code: def test_remote_decorator_fields_consistency(
      get_execution_role, session
  ):
      expected_remote_decorator_attributes = {
          "sagemaker_session",
          "environment_variables",
          "image_uri",
          "dependencies",
          "pre_execution_commands",
          "pre_execution_script",
          "include_local_workdir",
          "instance_type",
          "instance_count",
          "volume_size",
          "max_runtime_in_seconds",
          "max_retry_attempts",
          "keep_alive_period_in_seconds",
          "spark_config",
          "job_conda_env",
          "job_name_prefix",
          "encrypt_inter_container_traffic",
          "enable_network_isolation",
          "role",
          "s3_root_uri",
          "s3_kms_key",
          "volume_kms_key",
          "vpc_config",
          "tags",
          "use_spot_instances",
          "max_wait_time_in_seconds",
          "custom_file_filter",
      }
  
      job_settings = _JobSettings(
          image_uri=IMAGE,
          s3_root_uri=S3_URI,
          role=EXECUTION_ROLE_ARN,
          include_local_workdir=True,
          instance_type="ml.m5.large",
          encrypt_inter_container_traffic=True,
      )
      actual_attributes = {
          attribute for attribute, _ in job_settings.__dict__.items()
      }
  
      assert expected_remote_decorator_attributes == actual_attributes
  
imports: from __future__ import absolute_import
  from datetime import datetime
  from typing import Callable
  import pytest
  import json
  from botocore.exceptions import ClientError
  from mock import Mock, patch, call
  from sagemaker.feature_store.feature_processor.feature_scheduler import FeatureProcessorLineageHandler
  from sagemaker.feature_store.feature_processor import FeatureProcessorPipelineEvents, FeatureProcessorPipelineExecutionStatus
  from sagemaker.lineage.context import Context
  from sagemaker.remote_function.spark_config import SparkConfig
  from sagemaker import Session
  from sagemaker.feature_store.feature_processor._enums import FeatureProcessorMode
  from sagemaker.feature_store.feature_processor._constants import FEATURE_PROCESSOR_TAG_KEY, FEATURE_PROCESSOR_TAG_VALUE, EXECUTION_TIME_PIPELINE_PARAMETER_FORMAT, PIPELINE_NAME_MAXIMUM_LENGTH
  from sagemaker.feature_store.feature_processor.feature_scheduler import schedule, to_pipeline, execute, delete_schedule, describe, list_pipelines, put_trigger, enable_trigger, disable_trigger, delete_trigger, _validate_fg_lineage_resources, _validate_pipeline_lineage_resources
  from sagemaker.remote_function.job import _JobSettings, SPARK_APP_SCRIPT_PATH, RUNTIME_SCRIPTS_CHANNEL_NAME, REMOTE_FUNCTION_WORKSPACE, ENTRYPOINT_SCRIPT_NAME, SPARK_CONF_CHANNEL_NAME
  from sagemaker.workflow.parameters import Parameter, ParameterTypeEnum
  from sagemaker.workflow.retry import StepRetryPolicy, StepExceptionTypeEnum, SageMakerJobStepRetryPolicy, SageMakerJobExceptionTypeEnum
  import test_data_helpers
label_desc: Use image node_id 25 for calling a global function with example usage: test_remote_decorator_fields_consistency(get_execution_role, session) without return types