code: def _create_compilation_job(input_shape, output_location):
      return {
          "input_model_config": {
              "DataInputConfig": input_shape,
              "Framework": FRAMEWORK.upper(),
              "S3Uri": "s3://m/m.tar.gz",
          },
          "job_name": COMPILATION_JOB_NAME,
          "output_model_config": {
              "S3OutputLocation": output_location,
              "TargetDevice": "ml_c4",
          },
          "role": ROLE,
          "stop_condition": {"MaxRuntimeInSeconds": 900},
          "tags": None,
      }
  
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  import pytest
  from mock import MagicMock, Mock, ANY
  from mock import patch
  from pkg_resources import parse_version
  from sagemaker.fw_utils import UploadedCode
  from sagemaker.drift_check_baselines import DriftCheckBaselines
  from sagemaker.metadata_properties import MetadataProperties
  from sagemaker.model_metrics import FileSource, MetricsSource, ModelMetrics
  from sagemaker.mxnet import defaults
  from sagemaker.mxnet import MXNet
  from sagemaker.mxnet import MXNetPredictor, MXNetModel
  from sagemaker.session_settings import SessionSettings
label_desc: Use image node_id 8 for calling a global function with example usage: _create_compilation_job(input_shape, output_location) and returns: dict