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nn_models refactoring #120

Merged
merged 55 commits into from
Feb 22, 2024
Merged

nn_models refactoring #120

merged 55 commits into from
Feb 22, 2024

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technocreep
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  • base_nn_model refactoring
  • improved validation

@technocreep
fix
556ff06
@technocreep
fixed metrics calculation and logging
08fec4d
@technocreep
microfix test
9c3fe59
@technocreep
reqs fix to compatible state
d3e7a30
@technocreep
optimized requirements.txt content
992c1df
@technocreep
deleted obsolete modules
35dc2ba
@technocreep
fix
1d9f9d0
@technocreep
fixed metrics calculation and logging
24bebf6
@technocreep
microfix test
d8a33df
@technocreep
reqs fix to compatible state
2a8c2e7
@technocreep
optimized requirements.txt content
77130dd
@technocreep
deleted obsolete modules
4fddfa6
@technocreep
minor improvements
4d504ac
@technocreep
Merge remote-tracking branch 'origin/unit-integration' into unit-inte…
6285099 
…gration
@technocreep
fixed resnet performance
ba09870
@technocreep
# Conflicts:
7764649 
#	fedot_ind/api/main.py
#	fedot_ind/core/metrics/metrics_implementation.py
#	fedot_ind/core/operation/transformation/basis/eigen_basis.py
#	fedot_ind/tools/loader.py
@technocreep
fixed dataset configuration
de831d2
@technocreep
added colorization to recurrence extractor (kernel_matrix)
1fcd529
@technocreep
example recur + resnet
c2df899
@technocreep
added 3-channel recurrence representation of ts
d227ead
@technocreep
refactored base_nn_model: best val model saving, new methods
73ed291
@technocreep technocreep added the enhancement New feature or request label Feb 21, 2024
@technocreep technocreep self-assigned this Feb 21, 2024
@technocreep
fix
348a232
@technocreep
minor improvements
3c5caea
@technocreep
fixed resnet performance
6edb674
@technocreep
# Conflicts:
af6d394 
#	fedot_ind/api/main.py
#	fedot_ind/core/metrics/metrics_implementation.py
#	fedot_ind/core/operation/transformation/basis/eigen_basis.py
#	fedot_ind/tools/loader.py
@technocreep
fixed dataset configuration
dca7163
@technocreep
added colorization to recurrence extractor (kernel_matrix)
4f97706
@technocreep
example recur + resnet
a5a7992
@technocreep
fix
2e191d9
@technocreep
minor improvements
b9cab5f
@technocreep
fixed resnet performance
c741fce
@technocreep
# Conflicts:
37f1bfb 
#	fedot_ind/api/main.py
#	fedot_ind/core/metrics/metrics_implementation.py
#	fedot_ind/core/operation/transformation/basis/eigen_basis.py
#	fedot_ind/tools/loader.py
@technocreep
fixed dataset configuration
71ce32c
@technocreep
added colorization to recurrence extractor (kernel_matrix)
66c7231
@technocreep
example recur + resnet
da6e5fd
@technocreep
added 3-channel recurrence representation of ts
9e0a6a4
@technocreep
refactored base_nn_model: best val model saving, new methods
e5b6af9
@technocreep
fix resnet node
37caaab
@technocreep
fixed resnet performance
8af0d32
@technocreep
fixed dataset configuration
7ea341f
@technocreep
refactored base_nn_model: best val model saving, new methods
1f909ba
@technocreep
Merge remote-tracking branch 'origin/multi_channel_rec' into multi_ch…
8daecf3 
…annel_rec

# Conflicts:
#	fedot_ind/api/main.py
#	fedot_ind/core/metrics/metrics_implementation.py
#	fedot_ind/core/operation/transformation/basis/eigen_basis.py
@technocreep
pep8 fix
6ca1fe5
@technocreep
req fix
9efe3ae
@technocreep
fixed imports, pep8, unit-tests
c63e2a9
@technocreep
more test fix
1df15dd
@codecov Codecov
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codecov bot commented Feb 21, 2024 •
edited
Loading

Codecov Report

Attention: 130 lines in your changes are missing coverage. Please review.

Comparison is base (fc114be) 56.15% compared to head (143654c) 56.27%.
Report is 1 commits behind head on main.

Files Patch % Lines
...t_ind/core/models/nn/network_impl/base_nn_model.py 28.91% 59 Missing ⚠️
fedot_ind/api/utils/recurrent_image.py 0.00% 22 Missing ⚠️
...t_ind/core/models/ts_forecasting/ssa_forecaster.py 55.00% 9 Missing ⚠️
.../core/architecture/preprocessing/data_convertor.py 38.46% 8 Missing ⚠️
fedot_ind/core/models/nn/network_impl/inception.py 50.00% 7 Missing ⚠️
...edot_ind/core/models/nn/network_impl/omni_scale.py 41.66% 7 Missing ⚠️
fedot_ind/api/main.py 0.00% 6 Missing ⚠️
fedot_ind/core/models/nn/network_impl/resnet.py 0.00% 4 Missing ⚠️
...ot_ind/core/architecture/abstraction/decorators.py 0.00% 2 Missing ⚠️
...peration/transformation/regularization/spectrum.py 33.33% 2 Missing ⚠️
... and 4 more
Additional details and impacted files 
@@            Coverage Diff             @@
##             main     #120      +/-   ##
==========================================
+ Coverage   56.15%   56.27%   +0.11%     
==========================================
  Files         102      102              
  Lines        8946     9004      +58     
==========================================
+ Hits         5024     5067      +43     
- Misses       3922     3937      +15
Flag Coverage Δ
unittests 56.27% <45.83%> (+0.11%) ⬆️

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

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@technocreep technocreep requested a review from v1docq February 21, 2024 15:54
technocreep and others added 5 commits February 22, 2024 13:56
@technocreep
# Conflicts:
ea9bca4 
#	fedot_ind/api/main.py
#	fedot_ind/core/operation/transformation/basis/eigen_basis.py
#	fedot_ind/core/repository/constanst_repository.py
@technocreep
merged IRevin fixes
fcd1849
@technocreep
model repo fix
c630b59
@technocreep
small fix
32c4093
fix in convert predict, add accuracy logging
143654c
@technocreep technocreep merged commit 7c37e1c into main Feb 22, 2024
7 checks passed
@technocreep technocreep deleted the multi_channel_rec branch February 22, 2024 15:30
MisterZurg pushed a commit to MisterZurg/Fedot.Industrial that referenced this pull request Apr 22, 2024
@technocreep @MisterZurg
nn_models refactoring (aimclub#120)
b935804 
* fixed metrics calculation and logging
* reqs fix to compatible state
* deleted obsolete modules
* fixed resnet performance
* fixed dataset configuration
* added colorization to recurrence extractor (kernel_matrix)
* example recur + resnet
* added 3-channel recurrence representation of ts
* refactored base_nn_model: best val model saving, new methods
* pep8 fix
* fix in convert predict, add accuracy logging

---------

Co-authored-by: v1docq <ir@raxeltelematics.com>
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Reviewers

@valer1435 valer1435 valer1435 approved these changes

@v1docq v1docq Awaiting requested review from v1docq

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@technocreep @pep8speaks @valer1435