def __init__(self, in_channels, out_channels, kernel_size, padding=0, stride=1, use_batchnorm=True):
    conv = nn.Conv3d(in_channels, out_channels, kernel_size, stride=stride, padding=padding, bias=(not use_batchnorm))
    relu = nn.ReLU(inplace=True)
    bn = nn.BatchNorm3d(out_channels)
    super(Conv3dReLU, self).__init__(conv, bn, relu)
def __init__(self, in_channels, out_channels, kernel_size, padding=0, stride=1, use_batchnorm=True):
    conv = nn.Conv3d(in_channels, out_channels, kernel_size, stride=stride, padding=padding, bias=(not use_batchnorm))
    relu = nn.ReLU(inplace=True)
    bn = nn.BatchNorm3d(out_channels)
    super(Conv3dReLU, self).__init__(conv, bn, relu)