class_docstr: Model allows using pre-trained models.
class_docstr_tok: ["Model","allows","using","pre-trained","models","."]
code: def save(
      save_url, input_name, output_names, image_shape, image_value_range
  ):
      if ":" in input_name:
          raise ValueError(
              "input_name appears to be a tensor (name contains ':') but must be an op."
          )
      if any([":" in name for name in output_names]):
          raise ValueError(
              "output_namess appears to be contain tensor (name contains ':') but must be ops."
          )
  
      metadata = {
          "input_name": input_name,
          "image_shape": image_shape,
          "image_value_range": image_value_range,
      }
  
      graph_def = model_util.frozen_default_graph_def(
          [input_name], output_names
      )
      model_util.infuse_metadata(graph_def, metadata)
      save(graph_def, save_url)
  
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 19 for calling the Model obj's underlying member method code with example usage: obj.save(save_url, input_name, output_names, image_shape, image_value_range) without return types