class_docstr: In order to be hooked into Gemini's '__torch_function__', adding a view operation to weight and bias. Used in FusedLayerNorm
class_docstr_tok: ["In","order","to","be","hooked","into","Gemini","'s","'__torch_function__","'",",","adding","a","view","operation","to","weight","and","bias",".","Used","in","FusedLayerNorm"]
code: def backward(ctx, grad_output):
      weight, bias = ctx.saved_tensors
      if weight is not None:
          weight = weight.view(weight.shape)
      if bias is not None:
          bias = bias.view(bias.shape)
      return grad_output, None, None
  
imports: import torch
  import torch.distributed
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the HookParameter obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: grad_output,  None,  None