code: def _no_sync_in_gradient_accumulation(self):
      return False
  
file_path: transformers/src/transformers/sagemaker/training_args_sm.py
imports: import importlib.util
  import json
  import os
  import warnings
  from dataclasses import dataclass, field
  import torch
  from ..training_args import TrainingArguments
  from ..utils import cached_property, is_sagemaker_dp_enabled, logging
label_desc: Use image node_id 5 for calling the SageMakerTrainingArguments obj's underlying member method code with example usage: obj._no_sync_in_gradient_accumulation() and returns: False