Areas of improvement
- Improve generator methods (
predict_generator
,fit_generator
,evaluate_generator
) and add data enqueuing utilities. - Bug fixes and performance improvements.
- New features: new
Conv3DTranspose
layer, newMobileNet
application, self-normalizing networks.
API changes
- Self-normalizing networks: add
selu
activation function,AlphaDropout
layer,lecun_normal
initializer. - Data enqueuing: add
Sequence
,SequenceEnqueuer
,GeneratorEnqueuer
toutils
. - Generator methods: rename arguments
pickle_safe
(replaced withuse_multiprocessing
) andmax_q_size
(replaced withmax_queue_size
). - Add
MobileNet
to the applications module. - Add
Conv3DTranspose
layer. - Allow custom print functions for model's
summary
method (argumentprint_fn
).