def __init__(self, in_channels, out_channels, ksize, stride=1, pad=0,
                 wscale=1, activation=relu.relu, use_cudnn=True):
        assert len(out_channels) > 0
        convs = [convolution_2d.Convolution2D(
            in_channels, out_channels[0], ksize, stride, pad,
            wscale=wscale, use_cudnn=use_cudnn)]
        for n_in, n_out in zip(out_channels, out_channels[1:]):
            convs.append(convolution_2d.Convolution2D(
                n_in, n_out, 1, wscale=wscale, use_cudnn=use_cudnn))
        super(MLPConvolution2D, self).__init__(*convs)
        self.activation = activation
dataset/ETHPy150Open pfnet/chainer/chainer/links/connection/mlp_convolution_2d.py/MLPConvolution2D.__init__/original