readers.py 文件源码

def resize_axis(tensor, axis, new_size, fill_value=0):
  """Truncates or pads a tensor to new_size on on a given axis.

  Truncate or extend tensor such that tensor.shape[axis] == new_size. If the
  size increases, the padding will be performed at the end, using fill_value.

  Args:
    tensor: The tensor to be resized.
    axis: An integer representing the dimension to be sliced.
    new_size: An integer or 0d tensor representing the new value for
      tensor.shape[axis].
    fill_value: Value to use to fill any new entries in the tensor. Will be
      cast to the type of tensor.

  Returns:
    The resized tensor.
  """
  tensor = tf.convert_to_tensor(tensor)
  shape = tf.unstack(tf.shape(tensor))

  pad_shape = shape[:]
  pad_shape[axis] = tf.maximum(0, new_size - shape[axis])

  shape[axis] = tf.minimum(shape[axis], new_size)
  shape = tf.stack(shape)

  resized = tf.concat([
      tf.slice(tensor, tf.zeros_like(shape), shape),
      tf.fill(tf.stack(pad_shape), tf.cast(fill_value, tensor.dtype))
  ], axis)

  # Update shape.
  new_shape = tensor.get_shape().as_list()  # A copy is being made.
  new_shape[axis] = new_size
  resized.set_shape(new_shape)
  return resized