def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None, bn_momentum=0.1, dimension=(- 1)):
    super(BasicBlockShallow, self).__init__()
    assert (dimension > 0)
    self.conv1 = ME.MinkowskiConvolution(inplanes, planes, kernel_size=1, stride=stride, dilation=dilation, dimension=dimension)
    self.norm1 = ME.MinkowskiBatchNorm(planes, momentum=bn_momentum)
    self.conv2 = ME.MinkowskiConvolution(planes, planes, kernel_size=1, stride=1, dilation=dilation, dimension=dimension)
    self.norm2 = ME.MinkowskiBatchNorm(planes, momentum=bn_momentum)
    self.relu = ME.MinkowskiReLU(inplace=True)
    self.downsample = downsample
def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None, bn_momentum=0.1, dimension=(- 1)):
    super(BasicBlockShallow, self).__init__()
    assert (dimension > 0)
    self.conv1 = ME.MinkowskiConvolution(inplanes, planes, kernel_size=1, stride=stride, dilation=dilation, dimension=dimension)
    self.norm1 = ME.MinkowskiBatchNorm(planes, momentum=bn_momentum)
    self.conv2 = ME.MinkowskiConvolution(planes, planes, kernel_size=1, stride=1, dilation=dilation, dimension=dimension)
    self.norm2 = ME.MinkowskiBatchNorm(planes, momentum=bn_momentum)
    self.relu = ME.MinkowskiReLU(inplace=True)
    self.downsample = downsample