tensorflow_probability/examples/generative_adversarial_network.py
def build_input_pipeline(train_images, batch_size):
  """Build an iterator over training batches."""

  training_dataset = tf.data.Dataset.from_tensor_slices(train_images)
  training_batches = training_dataset.shuffle(
      50000, reshuffle_each_iteration=True).repeat().batch(batch_size)
  training_iterator = tf.compat.v1.data.make_one_shot_iterator(training_batches)
  images = training_iterator.get_next()
  return images
def build_input_pipeline(train_images, batch_size):
  """Build an iterator over training batches."""

  training_dataset = tf.data.Dataset.from_tensor_slices(train_images)
  training_batches = training_dataset.shuffle(
      50000, reshuffle_each_iteration=True).repeat().batch(batch_size)
  training_iterator = tf.compat.v1.data.make_one_shot_iterator(training_batches)
  images = training_iterator.get_next()
  return images
Build an iterator over training batches.