code: def test_create_sagemaker_model_creates_correct_session(
      local_session, session
  ):
      local_session.return_value.sagemaker_config = {}
      session.return_value.sagemaker_config = {}
      model = Model(MODEL_IMAGE, MODEL_DATA)
      model._create_sagemaker_model("local")
      assert model.sagemaker_session == local_session.return_value
  
      model = Model(MODEL_IMAGE, MODEL_DATA)
      model._create_sagemaker_model("ml.m5.xlarge")
      assert model.sagemaker_session == session.return_value
  
imports: from __future__ import absolute_import
  import random
  from unittest.mock import MagicMock
  import pytest
  from mock import Mock, patch
  import sagemaker
  from sagemaker.async_inference import AsyncInferenceConfig
  from sagemaker.model import FrameworkModel, Model
  from sagemaker.huggingface.model import HuggingFaceModel
  from sagemaker.jumpstart.constants import JUMPSTART_GATED_AND_PUBLIC_BUCKET_NAME_SET, JUMPSTART_RESOURCE_BASE_NAME
  from sagemaker.jumpstart.enums import JumpStartTag
  from sagemaker.mxnet.model import MXNetModel
  from sagemaker.pytorch.model import PyTorchModel
  from sagemaker.session_settings import SessionSettings
  from sagemaker.sklearn.model import SKLearnModel
  from sagemaker.tensorflow.model import TensorFlowModel
  from sagemaker.xgboost.model import XGBoostModel
  from sagemaker.enums import EndpointType
  from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements
  from sagemaker.workflow.properties import Properties
  from tests.unit import _test_default_bucket_and_prefix_combinations, DEFAULT_S3_BUCKET_NAME, DEFAULT_S3_OBJECT_KEY_PREFIX_NAME, SAGEMAKER_CONFIG_EDGE_PACKAGING_JOB
label_desc: Use image node_id 19 for calling a global function with example usage: test_create_sagemaker_model_creates_correct_session(local_session, session) without return types