program": json.dumps("dummy_script.py"),
              "sagemaker_container_log_level": str(logging.INFO),
              "sagemaker_job_name": json.dumps(JOB_NAME),
              "sagemaker_submit_directory": json.dumps(
                  "s3://{}/{}/source/sourcedir.tar.gz".format(
                      BUCKET_NAME, JOB_NAME
                  )
              ),
              "sagemaker_region": '"us-west-2"',
          },
          "stop_condition": {"MaxRuntimeInSeconds": 24 * 60 * 60},
          "retry_strategy": None,
          "tags": None,
          "vpc_config": None,
          "metric_definitions": None,
          "environment": None,
          "experiment_config": None,
          "debugger_hook_config": {
              "CollectionConfigurations": [],
              "S3OutputPath": "s3://{}/".format(BUCKET_NAME),
          },
          "profiler_config": {
              "DisableProfiler": False,
              "S3OutputPath": "s3://{}/".format(BUCKET_NAME),
          },
      }
  
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  from distutils.util import strtobool
  import pytest
  from mock import MagicMock, Mock, ANY
  from mock import patch
  from sagemaker.chainer import defaults
  from sagemaker.chainer import Chainer
  from sagemaker.chainer import ChainerPredictor, ChainerModel
  from sagemaker.session_settings import SessionSettings
label_desc: Use image node_id 4 for calling a global function with example usage: _create_train_job(version, py_version) and returns: dict