class_docstr: Autograd function to make a viewless tensor.
  
  This function should be used in cases where the computation graph needs
  to be propagated, but we only want a viewless tensor (e.g.,
  ParallelTransformer's hidden_states). Call this function by passing
  'keep_graph = True' to 'make_viewless_tensor()'.
class_docstr_tok: ["Autograd","function","to","make","a","viewless","tensor",".","This","function","should","be","used","in","cases","where","the","computation","graph","needs","to","be","propagated",",","but","we","only","want","a","viewless","tensor","(","e.g.",",","ParallelTransformer","'s","hidden_states",")",".","Call","this","function","by","passing","'keep_graph","=","True","'","to","'make_viewless_tensor","(",")","'","."]
code: def backward(ctx, grad_output):
      return grad_output, None
  
imports: import math
  import operator
  from functools import reduce
  import torch
  from megatron.core import parallel_state
  from megatron.core.dist_checkpointing.mapping import ShardedTensor
label_desc: Use image node_id 2 for calling the MakeViewlessTensor obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: grad_output,  None