Dense to Sparse conversion keeps zero values

[AlexeyGB]

Describe the bug
I have a dense tensor with 3D data (voxels from ScanNet) and I want to convert it to sparse for sparse NN training. I did not found any way except the ME.to_sparse() function (MinkowskiToSparseTensor module uses same function under the hood). But when I converted my dense tensor to sparse I found, that new sparse tensor stores all values of dense tensor as features including zero values.
I believe that this behaviour of the ME.to_sparse()` function is incorrect and a sparse tensor should not store zero values by definition.
If I am wrong please correct me and tell me how I should convert a dense tensor to a sparse one for further efficient operation.

To Reproduce
I use a simpler tensor to reproduce the behaviour.

dense_batch = torch.tensor(
    [[[[0., 0.],
      [5., 0.]]],

    [[[0., 5.],
      [0., 0.]]],

    [[[0., 0.],
      [5., 0.]]]])
# shape is [3, 1, 2, 2]

sparse = ME.to_sparse(dense_batch)
sparse

Returns:

SparseTensor(
  coordinates=tensor([[0, 0, 0],
        [0, 0, 1],
        [0, 1, 0],
        [0, 1, 1],
        [1, 0, 0],
        [1, 0, 1],
        [1, 1, 0],
        [1, 1, 1],
        [2, 0, 0],
        [2, 0, 1],
        [2, 1, 0],
        [2, 1, 1]], dtype=torch.int32)
  features=tensor([[0.],
        [0.],
        [5.],
        [0.],
        [0.],
        [5.],
        [0.],
        [0.],
        [0.],
        [0.],
        [5.],
        [0.]])
  coordinate_map_key=coordinate map key:[1, 1]
  coordinate_manager=CoordinateMapManagerCPU(
	[1, 1, ��]:	CoordinateMapCPU:12x3
	algorithm=MinkowskiAlgorithm.DEFAULT
  )
  spatial dimension=2)

Expected behavior
I expect that the resulting sparse tensor will store only non-zero values.

Desktop (please complete the following information):

OS: Ubuntu 18.04.4 LTS
Python version: 3.8.1
CUDA version: 10.2
NVIDIA Driver version: 440.64
Minkowski Engine version: 0.5.1

• Output of the following command. (If you installed the latest MinkowskiEngine, simply call MinkowskiEngine.print_diagnostics())

wget -q https://raw.githubusercontent.com/NVIDIA/MinkowskiEngine/master/MinkowskiEngine/diagnostics.py ; python diagnostics.py

==========System==========
Linux-5.3.0-28-generic-x86_64-with-glibc2.10
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=18.04
DISTRIB_CODENAME=bionic
DISTRIB_DESCRIPTION="Ubuntu 18.04.4 LTS"
3.8.1 (default, Jan  8 2020, 22:29:32) 
[GCC 7.3.0]
==========Pytorch==========
1.7.1
torch.cuda.is_available(): True
==========NVIDIA-SMI==========
/usr/bin/nvidia-smi
Driver Version 440.64
CUDA Version 10.2
VBIOS Version 90.02.2E.00.0C
Image Version G001.0000.02.04
==========NVCC==========
/usr/local/cuda/bin/nvcc
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
==========CC==========
/usr/bin/c++
c++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

==========MinkowskiEngine==========
0.5.1
MinkowskiEngine compiled with CUDA Support: True
NVCC version MinkowskiEngine is compiled: 10020
CUDART version MinkowskiEngine is compiled: 10020

Additional context

[chrischoy]

Renamed the previous to_sparse function to to_sparse_all. Added a new to_sparse that removes the zero valued coordinates on

MinkowskiEngine/MinkowskiEngine/MinkowskiOps.py

Line 279 in aba0db2

def to_sparse(x: torch.Tensor, format: str = None, coordinates=None, device=None):

.

Please read the docstring to provide the correct format.