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How to use transposed conv3d correctly? #346

@GCChen97

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@GCChen97

Hi, thanks for the cool torchsparse! Recently I am trying to use it but I don't know how to upsample the input.
I made the following model to test, but it raised an empty kmaps error:

model = tsnn.Conv3d(3, 32, 2, 2, transposed=True).to('cuda')

After debugging, I found that it seems to require some "downsample" convolutions before transposed convolutions. Is my guess right?

Besides, how to set_kmap_mode correctly?

F.set_kmap_mode("hashmap")
model = tsnn.Conv3d(3, 3, 2, 2, transposed=True, generative=True).to('cuda')

I've set the mode as the code above. But it still raised an error and told me to set "hashmap" instead of "hashmap_on_the_fly".

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