generator.py 文件源码

def build_decoder(net):
    net['uconv5_3']= ConvLayer(net['conv5_3'], 512, 3, pad=1)
    print "uconv5_3: {}".format(net['uconv5_3'].output_shape[1:])

    net['uconv5_2'] = ConvLayer(net['uconv5_3'], 512, 3, pad=1)
    print "uconv5_2: {}".format(net['uconv5_2'].output_shape[1:])

    net['uconv5_1'] = ConvLayer(net['uconv5_2'], 512, 3, pad=1)
    print "uconv5_1: {}".format(net['uconv5_1'].output_shape[1:])

    net['upool4'] = Upscale2DLayer(net['uconv5_1'], scale_factor=2)
    print "upool4: {}".format(net['upool4'].output_shape[1:])

    net['uconv4_3'] = ConvLayer(net['upool4'], 512, 3, pad=1)
    print "uconv4_3: {}".format(net['uconv4_3'].output_shape[1:])

    net['uconv4_2'] = ConvLayer(net['uconv4_3'], 512, 3, pad=1)
    print "uconv4_2: {}".format(net['uconv4_2'].output_shape[1:])

    net['uconv4_1'] = ConvLayer(net['uconv4_2'], 512, 3, pad=1)
    print "uconv4_1: {}".format(net['uconv4_1'].output_shape[1:])

    net['upool3'] = Upscale2DLayer(net['uconv4_1'], scale_factor=2)
    print "upool3: {}".format(net['upool3'].output_shape[1:])

    net['uconv3_3'] = ConvLayer(net['upool3'], 256, 3, pad=1)
    print "uconv3_3: {}".format(net['uconv3_3'].output_shape[1:])

    net['uconv3_2'] = ConvLayer(net['uconv3_3'], 256, 3, pad=1)
    print "uconv3_2: {}".format(net['uconv3_2'].output_shape[1:])

    net['uconv3_1'] = ConvLayer(net['uconv3_2'], 256, 3, pad=1)
    print "uconv3_1: {}".format(net['uconv3_1'].output_shape[1:])

    net['upool2'] = Upscale2DLayer(net['uconv3_1'], scale_factor=2)
    print "upool2: {}".format(net['upool2'].output_shape[1:])

    net['uconv2_2'] = ConvLayer(net['upool2'], 128, 3, pad=1)
    print "uconv2_2: {}".format(net['uconv2_2'].output_shape[1:])

    net['uconv2_1'] = ConvLayer(net['uconv2_2'], 128, 3, pad=1)
    print "uconv2_1: {}".format(net['uconv2_1'].output_shape[1:])

    net['upool1'] = Upscale2DLayer(net['uconv2_1'], scale_factor=2)
    print "upool1: {}".format(net['upool1'].output_shape[1:])

    net['uconv1_2'] = ConvLayer(net['upool1'], 64, 3, pad=1,)
    print "uconv1_2: {}".format(net['uconv1_2'].output_shape[1:])

    net['uconv1_1'] = ConvLayer(net['uconv1_2'], 64, 3, pad=1)
    print "uconv1_1: {}".format(net['uconv1_1'].output_shape[1:])

    net['output'] = ConvLayer(net['uconv1_1'], 1, 1, pad=0,nonlinearity=sigmoid)
    print "output: {}".format(net['output'].output_shape[1:])

    return net