code: def test_backward(
      self,
      is_preln,
      use_fp16,
      batch_size,
      hidden_size,
      seq_len,
      heads,
      num_layers,
      atol,
  ):
      # Only run fp16 test cases on devices with FP16 capability.
      if not get_accelerator().is_fp16_supported() and (
          use_fp16 is True or is_preln is False
      ):
          return
  
      ds_config = DeepSpeedTransformerConfig()
      ds_config.layer_id = None
      ds_config.batch_size = batch_size
      ds_config.hidden_size = hidden_size
      ds_config.intermediate_size = hidden_size
      ds_config.heads = heads
      ds_config.attn_dropout_ratio = 0.0
      ds_config.hidden_dropout_ratio = 0.0
      ds_config.num_hidden_layers = num_layers
      ds_config.pre_layer_norm = is_preln
      ds_config.initializer_range = 0.02
      ds_config.fp16 = use_fp16
  
      run_backward(ds_config, seq_len, atol=atol, verbose=True)
  
imports: import numpy
  import torch
  import pytest
  import random
  import copy
  import os
  from torch import nn
  from deepspeed import DeepSpeedTransformerLayer, DeepSpeedTransformerConfig
  from deepspeed.accelerator import get_accelerator
  from unit.modeling import BertConfig, BertLayerNorm, BertEncoder
  from unit.modelingpreln import BertEncoder
  from unit.common import DistributedTest, is_rocm_pytorch
label_desc: Use image node_id 1 for calling the TestCUDABackward obj's underlying member method code with example usage: obj.test_backward(is_preln, use_fp16, batch_size, hidden_size, seq_len, heads, num_layers, atol) without return types