- feat: add Transformer model and layer architecture (wip) - fix(Transformer): gradient propagation between layers - fix(Transformer): tokenization, sequence handling and shapes - fix(callbacks): now compatible with every model architecture - fix_later: find why the Transformer output won't work - ci: bump version to 3.3.6
3.3.5
- feat(autoencoder): add VAE image generation - refactor: imports organization - refactor: examples folder tree organization - docs: fix typo - feat(preprocessing): add ImageDataGenerator - ci: bump version to 3.3.5
3.3.4
- docs: update readme - docs: remove useless comments - fix(convolution): stride parameter - feat(layer): add UpSampling2D" - docs: update readme - perf: changed NCHW to NHWC for CPU efficiency - docs: update readme - perf: switch from NCL to NLC for CPU efficiency - ci: bump version to 3.3.4
3.3.3
- fix(example): weight init - docs(examples): fresh run - docs: update readme - fix(layers): encoder and decoder layers - fix(conv2d): align output shape calculation between im2col and convolve - ci: bump version to 3.3.3
3.3.2
- fix(model): save method - docs: update readme - docs: update readme - feat(autoencoder): add variational autoencoder (VAE) - ci: bump version to 3.3.2
3.3.1
- docs: update todo - feat(preprocessing): add cosine similarity - docs: update todo - feat(callbacks): add LearningRateScheduler - ci: bump version to 3.3.1