shahaamirbader
commented
2 years ago Found out this is correct by installing on various conda evnironments with different pytorch settings.
Closed shahaamirbader closed 2 years ago
shahaamirbader
commented
2 years ago Found out this is correct by installing on various conda evnironments with different pytorch settings.
Hi I have tried installing sparseconvnet on almost all possible pytorch versions (1.3-1.9) with different combinations of cuda (10.2-11.3). Although sparseconvnet gets installed into the environment however when ever I run hello_world.py I get the following list of tensors on the terminal. Is that what I am supposed to see when I run the hello_world.py ? Am I not suppose to see HELLO WORLD written in the form of tensors?
(QGN) [ashah29@ecoms examples]$ python hello-world.py Using CUDA. Input SparseConvNetTensor: SparseConvNetTensor<<features=tensor([[1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.]]),features.shape=torch.Size([132, 1]),batch_locations=tensor([[ 0, 1, 0], [ 0, 5, 0], [ 0, 8, 0], [ 0, 9, 0], [ 0, 10, 0], [ 0, 13, 0], [ 0, 18, 0], [ 0, 23, 0], [ 0, 24, 0], [ 0, 30, 0], [ 0, 38, 0], [ 0, 42, 0], [ 0, 43, 0], [ 0, 47, 0], [ 0, 48, 0], [ 0, 49, 0], [ 0, 53, 0], [ 0, 58, 0], [ 0, 59, 0], [ 0, 60, 0], [ 1, 1, 0], [ 1, 5, 0], [ 1, 8, 0], [ 1, 13, 0], [ 1, 18, 0], [ 1, 22, 0], [ 1, 25, 0], [ 1, 30, 0], [ 1, 38, 0], [ 1, 41, 0], [ 1, 44, 0], [ 1, 47, 0], [ 1, 50, 0], [ 1, 53, 0], [ 1, 58, 0], [ 1, 61, 0], [ 2, 1, 0], [ 2, 2, 0], [ 2, 3, 0], [ 2, 4, 0], [ 2, 5, 0], [ 2, 8, 0], [ 2, 9, 0], [ 2, 13, 0], [ 2, 18, 0], [ 2, 22, 0], [ 2, 25, 0], [ 2, 30, 0], [ 2, 34, 0], [ 2, 38, 0], [ 2, 41, 0], [ 2, 44, 0], [ 2, 47, 0], [ 2, 48, 0], [ 2, 49, 0], [ 2, 53, 0], [ 2, 58, 0], [ 2, 62, 0], [ 3, 1, 0], [ 3, 5, 0], [ 3, 8, 0], [ 3, 13, 0], [ 3, 18, 0], [ 3, 22, 0], [ 3, 25, 0], [ 3, 31, 0], [ 3, 33, 0], [ 3, 35, 0], [ 3, 37, 0], [ 3, 41, 0], [ 3, 44, 0], [ 3, 47, 0], [ 3, 50, 0], [ 3, 53, 0], [ 3, 58, 0], [ 3, 61, 0], [ 4, 1, 0], [ 4, 5, 0], [ 4, 8, 0], [ 4, 9, 0], [ 4, 10, 0], [ 4, 13, 0], [ 4, 14, 0], [ 4, 15, 0], [ 4, 18, 0], [ 4, 19, 0], [ 4, 20, 0], [ 4, 23, 0], [ 4, 24, 0], [ 4, 32, 0], [ 4, 36, 0], [ 4, 42, 0], [ 4, 43, 0], [ 4, 47, 0], [ 4, 50, 0], [ 4, 53, 0], [ 4, 54, 0], [ 4, 55, 0], [ 4, 58, 0], [ 4, 59, 0], [ 4, 60, 0], [ 0, 1, 1], [ 0, 2, 1], [ 0, 3, 1], [ 0, 18, 1], [ 0, 19, 1], [ 0, 20, 1], [ 0, 21, 1], [ 0, 22, 1], [ 1, 1, 1], [ 1, 4, 1], [ 1, 7, 1], [ 1, 11, 1], [ 1, 12, 1], [ 1, 13, 1], [ 1, 21, 1], [ 2, 1, 1], [ 2, 2, 1], [ 2, 3, 1], [ 2, 20, 1], [ 3, 1, 1], [ 3, 7, 1], [ 3, 11, 1], [ 3, 12, 1], [ 3, 13, 1], [ 3, 21, 1], [ 4, 1, 1], [ 4, 7, 1], [ 4, 18, 1], [ 4, 19, 1], [ 4, 20, 1], [ 4, 21, 1]]),batch_locations.shape=torch.Size([132, 3]),spatial size=tensor([87, 87])>> Output SparseConvNetTensor: tensor([[[[0.5827, 0.5431, -0.0000, ..., 1.1020, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], ..., [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000]],
Input SparseConvNetTensor: SparseConvNetTensor<<features=tensor([[1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.], [1.]]),features.shape=torch.Size([132, 1]),batch_locations=tensor([[ 0, 1, 0], [ 0, 5, 0], [ 0, 8, 0], [ 0, 9, 0], [ 0, 10, 0], [ 0, 13, 0], [ 0, 18, 0], [ 0, 23, 0], [ 0, 24, 0], [ 0, 30, 0], [ 0, 38, 0], [ 0, 42, 0], [ 0, 43, 0], [ 0, 47, 0], [ 0, 48, 0], [ 0, 49, 0], [ 0, 53, 0], [ 0, 58, 0], [ 0, 59, 0], [ 0, 60, 0], [ 1, 1, 0], [ 1, 5, 0], [ 1, 8, 0], [ 1, 13, 0], [ 1, 18, 0], [ 1, 22, 0], [ 1, 25, 0], [ 1, 30, 0], [ 1, 38, 0], [ 1, 41, 0], [ 1, 44, 0], [ 1, 47, 0], [ 1, 50, 0], [ 1, 53, 0], [ 1, 58, 0], [ 1, 61, 0], [ 2, 1, 0], [ 2, 2, 0], [ 2, 3, 0], [ 2, 4, 0], [ 2, 5, 0], [ 2, 8, 0], [ 2, 9, 0], [ 2, 13, 0], [ 2, 18, 0], [ 2, 22, 0], [ 2, 25, 0], [ 2, 30, 0], [ 2, 34, 0], [ 2, 38, 0], [ 2, 41, 0], [ 2, 44, 0], [ 2, 47, 0], [ 2, 48, 0], [ 2, 49, 0], [ 2, 53, 0], [ 2, 58, 0], [ 2, 62, 0], [ 3, 1, 0], [ 3, 5, 0], [ 3, 8, 0], [ 3, 13, 0], [ 3, 18, 0], [ 3, 22, 0], [ 3, 25, 0], [ 3, 31, 0], [ 3, 33, 0], [ 3, 35, 0], [ 3, 37, 0], [ 3, 41, 0], [ 3, 44, 0], [ 3, 47, 0], [ 3, 50, 0], [ 3, 53, 0], [ 3, 58, 0], [ 3, 61, 0], [ 4, 1, 0], [ 4, 5, 0], [ 4, 8, 0], [ 4, 9, 0], [ 4, 10, 0], [ 4, 13, 0], [ 4, 14, 0], [ 4, 15, 0], [ 4, 18, 0], [ 4, 19, 0], [ 4, 20, 0], [ 4, 23, 0], [ 4, 24, 0], [ 4, 32, 0], [ 4, 36, 0], [ 4, 42, 0], [ 4, 43, 0], [ 4, 47, 0], [ 4, 50, 0], [ 4, 53, 0], [ 4, 54, 0], [ 4, 55, 0], [ 4, 58, 0], [ 4, 59, 0], [ 4, 60, 0], [ 0, 1, 1], [ 0, 2, 1], [ 0, 3, 1], [ 0, 18, 1], [ 0, 19, 1], [ 0, 20, 1], [ 0, 21, 1], [ 0, 22, 1], [ 1, 1, 1], [ 1, 4, 1], [ 1, 7, 1], [ 1, 11, 1], [ 1, 12, 1], [ 1, 13, 1], [ 1, 21, 1], [ 2, 1, 1], [ 2, 2, 1], [ 2, 3, 1], [ 2, 20, 1], [ 3, 1, 1], [ 3, 7, 1], [ 3, 11, 1], [ 3, 12, 1], [ 3, 13, 1], [ 3, 21, 1], [ 4, 1, 1], [ 4, 7, 1], [ 4, 18, 1], [ 4, 19, 1], [ 4, 20, 1], [ 4, 21, 1]]),batch_locations.shape=torch.Size([132, 3]),spatial size=tensor([87, 87])>> Output SparseConvNetTensor: tensor([[[[0.5827, 0.5431, -0.0000, ..., 1.1020, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], ..., [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000], [0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000]],