Deepctr

Major Features and Improvements
- Modify output shape of `BiInteractionPooling`, `InnerProductLayer` to make
sure that the dimensions of the output and input of a layer are same if possible

Bug Fixes and Other Changes
- Minimize the nesting of other layers in the custom layer, because I found that the statistics of the parameters number of `model.summary()` are incorrect when using other layers.

Major Features and Improvements
- Use a more space efficient implementation in `deepctr.layers.CrossNet`
- Add linear and bias term in `deepctr.models.FNN`
- Add `custom_objects` in `deepctr.utils` which will be used in `tf.keras.models.load_model`
Bug Fixes and Other Changes
- Fix bug in `deepctr.layers.MLP` when use advance activation layer

Major Features and Improvements
- Simplify input logic,[examples](https://deepctr-torch.readthedocs.io/en/latest/Examples.html#classification-criteo)

Major Features and Improvements
- Add [sequence(multi-value) input support](https://deepctr-torch.readthedocs.io/en/latest/Examples.html#multi-value-input-movielens) .

Change Log
Major Features and Improvements

- Add [CCPM(Convolutional Click Prediction Model)](https://deepctr-torch.readthedocs.io/en/latest/Features.html#ccpm-convolutional-click-prediction-model)
中文介绍[CCPM&FGCNN:使用CNN进行特征生成的CTR预测模型](https://zhuanlan.zhihu.com/p/64015347)