Replace old sparse -> dense -> sparse with new from_sparse method

[jkhouja]

Replaces all sparse torch casting to new method from_sparse except in 1 example where there's an issue #236 that's been documented.

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Codecov Report

All modified lines are covered by tests ✅

Comparison is base (1178970) 96.54% compared to head (5118ee2) 96.54%.

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #235   +/-   ##
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  Coverage   96.54%   96.54%           
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  Files          58       58           
  Lines        2230     2230           
=======================================
  Hits         2153     2153           
  Misses         77       77           

Files	Coverage Δ
topomodelx/utils/sparse.py	100.00% <100.00%> (ø)

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[ninamiolane]

Tests need to pass before we can review. See failures here:
https://github.com/pyt-team/TopoModelX/actions/runs/6424391426/job/17444941942?pr=235

[jkhouja]

@ninamiolane Thank you for taking a look. I was about to tag you and @mhajij for your thoughts. There's a weird issue in can_train tutorial that I've been working on since yesterday.

TLDR. can_layer errors when accessing index of the sparse matrix. So need to call coalesce before that. But then it's causing a matrix dimension mismatch in MultiHeadLiftLayer during training which made me suspicious of something deeper going on:

File [~/workspace/code/TopoModelX/topomodelx/nn/cell/can_layer.py:273](https://file+.vscode-resource.vscode-cdn.net/Users/jkhouja/workspace/code/TopoModelX/tutorials/cell/~/workspace/code/TopoModelX/topomodelx/nn/cell/can_layer.py:273), in MultiHeadLiftLayer.forward(self, x_0, neighborhood_0_to_0, x_1)
    271     print(combined_x_1.shape)
    272     print(x_1.shape)
--> 273     combined_x_1 = torch.cat(
    274         (combined_x_1, x_1), dim=1
    275     )  # (num_edges, heads + in_channels_1)
    277 return combined_x_1

RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 55 but got size 38 for tensor number 1 in the list.

So I'm tracing the source of the issue, identifying the matrix. It's taking me longer since I'm not familiar with CAN architecture. Will keep you posted.

[jkhouja]

@ninamiolane @mhajij I created a new ticket where I documented the details issue #236