class_docstr: A value which can be inferred from a forward pass. Infer objects should
  be passed as arguments or keyword arguments to Lazy objects; see Lazy
  documentation for more details.
class_docstr_tok: ["A","value","which","can","be","inferred","from","a","forward","pass",".","Infer","objects","should","be","passed","as","arguments","or","keyword","arguments","to","Lazy","objects",";","see","Lazy","documentation","for","more","details","."]
docstr: resolve_fn is called by Lazy on the arguments of the first forward pass
  to the Lazy module, and the Infer object will be replaced in the call by the
  output of this function. It should have the same signature as the
  Lazy-wrapped Module's forward function.
docstr_tok: ["resolve_fn","is","called","by","Lazy","on","the","arguments","of","the","first","forward","pass","to","the","Lazy","module",",","and","the","Infer","object","will","be","replaced","in","the","call","by","the","output","of","this","function",".","It","should","have","the","same","signature","as","the","Lazy-wrapped","Module","'s","forward","function","."]
code: def __init__(self, resolve_fn):
      """resolve_fn is called by Lazy on the arguments of the first forward pass
      to the Lazy module, and the Infer object will be replaced in the call by the
      output of this function. It should have the same signature as the
      Lazy-wrapped Module's forward function."""
      self.resolve = resolve_fn
  
imports: import functools
  from typing import Tuple
  import torch
  from torch import nn
label_desc: Use image node_id 1 to create a new Infer object  with example: obj = Infer(resolve_fn)