CNN.py 文件源码

def predict(self, lnew_data, rnew_data):
        """
        predict for new data
        """
        lconv_out = conv.conv2d(input=lnew_data, filters=self.W)
        rconv_out = conv.conv2d(input=rnew_data, filters=self.W)
        lconv_out_tanh = T.tanh(lconv_out + self.b.dimshuffle('x', 0, 'x', 'x'))
        rconv_out_tanh = T.tanh(rconv_out + self.b.dimshuffle('x', 0, 'x', 'x'))
        loutput = downsample.max_pool_2d(input=lconv_out_tanh, ds=self.poolsize, ignore_border=True, mode="max")
        routput = downsample.max_pool_2d(input=rconv_out_tanh, ds=self.poolsize, ignore_border=True, mode="max")
        return loutput, routput