kdllib.py 文件源码

def conv2d(input, filters, biases=None, border_mode=0, stride=(1, 1)):
    """
    Light wrapper around conv2d - optionally handle biases
    """
    r = nnet.conv2d(
            input=input,
            filters=filters,
            border_mode=border_mode,
            subsample=stride,
            filter_flip=True)
    if biases is None:
        return r
    else:
        return r + biases.dimshuffle('x', 0, 'x', 'x')