code: def test_create_model_with_custom_image(
      name_from_base, sagemaker_session
  ):
      container_log_level = '"logging.INFO"'
      source_dir = "s3://mybucket/source"
      custom_image = "mxnet:2.0"
      base_job_name = "job"
  
      mx = MXNet(
          entry_point=SCRIPT_NAME,
          source_dir=source_dir,
          framework_version="2.0",
          py_version="py3",
          role=ROLE,
          sagemaker_session=sagemaker_session,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          image_uri=custom_image,
          container_log_level=container_log_level,
          base_job_name=base_job_name,
      )
  
      mx.fit(inputs="s3://mybucket/train", job_name="new_name")
  
      model_name = "model_name"
      name_from_base.return_value = model_name
      model = mx.create_model()
  
      assert model.sagemaker_session == sagemaker_session
      assert model.image_uri == custom_image
      assert model.entry_point == SCRIPT_NAME
      assert model.role == ROLE
      assert model.name == model_name
      assert model.container_log_level == container_log_level
      assert model.source_dir == source_dir
  
      name_from_base.assert_called_with(base_job_name)
  
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 11 for calling a global function with example usage: test_create_model_with_custom_image(name_from_base, sagemaker_session) without return types