class_docstr: A backward trigger function.
class_docstr_tok: ["A","backward","trigger","function","."]
docstr: We take a weight tensor and the trigger as inputs and output the weight directly.
docstr_tok: ["We","take","a","weight","tensor","and","the","trigger","as","inputs","and","output","the","weight","directly","."]
code: def forward(ctx: Any, w: torch.Tensor, trigger_tensor: torch.Tensor) -> torch.Tensor:  # type: ignore
      """We take a weight tensor and the trigger as inputs and output the weight directly."""
      if DEBUG and dist.is_initialized() and dist.get_rank() == 0:
          print("DEBUG trigger fwd")
      ctx.save_for_backward(w, trigger_tensor)
      return w
  
imports: from typing import Any, Optional, Tuple
  import torch
  from torch import nn
  import torch.distributed
  import torch.nn.functional
label_desc: Use image node_id 1 for calling the BackwardTriggerFn obj's underlying member method code with example usage: obj.forward(ctx, w, trigger_tensor) and returns: w