message: Return a classifier score of the same type as the logits.
diff: @@ -297,7 +297,8 @@ def classifier_score(images, classifier_fn, num_batches=1):
  efficiently run them through the classifier network.
  Returns:
  - The classifier score. A floating-point scalar.
  + The classifier score. A floating-point scalar of the same type as the output
  + of `classifier_fn`.
  """
  generated_images_list = array_ops.split(
  images, num_or_size_splits=num_batches)
  @@ -316,7 +317,7 @@ def classifier_score(images, classifier_fn, num_batches=1):
  # Use maximum precision for best results.
  logits_dtype = logits.dtype
  if logits_dtype != dtypes.float64:
  - logits = math_ops.cast(logits, dtypes.float64)
  + logits = math_ops.to_double(logits)
  p = nn_ops.softmax(logits)
  q = math_ops.reduce_mean(p, axis=0)
  @@ -326,7 +327,7 @@ def classifier_score(images, classifier_fn, num_batches=1):
  final_score = math_ops.exp(log_score)
  if logits_dtype != dtypes.float64:
  - final_score = math_ops.cast(final_score, dtypes.float64)
  + final_score = math_ops.cast(final_score, logits_dtype)
  return final_score
  