def __init__(self, n_units, n_out, in_channels=IN_CHANNELS, out_channels=OUT_CHANNELS):
    super(CNN, self).__init__()
    with self.init_scope():
        self.conv1 = L.Convolution2D(in_channels, out_channels, (3, 1), pad=0)
        self.conv2 = L.Convolution2D(out_channels, out_channels, (3, 1), pad=0)
        self.conv3 = L.Convolution2D(out_channels, out_channels, (3, 1), pad=0)
        self.l1 = L.Linear(None, n_out)
    np.random.seed(100)
def __init__(self, n_units, n_out, in_channels=IN_CHANNELS, out_channels=OUT_CHANNELS):
    super(CNN, self).__init__()
    with self.init_scope():
        self.conv1 = L.Convolution2D(in_channels, out_channels, (3, 1), pad=0)
        self.conv2 = L.Convolution2D(out_channels, out_channels, (3, 1), pad=0)
        self.conv3 = L.Convolution2D(out_channels, out_channels, (3, 1), pad=0)
        self.l1 = L.Linear(None, n_out)
    np.random.seed(100)