class_docstr: Model allows using pre-trained models.
class_docstr_tok: ["Model","allows","using","pre-trained","models","."]
docstr: Create input tensor.
docstr_tok: ["Create","input","tensor","."]
code: def create_input(self, t_input=None, forget_xy_shape=True):
      """Create input tensor."""
      if t_input is None:
          t_input = tf.placeholder(tf.float32, self.image_shape)
      t_prep_input = t_input
      if len(t_prep_input.shape) == 3:
          t_prep_input = tf.expand_dims(t_prep_input, 0)
      if forget_xy_shape:
          t_prep_input = model_util.forget_xy(t_prep_input)
      if hasattr(self, "is_BGR") and self.is_BGR is True:
          t_prep_input = tf.reverse(t_prep_input, [-1])
      lo, hi = self.image_value_range
      t_prep_input = lo + t_prep_input * (hi - lo)
      return t_input, t_prep_input
  
imports: from __future__ import absolute_import, division, print_function
  from os import path
  import warnings
  import logging
  from itertools import chain
  import tensorflow
  import numpy
  from lucid.modelzoo import util
  from lucid.modelzoo.aligned_activations import get_aligned_activations
  from lucid.modelzoo.get_activations import get_activations
  from lucid.misc.io import load, save
  import lucid.misc.io.showing
label_desc: Use image node_id 14 for calling the Model obj's underlying member method code with example usage: obj.create_input(t_input, forget_xy_shape) and returns: t_input,  t_prep_input