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: A helper for creating Infer arguments looking at specific dimensions.
docstr_tok: ["A","helper","for","creating","Infer","arguments","looking","at","specific","dimensions","."]
code: def dimension(cls, dim):
      """A helper for creating Infer arguments looking at specific dimensions."""
      return cls(lambda input: input.size()[dim])
  
imports: import functools
  from typing import Tuple
  import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the Infer obj's underlying member method code with example usage: obj.dimension(cls, dim) and returns: cls