[ModelZoo] Support Co_Action Network

modelzoo/CAN/README.md

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+# Co-Action Network
+
+The following is a brief directory structure and description for this example:
+
+
+
+```
+├── data                          # Data set directory
+│   ├── prepare_data.sh          # Shell script to download and process dataset
+│   └── README.md               # Documentation describing how to prepare dataset
+│   └── script                      # Directory contains scripts to process dataset
+│       ├── data_iterator.py           
+│       ├── generate_voc.py         # Create a list of features
+│       ├── local_aggretor.py       # Generate sample data     
+│       ├── shuffle.py
+│       ├──process_data.py          # Parse raw json data
+│       └── split_by_user.py        # Divide the dataset
+├── script                       #  Directory contains scripts to CAN model
+│	├── Dice.py
+│	├── model.py
+│	├── model_avazu.py
+│	├── rnn.py
+│	└── utils.py
+├── README.md                     # Documentation
+└── train.py                      # Training script
+```
+
+
+
+## Content
+
+[TOC]
+
+
+
+## Model Structure
+
+Implementation of paper "CAN: Revisiting Feature Co-Action for Click Through Rate Prediction".
+
+paper: [arxiv (to be released)]()
+
+
+
+## Usage
+
+### Stand-alone Training
+
+1. Please prepare the data set and DeepRec env.
+
+   1. Manually
+
+      - Follow [dataset preparation](https://github.com/alibaba/DeepRec/tree/main/modelzoo/DIEN#prepare) to prepare data set.
+      - Download code by `git clone https://github.com/alibaba/DeepRec`
+      - Follow [How to Build](https://github.com/alibaba/DeepRec#how-to-build) to build DeepRec whl package and install by `pip install $DEEPREC_WHL`.
+
+   2. Docker(Recommended)
+
+      ```
+      docker pull alideeprec/deeprec-release-modelzoo:latest
+      docker run -it alideeprec/deeprec-release-modelzoo:latest /bin/bash
+
+      # In docker container
+      cd /root/modelzoo/CAN
+      ```
+
+​	2.train.
+
+```
+python train.py
+```
+
+​	
+
+
+
+## Dataset
+
+Amazon Dataset Books dataset is used as benchmark dataset.
+
+### Prepare
+
+For details of Data download, see `./data`
+
+
+

modelzoo/CAN/data/README.md

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+# Dataset
+
+## Prepare dataset
+
+Prepare data of DIEN first;
+
+Run `prepare_data.sh` to download and process data:
+
+```
+sh prepare_data.sh
+```
+
+Put data into this folder.
+

modelzoo/CAN/data/prepare_data.sh

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+export PATH="~/anaconda4/bin:$PATH"
+wget http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Books.json.gz
+wget http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Books.json.gz
+gunzip reviews_Books.json.gz
+gunzip meta_Books.json.gz
+python script/process_data.py meta_Books.json reviews_Books.json
+python script/local_aggretor.py
+python script/split_by_user.py
+python script/generate_voc.py
+