Support Sparse Matrix as Target Matrix

[yoyolicoris]

This PR add the ability to call fit and sparse_fit when target is a 2-dimensional torch.sparse_coo_tensor.
This is only valid on NMF, other class of NMF will throw not implemented error.

[codecov-io]

Codecov Report

Merging #16 (dec2d34) into master (ea4ebcb) will decrease coverage by 5.99%.
The diff coverage is 74.01%.

@@            Coverage Diff             @@
##           master      #16      +/-   ##
==========================================
- Coverage   94.63%   88.63%   -6.00%     
==========================================
  Files           7        7              
  Lines         671      792     +121     
==========================================
+ Hits          635      702      +67     
- Misses         36       90      +54     

Flag	Coverage Δ
unittests	88.63% <74.01%> (-6.00%)	⬇️

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Impacted Files	Coverage Δ
torchnmf/nmf.py	84.34% <71.95%> (-11.37%)	⬇️
torchnmf/metrics.py	100.00% <100.00%> (ø)
torchnmf/trainer.py	93.75% <100.00%> (+0.11%)	⬆️

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[yoyolicoris]

Seems that training would become very unstable when using sparse_fit with sparse target and beta < 0,
Maybe add extra docstring on sparse_fit to mention that beta = 2 is prefered (the original paper only use euclidean distance), other beta values is not gaurantee to work.