Deepctr

Change Log

Bug Fixes and Other Changes
- Fix numerical instability in `LayerNormalization`

API changes

- Remove `embedding_size` parameter from `PNN` model

Change Log
Major Features and Improvements

- Add [FLEN](https://deepctr-doc.readthedocs.io/en/latest/Features.html#flen-field-leveraged-embedding-network) Chinese Introducton [FLEN: 一种时空高效的利用场信息缓解梯度耦合的大规模CTR预测模型
](https://zhuanlan.zhihu.com/p/92787577)

Change Log

Bug Fixes and Other Changes
Fix the inconsistency of prediction results when the model is loaded with trained weights.

Change Log

- fix bug in `get_varlen_pooling_list`
- fix bug in `SequencePoolingLayer` when `mode='max'`
- Add alias `ONN` for model `NFFM`

Change Log [中文版本更新说明](https://zhuanlan.zhihu.com/p/104207011)

Major Features and Improvements
- Simplify [VarLenSparseFeat](https://deepctr-doc.readthedocs.io/en/latest/Features.html#varlensparsefeat),support setting weight_normalization. 163

Bug Fixes and Other Changes
- Fix problem of embedding size of `SparseFeat` in `linear_feature_columns`. 178

API changes

deepctr.layers.sequence.WeightedSequenceLayer
default value of `weight_normalization` in `WeightedSequenceLayer` is set to `True`。

- previous：`deepctr.layers.sequence.WeightedSequenceLayer(weight_normalization=False, supports_masking=False)`

- now：`deepctr.layers.sequence.WeightedSequenceLayer(weight_normalization=True, supports_masking=False)`


deepctr.inputs.VarLenSparseFeat

Parameter list of `VarLenSparseFeat` consists of a instance of `SparseFeat` and parameters related to sequence.


- previous：`VarLenSparseFeat(name, maxlen, vocabulary_size, embedding_dim=4, combiner="mean", use_hash=False, dtype="float32",
length_name=None, weight_name=None, embedding_name=None, group_name=DEFAULT_GROUP_NAME)`

- now：`VarLenSparseFeat(sparsefeat, maxlen, combiner="mean", length_name=None, weight_name=None, weight_norm=True)`

Change Log
Major Features and Improvements
- Refactor [feature columns](https://deepctr-doc.readthedocs.io/en/latest/Features.html#feature-columns).
- Different features can use different `embedding_dim`
- group-wise interaction is available by setting `group_name`.
- add linear part to some models

API changes
- `embedding_size` parameter of models is removed.Now we must set `embedding_dim`(default 4) in `SparseFeat` or `VarLenSparseFeat `.