code: def step_model_create(
      pipeline_session,
      role,
  ):
      xgb_model_data_s3 = pipeline_session.upload_data(
          path=os.path.join(
              os.path.join(DATA_DIR, "xgboost_abalone"),
              "xgb_model.tar.gz",
          ),
          key_prefix="integ-test-data/xgboost/model",
      )
  
      xgb_model = XGBoostModel(
          model_data=xgb_model_data_s3,
          framework_version="1.3-1",
          role=role,
          sagemaker_session=pipeline_session,
          entry_point=os.path.join(
              os.path.join(DATA_DIR, "xgboost_abalone"), "inference.py"
          ),
          enable_network_isolation=True,
      )
  
      create_model_step_args = xgb_model.create(
          instance_type="ml.m5.large",
      )
      step_model_create = ModelStep(
          name="MyModel",
          step_args=create_model_step_args,
      )
      return step_model_create
  
imports: from __future__ import absolute_import
  import json
  import logging
  import os
  import pytest
  from tests.integ.sagemaker.workflow.helpers import wait_pipeline_execution
  from sagemaker.clarify import BiasConfig, DataConfig
  from sagemaker.s3 import S3Uploader, S3Downloader
  from sagemaker.workflow.clarify_check_step import DataBiasCheckConfig
  from sagemaker.workflow.monitor_batch_transform_step import MonitorBatchTransformStep
  from sagemaker.workflow.model_step import ModelStep
  from sagemaker.workflow.parameters import ParameterString
  from tests.integ import DATA_DIR
  from sagemaker.model_monitor import DatasetFormat, Statistics, Constraints
  from sagemaker.xgboost import XGBoostModel
  from sagemaker.transformer import Transformer
  from sagemaker import get_execution_role, utils
  from sagemaker.workflow.pipeline import Pipeline
  from sagemaker.workflow.check_job_config import CheckJobConfig
  from tests.integ.retry import retries
  from sagemaker.workflow.quality_check_step import DataQualityCheckConfig, ModelQualityCheckConfig
label_desc: Use image node_id 17 for calling a global function with example usage: step_model_create(pipeline_session, role) and returns: step_model_create