code: def test_create_tf_estimator_w_image_with_framework_profile(
      sagemaker_session,
      tensorflow_inference_version,
      tensorflow_inference_py_version,
      default_framework_profile,
  ):
      image_uri = image_uris.retrieve(
          "tensorflow",
          REGION,
          version=tensorflow_inference_version,
          py_version=tensorflow_inference_py_version,
          instance_type=INSTANCE_TYPE,
          image_scope="inference",
      )
  
      profiler_config = ProfilerConfig(
          framework_profile_params=default_framework_profile
      )
  
      with warnings.catch_warnings(record=True) as warn_list:
          warnings.simplefilter("always")
          tf = TensorFlow(
              entry_point=SCRIPT_PATH,
              role=ROLE,
              sagemaker_session=sagemaker_session,
              instance_count=INSTANCE_COUNT,
              instance_type=INSTANCE_TYPE,
              image_uri=image_uri,
              profiler_config=profiler_config,
          )
  
          framework_version = None
          _, _, image_tag, _ = fw.framework_name_from_image(image_uri)
  
          if image_tag is not None:
              framework_version = fw.framework_version_from_tag(
                  image_tag
              )
  
          if framework_version is not None:
              _check_framework_profile_deprecation_warning(
                  framework_version, tf._framework_name, warn_list
              )
  
imports: from __future__ import absolute_import
  import os
  import pytest
  import re
  import time
  import warnings
  from packaging import version
  from sagemaker import image_uris
  import sagemaker.fw_utils
  from sagemaker.pytorch import PyTorch
  from sagemaker.tensorflow import TensorFlow
  from sagemaker.debugger import get_rule_container_image_uri
  from sagemaker.debugger.profiler_config import FrameworkProfile
  from sagemaker import ProfilerConfig, Profiler
  from sagemaker.debugger.metrics_config import StepRange, TimeRange, DetailedProfilingConfig, DataloaderProfilingConfig, PythonProfilingConfig, HorovodProfilingConfig, SMDataParallelProfilingConfig
  from sagemaker.debugger.profiler_constants import BASE_FOLDER_DEFAULT, CLOSE_FILE_INTERVAL_DEFAULT, FILE_OPEN_FAIL_THRESHOLD_DEFAULT, MAX_FILE_SIZE_DEFAULT, DATALOADER_PROFILING_CONFIG_NAME, DATALOADER_PROFILING_START_STEP_DEFAULT, DETAILED_PROFILING_CONFIG_NAME, DETAILED_PROFILING_START_STEP_DEFAULT, SMDATAPARALLEL_PROFILING_CONFIG_NAME, SMDATAPARALLEL_PROFILING_START_STEP_DEFAULT, HOROVOD_PROFILING_CONFIG_NAME, HOROVOD_PROFILING_START_STEP_DEFAULT, PROFILING_NUM_STEPS_DEFAULT, PYTHON_PROFILING_CONFIG_NAME, PYTHON_PROFILING_NUM_STEPS_DEFAULT, PYTHON_PROFILING_START_STEP_DEFAULT, START_STEP_DEFAULT, DETAIL_PROF_PROCESSING_DEFAULT_INSTANCE_TYPE, DETAIL_PROF_PROCESSING_DEFAULT_VOLUME_SIZE
  from sagemaker.debugger.utils import PythonProfiler, cProfileTimer, ErrorMessages
label_desc: Use image node_id 49 for calling a global function with example usage: test_create_tf_estimator_w_image_with_framework_profile(sagemaker_session, tensorflow_inference_version, tensorflow_inference_py_version, default_framework_profile) without return types