cnn_layers.py 文件源码

def encoder(tparams, layer0_input, filter_shape, pool_size,
                      prefix='cnn_encoder'):

    """ filter_shape: (number of filters, num input feature maps, filter height,
                        filter width)
        image_shape: (batch_size, num input feature maps, image height, image width)
    """

    conv_out = conv.conv2d(input=layer0_input, filters=tparams[_p(prefix,'W')], 
                            filter_shape=filter_shape)

    conv_out_tanh = tensor.tanh(conv_out + tparams[_p(prefix,'b')].dimshuffle('x', 0, 'x', 'x'))
    output = pool.pool_2d(input=conv_out_tanh, ds=pool_size, ignore_border=True)

    return output.flatten(2)