fractal_block.py 文件源码

def fractal_template(inputs,
                     num_columns,
                     block_fn,
                     block_asc,
                     joined=True,
                     is_training=True,
                     reuse=False,
                     scope=None):
  """Template for making fractal blocks.

  Given a function and a corresponding arg_scope `fractal_template`
  will build a truncated fractal with `num_columns` columns.

  Args:
    inputs: a 4-D tensor  `[batch_size, height, width, channels]`.
    num_columns: integer, the columns in the fractal.
    block_fn: function to be called within each fractal.
    block_as: A function that returns argscope for `block_fn`.
    joined: boolean, whether the output columns should be joined.
    reuse: whether or not the layer and its variables should be reused. To be
      able to reuse the layer scope must be given.
    scope: Optional scope for `variable_scope`.
  """

  def fractal_expand(inputs, num_columns, joined):
    '''Recursive Helper Function for making fractal'''
    with block_asc():
      output = lambda cols: join(cols, coin) if joined else cols
      if num_columns == 1:
        return output([block_fn(inputs)])
      left = block_fn(inputs)
      right = fractal_expand(inputs, num_columns-1, joined=True)
      right = fractal_expand(right, num_columns-1, joined=False)
      cols=[left]+right
    return output(cols)

  with tf.variable_op_scope([inputs], scope, 'Fractal',
                            reuse=reuse) as scope:
    coin = coin_flip()
    net=fractal_expand(inputs, num_columns, joined)

  return net