def conv3d1x1(in_planes, out_planes, stride=1):
"""1x1 convolution"""
ret = nn.Conv3d(in_planes,
out_planes,
kernel_size=1,
stride=stride,
bias=True)
ret.apply(KaimingNormalWeightsZeroBias())
return ret
def conv3d3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
ret = nn.Conv3d(in_planes,
out_planes,
kernel_size=3,
stride=stride,
padding=1,
bias=True)
ret.apply(KaimingNormalWeightsZeroBias())
return ret