Pooling (supports "LEFT").

def pool(inputs, window_size, pooling_type, padding, strides=(1, 1)):
  """Pooling (supports "LEFT")."""
  with tf.name_scope("pool", values=[inputs]):
    static_shape = inputs.get_shape()
    if not static_shape or len(static_shape) != 4:
      raise ValueError("Inputs to conv must have statically known rank 4.")
    # Add support for left padding.
    if padding == "LEFT":
      assert window_size[0] % 2 == 1 and window_size[1] % 2 == 1
      if len(static_shape) == 3:
        width_padding = 2 * (window_size[1] // 2)
        padding_ = [[0, 0], [width_padding, 0], [0, 0]]
      else:
        height_padding = 2 * (window_size[0] // 2)
        cond_padding = tf.cond(
            tf.equal(shape_list(inputs)[2], 1), lambda: tf.constant(0),
            lambda: tf.constant(2 * (window_size[1] // 2)))
        width_padding = 0 if static_shape[2] == 1 else cond_padding
        padding_ = [[0, 0], [height_padding, 0], [width_padding, 0], [0, 0]]
      inputs = tf.pad(inputs, padding_)
      inputs.set_shape([static_shape[0], None, None, static_shape[3]])
      padding = "VALID"

  return tf.nn.pool(inputs, window_size, pooling_type, padding, strides=strides)