code: def forward(ctx, module, pre_backward_function, output):
      ctx.module = module
      if output.requires_grad:
          # TODO SOME TIMES post backward does not seem to be triggered debug in detail
          # Should only cause increase in memory not correctness issue
          # if output.grad_fn.__class__.__name__ == 'ViewBackward':
          #    ctx.view=True
          #    print(f"Warning view tensor for input to module : {module.__class__.__name__}. Backward hooks may not trigger properly")
          # assert len(module.parameters(recurse=False)), "The input tensor to the module is a view, and autograd Function or register_hook is not triggered with view tensors."
          # if module.ds_grads_remaining == 0:
          #    print(f"Before Forward: {ctx.module.__class__.__name__}")
          module.ds_grads_remaining += 1
          ctx.pre_backward_function = pre_backward_function
      output = output.detach()
      return output
  
imports: import sys
  import torch
  from torch.cuda import Stream
  from collections import OrderedDict
  from deepspeed.runtime.utils import see_memory_usage
  from deepspeed.runtime.zero.offload_config import OffloadDeviceEnum
  from deepspeed.runtime.zero.partition_parameters import _init_external_params
  from deepspeed.runtime.zero.partition_parameters import *
  from deepspeed.runtime.zero.partitioned_param_coordinator import PartitionedParameterCoordinator, iter_params
  from deepspeed import comm
label_desc: Use image node_id 1 for calling the PostBackwardFunction obj's underlying member method code with example usage: obj.forward(ctx, module, pre_backward_function, output) and returns: output