class_docstr: A ComptimeVar represents a Python value, at some particular point
  in time, in the Python code we are symbolically evaluating with
  torchdynamo.  This must be distinguished from a runtime value, as
  at compile-time there are some properties of the variable we
  do not know (for example, if the ComptimeVar represents a Tensor,
  we only know metadata about the tensor; we do NOT know what the
  actual data in the Tensor is.)
docstr: Returns the size of the tensor (if dim is None) or the size
  at the dimension dim.  The returned size may be a SymInt.
docstr_tok: ["Returns","the","size","of","the","tensor","(","if","dim","is","None",")","or","the","size","at","the","dimension","dim",".","The","returned","size","may","be","a","SymInt","."]
code: def size(self, dim: Optional[int] = None) -> Union[int, torch.SymInt]:
      """
      Returns the size of the tensor (if dim is None) or the size
      at the dimension dim.  The returned size may be a SymInt.
      """
      return self.as_fake().size(dim)
  
imports: import builtins
  import dis
  import traceback
  from typing import Optional, Union
  import torch
  from .exc import unimplemented
label_desc: Use image node_id 5 for calling the ComptimeVar obj's underlying member method code with example usage: obj.size(dim) and returns: self