layers.py 文件源码

def __init__(self, rng, input, filter_shape, image_shape, poolsize=(2, 2),
                 stride=(1, 1)):
        """
        Allocate a LeNetConvPoolLayer with shared variable internal parameters.
        """

        assert image_shape[1] == filter_shape[1]
        self.input = input
        fan_in = np.prod(filter_shape[1:])
        fan_out = (filter_shape[0] * np.prod(filter_shape[2:]) /
                   np.prod(poolsize))
        W_bound = np.sqrt(6. / (fan_in + fan_out))
        self.W = theano.shared(
            np.asarray(
                rng.uniform(low=-W_bound, high=W_bound, size=filter_shape),
                dtype=theano.config.floatX
            ),
            borrow=True
        )

        b_values = np.zeros((filter_shape[0],), dtype=theano.config.floatX)
        self.b = theano.shared(value=b_values, borrow=True)

        conv_out = conv.conv2d(
            input=input,
            filters=self.W,
            filter_shape=filter_shape,
            image_shape=image_shape,
            subsample=stride
        )

        pooled_out = downsample.max_pool_2d(
            input=conv_out,
            ds=poolsize,
            ignore_border=True
        )
        self.output = T.tanh(pooled_out + self.b.dimshuffle('x', 0, 'x', 'x'))