code: def dummy_eval(m, size=(64, 64)):
      "Evaluate `m` on a dummy input of a certain `size`"
      ch_in = in_channels(m)
      x = (
          one_param(m)
          .new(1, ch_in, *size)
          .requires_grad_(False)
          .uniform_(-1.0, 1.0)
      )
      with torch.no_grad():
          return m.eval()(x)
  
imports: from __future__ import annotations
  from ..basics import *
label_desc: Use image node_id 4 for calling a global function with example usage: dummy_eval(m, size) and returns: m