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Merge pull request #5684 from FederatedAI/dev-2.2.0
Merge FATE-v2.2.0's Upgrades
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.gitmodules

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[submodule "fate_client"]
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path = fate_client
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url = https://github.com/FederatedAI/FATE-Client
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branch = v2.1.1
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branch = v2.2.0
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[submodule "fate_flow"]
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path = fate_flow
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url = https://github.com/FederatedAI/FATE-Flow
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branch = v2.1.0
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branch = v2.2.0
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[submodule "fate_test"]
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path = fate_test
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url = https://github.com/FederatedAI/FATE-Test.git
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branch = v2.1.1
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branch = v2.2.0
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[submodule "fate_board"]
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path = fate_board
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url = https://github.com/FederatedAI/FATE-Board.git

RELEASE.md

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## Release 2.2.0
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### Major Features and Improvements
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> Deployment
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* Upgrade from Python 3.8 to Python 3.10
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* Upgrade the PyTorch version to 2.x
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## Release 2.1.1
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### Major Features and Improvements
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> Component

bin/install_os_dependencies.sh

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case "${system}" in
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"CentOS Linux")
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echo "CentOS System"
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sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
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sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
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sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
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$command yum -y install gcc gcc-c++ make openssl-devel supervisor gmp-devel mpfr-devel libmpc-devel libaio numactl autoconf automake libtool libffi-devel snappy snappy-devel zlib zlib-devel bzip2 bzip2-devel lz4-devel libasan lsof
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;;
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"Ubuntu")

deploy/standalone-deploy/README.md

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- Prepare and install [conda](https://docs.conda.io/projects/miniconda/en/latest/) environment.
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- Create a virtual environment:
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```shell
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# FATE requires Python >= 3.8
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conda create -n fate_env python=3.8
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# FATE requires Python >= 3.10
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conda create -n fate_env python=3.10
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conda activate fate_env
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```
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##### 2.2.1.1 Installing FATE, FATE-Flow, FATE-Client
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```shell
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pip install fate_client[fate,fate_flow]==2.1.1
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pip install fate_client[fate,fate_flow]==2.2.0
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```
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#### 2.2.1.2 Service Initialization
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```shell
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#### 2.2.2.1 Installing FATE
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```shell
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pip install pyfate==2.1.1
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pip install pyfate==2.2.0
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```
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#### 2.2.2.2 Using Guides
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Refer to [examples](../../doc/2.0/fate/ml)
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Set the necessary environment variables for deployment (note that environment variables set in this way are only valid for the current terminal session. If you open a new terminal session, such as logging in again or opening a new window, you will need to reset them).
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```bash
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export version={FATE version number for this deployment, e.g., 2.1.1}
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export version={FATE version number for this deployment, e.g., 2.2.0}
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```
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Example:
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```bash
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export version=2.1.1
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export version=2.2.0
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```
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### 3.2 Pull Docker Images

deploy/standalone-deploy/README.zh.md

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- [conda](https://docs.conda.io/projects/miniconda/en/latest/) 环境准备及安装
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- 创建虚拟环境
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```shell
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# fate的运行环境为python>=3.8
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conda create -n fate_env python=3.8
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# fate的运行环境为python>=3.10
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conda create -n fate_env python=3.10
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conda activate fate_env
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```
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##### 2.2.1.1 安装FATE、FATE-Flow、FATE-Client
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```shell
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pip install fate_client[fate,fate_flow]==2.1.1
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pip install fate_client[fate,fate_flow]==2.2.0
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```
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#### 2.2.1.2 服务初始化
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#### 2.2.1.1 安装 FATE
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```shell
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pip install pyfate==2.1.1
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pip install pyfate==2.2.0
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```
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#### 2.2.2.2 使用指引
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设置部署所需环境变量(注意,通过以下方式设置的环境变量仅在当前终端会话中有效。如果打开新的终端会话,例如重新登录或打开新窗口,请重新设置)。
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```bash
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export version={本次部署的 FATE 版本号, 如 2.1.1}
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export version={本次部署的 FATE 版本号, 如 2.2.0}
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```
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示例:
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```bash
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export version=2.1.1
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export version=2.2.0
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```
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### 3.2 拉取镜像

doc/2.0/fate/dag.md

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max_depth: 3
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num_trees: 2
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...
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schema_version: 2.1.1
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schema_version: 2.2.0
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kind: fate
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```
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max_depth: 3
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num_trees: 2
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...
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schema_version: 2.1.1
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schema_version: 2.2.0
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```
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- Step1: Change the job-level stage in DAG to "predict"

doc/2.0/fate/dag.zh.md

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max_depth: 3
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num_trees: 2
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schema_version: 2.1.1
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schema_version: 2.2.0
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kind: fate
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```
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max_depth: 3
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num_trees: 2
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...
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schema_version: 2.1.1
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schema_version: 2.2.0
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```
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- Step1: 将dag下的全局job阶段的stage改成predict
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- Step2: 将用不到的组件从dag下的tasks,以及party_tasks进行删除,同时需要注意的是,删除组件可能会导致部分下游组件的dependent,以及输入发生改变,也需要对应修改。

doc/2.0/fate/homo_quick_start.md

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1. install `fate_client` with extra package `fate`
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```sh
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python -m pip install -U pip && python -m pip install fate_client[fate,fate_flow]==2.1.1
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python -m pip install -U pip && python -m pip install fate_client[fate,fate_flow]==2.2.0
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```
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after installing packages successfully, initialize fate_flow service and fate_client
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```
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6. More tutorials
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More pipeline api guides can be found in this [link](https://github.com/FederatedAI/FATE-Client/blob/main/doc/pipeline.md)
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More pipeline api guides can be found in this [link](https://github.com/FederatedAI/FATE-Client/blob/main/doc/pipeline.md)

doc/2.0/fate/quick_start.md

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1. install `fate_client` with extra package `fate`
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```sh
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python -m pip install -U pip && python -m pip install fate_client[fate,fate_flow]==2.1.1
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python -m pip install -U pip && python -m pip install fate_client[fate,fate_flow]==2.2.0
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```
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after installing packages successfully, initialize fate_flow service and fate_client
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```
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6. More tutorials
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More pipeline api guides can be found in this [link](https://github.com/FederatedAI/FATE-Client/blob/main/doc/pipeline.md)
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More pipeline api guides can be found in this [link](https://github.com/FederatedAI/FATE-Client/blob/main/doc/pipeline.md)

doc/tutorial/README.md

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aaa
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# Guide
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[Upload Data with FATE-Pipeline](./pipeline_tutorial_transform_local_file_to_dataframe.ipynb)
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[Train & Predict Coordinated-LR with FATE-Pipeline](./pipeline_tutorial_hetero.ipynb)

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