code: def _batch_assert(
      status, ds_config, batch, micro_batch, gas, success
  ):
      if not success:
          assert not status
          print("Failed but All is well")
          return
  
      assert ds_config.train_batch_size == batch
      assert ds_config.train_micro_batch_size_per_gpu == micro_batch
      assert ds_config.gradient_accumulation_steps == gas
      print("All is well")
  
imports: import torch
  import pytest
  import json
  import argparse
  from deepspeed.runtime.zero.config import DeepSpeedZeroConfig
  from unit.common import DistributedTest, get_test_path
  from unit.simple_model import SimpleModel, create_config_from_dict, random_dataloader
  import deepspeed.comm
  import deepspeed
  from deepspeed.runtime.config import DeepSpeedConfig, get_bfloat16_enabled
label_desc: Use image node_id 5 for calling a global function with example usage: _batch_assert(status, ds_config, batch, micro_batch, gas, success) without return types