old_contents: # Copyright 2019 DeepMind Technologies Limited and Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     https://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  """Compute image metrics: IS, FID."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import tensorflow_gan as tfgan
  
  
  def get_image_metrics_for_samples(
      real_images, generator, prior, data_processor, num_eval_samples):
    """Compute inception score and FID."""
    max_classifier_batch = 10
    num_batches = num_eval_samples //  max_classifier_batch
  
    def sample_fn(arg):
      del arg
      samples = generator(prior.sample(max_classifier_batch))
      # Ensure data is in [0, 1], as expected by TFGAN.
      # Resizing to appropriate size is done by TFGAN.
      return data_processor.postprocess(samples)
  
    fake_outputs = tfgan.eval.sample_and_run_inception(
        sample_fn,
        sample_inputs=[1.0] * num_batches)  # Dummy inputs.
  
    fake_logits = fake_outputs['logits']
    inception_score = tfgan.eval.classifier_score_from_logits(fake_logits)
  
    real_outputs = tfgan.eval.run_inception(real_images, num_batches=num_batches)
    fid = tfgan.eval.frechet_classifier_distance_from_activations(
        real_outputs['pool_3'], fake_outputs['pool_3'])
  
    return {
        'inception_score': inception_score,
        'fid': fid}
  
new_contents: # Copyright 2019 DeepMind Technologies Limited and Google LLC
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     https://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  """Compute image metrics: IS, FID."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import tensorflow_gan as tfgan
  
  
  def get_image_metrics_for_samples(
      real_images, generator, prior, data_processor, num_eval_samples):
    """Compute inception score and FID."""
    max_classifier_batch = 10
    num_batches = num_eval_samples //  max_classifier_batch
  
    def sample_fn(arg):
      del arg
      samples = generator(prior.sample(max_classifier_batch))
      # Samples must be in [-1, 1], as expected by TFGAN.
      # Resizing to appropriate size is done by TFGAN.
      return samples
  
    fake_outputs = tfgan.eval.sample_and_run_inception(
        sample_fn,
        sample_inputs=[1.0] * num_batches)  # Dummy inputs.
  
    fake_logits = fake_outputs['logits']
    inception_score = tfgan.eval.classifier_score_from_logits(fake_logits)
  
    real_outputs = tfgan.eval.run_inception(
        data_processor.preprocess(real_images), num_batches=num_batches)
    fid = tfgan.eval.frechet_classifier_distance_from_activations(
        real_outputs['pool_3'], fake_outputs['pool_3'])
  
    return {
        'inception_score': inception_score,
        'fid': fid}
  
subject: Fix bug in evaluating FID and IS scores.