code: def forget_xy(t):
      """Ignore sizes of dimensions (1, 2) of a 4d tensor in shape inference.
  
      This allows using smaller input sizes, which create an invalid graph at higher
      layers (for example because a spatial dimension becomes smaller than a conv
      filter) when we only use early parts of it.
      """
      shape = (t.shape[0], None, None, t.shape[3])
      return tf.placeholder_with_default(t, shape)
  
file_path: lucid/lucid/modelzoo/util.py
imports: from __future__ import absolute_import, division, print_function
  import tensorflow
  import json
  from google.protobuf.message import DecodeError
  import logging
  import warnings
  from collections import defaultdict
  from itertools import chain
  from lucid.misc.io import load
  from lucid.misc.io.saving import ClarityJSONEncoder
label_desc: Use image node_id 3 for calling a global function with example usage: forget_xy(t) and returns: tf