pooling.py 文件源码

def _generate_conv(self):
        input = T.tensor4(name='input')
        if self.pooling == 'squareroot':
            conv_out = Pool.pool_2d(
                T.power(input,2),
                ds=(self.spatial[0], self.spatial[1]),
                ignore_border=self.ignore_border,
                mode='sum',
                padding=self.pad,
                st=None if self.stride is None else (self.stride, self.stride))
            conv_out = T.sqrt(conv_out)
        else:
            conv_out = Pool.pool_2d(
                input,
                ds=(self.spatial[0], self.spatial[1]),
                ignore_border=self.ignore_border,
                mode=self.pooling,
                padding=self.pad,
                st=None if self.stride is None else (self.stride, self.stride))
        if self.activation_fct is None:
            output = conv_out
        else:
            output = self.activation_fct(conv_out)
        self.conv = theano.function([input], output)