Deepctr

Change Log
Major Features and Improvements

- Add `History` callback([example](https://deepctr-torch.readthedocs.io/en/latest/FAQ.html#set-learning-rate-and-use-earlystopping))

Bug Fixes and Other Changes

- Solve issues in 69, 87, 93, 128, 130
- Fix regularization error in pytorch1.7,
- improve compatibility for old version

API changes


- Add `History` in `deepctr_torch.callbacks`

Major Features and Improvements
- Adopted a new feature config generation method.[ example](https://deepctr-doc.readthedocs.io/en/latest/Examples.html#classification-criteo
)
- Simplified input mechanism for multi-valued features.[example](https://deepctr-doc.readthedocs.io/en/latest/Examples.html#multi-value-input-movielens
)
Bug Fixes and Other Changes
- In some cases the order of model input placeholder and actual model input list does not match.
- Divide by zero overflow in `SequencePoolingLayer` when sequence length is 0.

API changes
- Now we must use `SingleFeat` and `VarLenFeat` to build feature configuration dict.**Previous versions of the code require a little modification to work properly**.[ example](https://deepctr-doc.readthedocs.io/en/latest/Examples.html#classification-criteo
)

Major Features and Improvements
- Add [sequence(multi-value) input support](https://deepctr-doc.readthedocs.io/en/latest/Examples.html#multi-value-input-movielens) for `AFM,AutoInt,DCN,DeepFM,FNN,NFM,PNN,xDeepFM` models
- Refactor Input&Embedding module

Major Features and Improvements
- Add [**AutoInt**](https://deepctr-doc.readthedocs.io/en/latest/Features.html#autoint-automatic-feature-interaction) [中文模型介绍](https://zhuanlan.zhihu.com/p/53462648)
) model.
- Add `deepctr.layers.InteractingLayer`

Major Features and Improvements
- Add [**xDeepFM**](https://deepctr-doc.readthedocs.io/en/latest/Features.html#xdeepfm
) model.
- Add automatic check for new version of pypi package
Bug Fixes and Other Changes
- Fix some bugs when model's input field size is 1.
- Encapsulate some duplicate code

Major Features and Improvements
- `deepctr` now is compatible with tensorflow from `1.4.0-1.12.0` **except for** `1.7.*`and`1.8.*`.
- Add `normalized_att_score` attribute in `deepctr.layers.AFMLayer`,so we can [get the attentional weight distribution of feature interactions](https://deepctr-doc.readthedocs.io/en/latest/FAQ.html) in `deepctr.models.AFM`.
- Refactor `deepctr.models.MLR`
- Update `deepctr.models.PredictionLayer` to support Layer type activations.
Bug Fixes and Other Changes
- Fix bug in `deepctr.layers.DCN` when only use CrossNet.
- Fix bug in get_config of `deepctr.layers.LocalActivationUnit`

API changes
- Add default args to `deepctr.layers.MLP` and `deepctr.layers.LocalActivationUnit`