transformer_net.py 文件源码

def conv_layer(in_, nb_filter, filter_length, subsample=1, upsample=1, only_conv=False):
    if upsample != 1:
        out = UpSampling2D(size=(upsample, upsample))(in_)
    else:
        out = in_
    padding = int(np.floor(filter_length / 2))
    out = ReflectPadding2D((padding, padding))(out)
    out = Conv2D(nb_filter, filter_length, filter_length, subsample=(subsample, subsample), border_mode="valid")(out)
    if not only_conv:
        out = InstanceNormalization()(out)
        out = Activation("relu")(out)
    return out