architecture.py 文件源码

def _upscore_layer(bottom, shape, num_classes, name, debug, ksize=4, stride=2):
    strides = [1, stride, stride, 1]
    with tf.variable_scope(name) :
        in_features = bottom.get_shape()[3].value

        if shape is None:
            # Compute shape out of Bottom
            in_shape = bottom.get_shape()

            h = ((in_shape[1] - 1) * stride) + 1
            w = ((in_shape[2] - 1) * stride) + 1
            new_shape = [in_shape[0], h, w, num_classes]
        else:
            new_shape = [shape[0], shape[1], shape[2], num_classes]
        output_shape = tf.pack(new_shape)
        logging.debug("Layer: %s, Fan-in: %d" % (name, in_features))
        f_shape = [ksize, ksize, num_classes, in_features]

        weights = get_deconv_filter(f_shape)
        deconv = tf.nn.conv2d_transpose(bottom, weights, output_shape,
                                        strides=strides, padding='SAME')
        deconv.set_shape(new_shape)
        print('Layer name: %s' % name)
        print('Layer shape: %s' % str(deconv.get_shape()))
        if debug:
            deconv = tf.Print(deconv, [deconv.get_shape()],
                              message='Shape of %s' % name,
                              summarize=4, first_n=1)

        _activation_summary(deconv)
        return deconv