code: def test_debug_compiler_config(
      self,
      time,
      name_from_base,
      sagemaker_session,
      tensorflow_training_version,
      tensorflow_training_py_version,
  ):
      compiler_config = TrainingCompilerConfig(debug=True)
  
      tf = TensorFlow(
          py_version=tensorflow_training_py_version,
          entry_point=SCRIPT_PATH,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          instance_count=INSTANCE_COUNT,
          instance_type=INSTANCE_TYPE,
          framework_version=tensorflow_training_version,
          enable_sagemaker_metrics=False,
          compiler_config=compiler_config,
      )
  
      inputs = "s3://mybucket/train"
  
      tf.fit(inputs=inputs, experiment_config=EXPERIMENT_CONFIG)
  
      sagemaker_call_names = [
          c[0] for c in sagemaker_session.method_calls
      ]
      assert sagemaker_call_names == ["train", "logs_for_job"]
      boto_call_names = [
          c[0] for c in sagemaker_session.boto_session.method_calls
      ]
      assert boto_call_names == ["resource"]
  
      expected_train_args = _create_train_job(
          tensorflow_training_version,
          INSTANCE_TYPE,
          compiler_config,
          tensorflow_training_py_version,
      )
      expected_train_args["input_config"][0]["DataSource"][
          "S3DataSource"
      ]["S3Uri"] = inputs
      expected_train_args["enable_sagemaker_metrics"] = False
      expected_train_args["hyperparameters"][
          TrainingCompilerConfig.HP_ENABLE_COMPILER
      ] = json.dumps(True)
      expected_train_args["hyperparameters"][
          TrainingCompilerConfig.HP_ENABLE_DEBUG
      ] = json.dumps(True)
  
      actual_train_args = sagemaker_session.method_calls[0][2]
      assert (
          actual_train_args == expected_train_args
      ), f"{json.dumps(actual_train_args, indent=2)} != {json.dumps(expected_train_args, indent=2)}"
  
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  from packaging import version
  import pytest
  from mock import MagicMock, Mock, patch
  from sagemaker import image_uris
  from sagemaker.session_settings import SessionSettings
  from sagemaker.tensorflow import TensorFlow, TrainingCompilerConfig
  from tests.unit.sagemaker.training_compiler import EC2_GPU_INSTANCE_CLASSES
label_desc: Use image node_id 3 for calling the TestTrainingCompilerConfig obj's underlying member method code with example usage: obj.test_debug_compiler_config(time, name_from_base, sagemaker_session, tensorflow_training_version, tensorflow_training_py_version) without return types