New Feature: 

Modify the `Hash` layer to support the lookup feature. 

Now there are two hash techniques  supported in the `Hash` layer:

1. Lookup Table: when setup `vocabulary_path`,  it can looks up input keys in a table  and output the corresponding values. Missed keys are always return the default value, eg. `0`.
2. Bucket Hash: when `vocabulary_path` is not set, `Hash` will hash the input keys to [0,num_buckets). Parameter `mask_zero` can set `True`, which will set the hash value `0` when the input keys are `0` or `0.0`, and other value will be hash in range [1,num_buckets).

Initializing `Hash` with `vocabulary_path` CSV file which need follow the convention：the first column as keys and second column as values which are seperated by comma. 

The following is example snippet:

    * `1,emerson`
    * `2,lake`
    * `3,palmer`

    >>> hash = Hash(
    ...   num_buckets=3+1,
    ...   vocabulary_path=filename,
    ...   default_value=0)
    >>> hash(tf.constant('lake')).numpy()
    2
    >>> hash(tf.constant('lakeemerson')).numpy()
    0

New Feature: Support pre-defined key-value vocabulary in Hash Layer

add multi task learning models：add Shared-Bottom, ESSM, MMOE, CGC, PLE

- optimize and refactor codes of multitask models
- set dnn_hidden_units parameter to (256, 128, 64) for all models
- adjust code structure 
- add docs and examples

…_multivalue_movielens_hash.py

- add multitask learning models：SharedBottom, ESSM, MMOE, PLE
- set `dnn_hidden_units` parameter to `(256, 128, 64)`
- add new package `deepctr.models.multitask` and `deepctr.models.sequence` 
- fix truncated feature value error when padding string sequence in run_multivalue_movielens_hash.py

Add tutorials to submit a distributed training job on Kubernetes

improve compatibility with tensorflow 2.x

- support python 3.9 and 3.10
- support `cos` and `ln` attention_type in transformer
- polish docstring

* feat: Add EDCN model.

Co-authored-by: 何意 <heyi.jack@bytedance.com>
Co-authored-by: 浅梦 <weichenswc@163.com>

update EDCN &fix typo

* fix: h5py version in python>=3.9
Co-authored-by: 浅梦 <weichenswc@163.com>

- add EDCN model
- fix savedmodel error in tf2.4
- fix typo in position encoding layer