deconvolution_2d.py 文件源码

def __init__(self, in_channels, out_channels, ksize, stride=1, pad=0,
                 wscale=1, bias=0, nobias=False, outsize=None, use_cudnn=True,
                 initialW=None, initial_bias=None):
        kh, kw = _pair(ksize)
        self.stride = _pair(stride)
        self.pad = _pair(pad)
        self.outsize = (None, None) if outsize is None else outsize
        self.use_cudnn = use_cudnn

        W_shape = (in_channels, out_channels, kh, kw)
        super(Deconvolution2D, self).__init__(W=W_shape)

        if isinstance(initialW, (numpy.ndarray, cuda.ndarray)):
            assert initialW.shape == (in_channels, out_channels, kh, kw)
        # For backward compatibility, the scale of weights is proportional to
        # the square root of wscale.
        initializers.init_weight(self.W.data, initialW,
                                 scale=math.sqrt(wscale))

        if nobias:
            self.b = None
        else:
            self.add_param('b', out_channels)
            if isinstance(initial_bias, (numpy.ndarray, cuda.ndarray)):
                assert initial_bias.shape == (out_channels,)
            if initial_bias is None:
                initial_bias = bias
            initializers.init_weight(self.b.data, initial_bias)