Here I want to create a new SparseTensor with
new_out:
feats: enc_out.feats[10:11, :],
coords: enc_out.coords[10:11, ]
spatial_range: enc_out.spatial_range
stride: enc_out.stride.
But it fails when I try to pass the new_out to U-net decoder.
File "/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, *kwargs)
File "/lib/python3.8/site-packages/torch/nn/modules/container.py", line 217, in forward
input = module(input)
File "/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(args, **kwargs)
File "/torchsparse/torchsparse/nn/modules/conv.py", line 98, in forward
return F.conv3d(
File "/torchsparse/torchsparse/nn/functional/conv/conv.py", line 138, in conv3d
kmap = F.transpose_kernel_map(
File "/torchsparse/torchsparse/nn/functional/conv/kmap/build_kmap.py", line 233, in transpose_kernel_map
kmap["out_in_map"], make_divisible(kmap["sizes"][0], cta_M)
TypeError: 'NoneType' object is not subscriptable
How should I adjust the values in cmap, kmap and hashmaps to achieve my goal?
I build a sparse U-Net (without skip connection) for 3d point cloud segmentation.
Suppose the input is of shape 16000x3, the output of encoder is 1000x3. I want to check the individual value of the encoder output.
enc_out: feats: 1000x128 coords: 1000x4 (B, X, Y, Z) spatial_range: (64x64x8)
Here I want to create a new SparseTensor with new_out: feats: enc_out.feats[10:11, :], coords: enc_out.coords[10:11, ] spatial_range: enc_out.spatial_range stride: enc_out.stride.
But it fails when I try to pass the new_out to U-net decoder.
File "/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/lib/python3.8/site-packages/torch/nn/modules/container.py", line 217, in forward input = module(input) File "/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, **kwargs) File "/torchsparse/torchsparse/nn/modules/conv.py", line 98, in forward return F.conv3d( File "/torchsparse/torchsparse/nn/functional/conv/conv.py", line 138, in conv3d kmap = F.transpose_kernel_map( File "/torchsparse/torchsparse/nn/functional/conv/kmap/build_kmap.py", line 233, in transpose_kernel_map kmap["out_in_map"], make_divisible(kmap["sizes"][0], cta_M) TypeError: 'NoneType' object is not subscriptable
How should I adjust the values in cmap, kmap and hashmaps to achieve my goal?