def __init__(self, in_size, ch):
    super(BottleNeckB, self).__init__()
    initialW = initializers.HeNormal()
    with self.init_scope():
        self.conv1 = L.Convolution2D(in_size, ch, 1, 1, 0, initialW=initialW, nobias=True)
        self.bn1 = L.BatchNormalization(ch)
        self.conv2 = L.Convolution2D(ch, ch, 3, 1, 1, initialW=initialW, nobias=True)
        self.bn2 = L.BatchNormalization(ch)
        self.conv3 = L.Convolution2D(ch, in_size, 1, 1, 0, initialW=initialW, nobias=True)
        self.bn3 = L.BatchNormalization(in_size)
def __init__(self, in_size, ch):
    super(BottleNeckB, self).__init__()
    initialW = initializers.HeNormal()
    with self.init_scope():
        self.conv1 = L.Convolution2D(in_size, ch, 1, 1, 0, initialW=initialW, nobias=True)
        self.bn1 = L.BatchNormalization(ch)
        self.conv2 = L.Convolution2D(ch, ch, 3, 1, 1, initialW=initialW, nobias=True)
        self.bn2 = L.BatchNormalization(ch)
        self.conv3 = L.Convolution2D(ch, in_size, 1, 1, 0, initialW=initialW, nobias=True)
        self.bn3 = L.BatchNormalization(in_size)