Fixing different device issue on multi-layer UNet and UNETR

[sarthakpati]

Fixes #N.A.

Proposed Changes

• using torch.nn.ModuleList instead of []
• added numbers to the tests to make it easier to track which ones fail
• specify scikit-image version

Checklist

• I have read the CONTRIBUTING guide
• My PR is based from the current GaNDLF master
• Non-breaking change (would not break existing functionality): please provide as many details as possible for any breaking change
• Function/class source code documentation added/updated
• Code has been blacked for style consistency
• If applicable, version information has been updated in GANDLF/version.py
• If adding a git submodule, add to list of exceptions for black styling in pyproject.toml file
• Usage documentation has been updated, if appropriate
• History has been updated, if appropriate
• Tests added or modified to cover the changes; if coverage is reduced, please give explanation
• If customized dependency installation is required (i.e., a separate pip install step is needed for PR to be functional), please ensure it is reflected in all the files that control the CI, namely: python-test.yml, and all docker files [1,2,3,4]

[dagshub]

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[codecov]

Codecov Report

Merging #399 (dee7452) into master (3e35ff0) will increase coverage by 0.02%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #399      +/-   ##
==========================================
+ Coverage   92.02%   92.04%   +0.02%     
==========================================
  Files         101      101              
  Lines        6003     6011       +8     
==========================================
+ Hits         5524     5533       +9     
+ Misses        479      478       -1     

Flag	Coverage Δ
unittests	92.04% <100.00%> (+0.02%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
setup.py	0.00% <ø> (ø)
GANDLF/models/light_unet_multilayer.py	98.00% <100.00%> (+0.04%)	⬆️
GANDLF/models/unet_multilayer.py	92.30% <100.00%> (+0.47%)	⬆️
GANDLF/models/unetr.py	97.08% <100.00%> (+0.01%)	⬆️
testing/test_full.py	98.23% <100.00%> (+<0.01%)	⬆️
...NDLF/data/preprocessing/template_matching/utils.py	97.67% <0.00%> (+2.32%)	⬆️

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