custom_layers.py 文件源码

def pad2d(inputs,
          pad=(0, 0),
          mode='CONSTANT',
          data_format='NHWC',
          trainable=True,
          scope=None):
    """2D Padding layer, adding a symmetric padding to H and W dimensions.

    Aims to mimic padding in Caffe and MXNet, helping the port of models to
    TensorFlow. Tries to follow the naming convention of `tf.contrib.layers`.

    Args:
      inputs: 4D input Tensor;
      pad: 2-Tuple with padding values for H and W dimensions;
      mode: Padding mode. C.f. `tf.pad`
      data_format:  NHWC or NCHW data format.
    """
    with tf.name_scope(scope, 'pad2d', [inputs]):
        # Padding shape.
        if data_format == 'NHWC':
            paddings = [[0, 0], [pad[0], pad[0]], [pad[1], pad[1]], [0, 0]]
        elif data_format == 'NCHW':
            paddings = [[0, 0], [0, 0], [pad[0], pad[0]], [pad[1], pad[1]]]
        net = tf.pad(inputs, paddings, mode=mode)
        return net