Neuralnetlib

- feat+fix(gan+compiles): metrics in compile + fixed labels in GAN
- refactor(gan): evaluate
- fix(gan): metrics handling
- fix(mmd): numerical instability
- refactor(gan): some improvements
- fix(dropout): input shape for gans
- feat(gan): add adaptive plot sample gen according to activation function
- docs(notebook): update gan example
- docs(readme): update transformer description
- fix(cgan): conditional handling in G/D
- fix(lr): add gan support
- feat: add balanced batch sampling
- fix(docs): notebook example for gan
- build: correct version
- fix: beam search

- fix(configs): layers states saving and loading
- fix(configs): losses states saving and loading
- fix(configs): optimizers states saving and loading
- fix(configs): models states saving and loading
- ci: bump version to 4.3.3

- docs: update readme
- fix(dropout/batchnorm): save&load
- ci: bump version to 4.3.2

- fix(batchnorm): init
- ci: bump version to 4.3.1

- fix(git): file caching
- feat: add support for multi-label classification
- fix(cgan): y_train when None
- feat(cgan): add label smoothing
- fix(cgan): predictions
- docs(gans): update
- docs(notebook): add svm
- feat(utils): add make_blobs
- feat(utils): add make_classification
- feat(metrics): add adjusted_rand_score
- feat(metrics): add adjusted_mutual_info_score
- fix(metrics): MAE, MSE, MAPE
- refactor: usage of standalone functions everywhere
- ci: bump version to 4.3.0

- docs(notebook): fresh run²
- docs(readme): update quick examples
- docs(readme): update²
- docs: add conv example for gan
- feat(layer): add Conv2DTranspose
- docs: add conv example for gan using conv2dtranspose
- feat(GAN): add Conditional GAN (CGAN)
- ci: bump version to 4.2.0