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‎docs/install/Tables.md‎

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@@ -328,7 +328,7 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
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<td> - </td>
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</tr>
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<tr>
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<td> cuda11.0-cudnn8-mkl-gcc8.2-avx </td>
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<td> cuda11.0-cudnn8.0-mkl-gcc8.2-avx </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.0-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post110-cp36-cp36m-linux_x86_64.whl">
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paddlepaddle_gpu-2.2.1.post110-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.0-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post110-cp37-cp37m-linux_x86_64.whl">
@@ -350,7 +350,7 @@ PaddePaddle通过编译时指定路径来实现引用各种BLAS/CUDA/cuDNN库。
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paddlepaddle_gpu-2.2.1.post111-cp39-cp39-linux_x86_64.whl</a></td>
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</tr>
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<tr>
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<td> cuda11.2-cudnn8-mkl-gcc8.2-avx </td>
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<td> cuda11.2-cudnn8.1-mkl-gcc8.2-avx </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.2-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post112-cp36-cp36m-linux_x86_64.whl">
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paddlepaddle_gpu-2.2.1.post112-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.2-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post112-cp37-cp37m-linux_x86_64.whl">
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda10.2-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post102-cp39-cp39-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp39-cp39-linux_x86_64.whl</a></td>
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</tr>
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<tr>
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<td> cuda11.0-cudnn8-mkl </td>
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<td> cuda11.0-cudnn8.0-mkl </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp38-cp38-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp38-cp38-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.1-cudnn8.1-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post111-cp39-cp39-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp39-cp39-linux_x86_64.whl</a></td>
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<td> cuda11.2-cudnn8-mkl </td>
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<td> cuda11.2-cudnn8.1-mkl </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp38-cp38-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp38-cp38-linux_x86_64.whl</a></td>

‎docs/install/Tables_en.md‎

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@@ -322,7 +322,7 @@ Please note that: in the commands, <code> paddlepaddle-gpu==2.2.1 </code> will i
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<td> cuda11.0-cudnn8-mkl-gcc8.2-avx </td>
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<td> cuda11.0-cudnn8.0-mkl-gcc8.2-avx </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.0-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post110-cp36-cp36m-linux_x86_64.whl">
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paddlepaddle_gpu-2.2.1.post110-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.0-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post110-cp37-cp37m-linux_x86_64.whl">
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<td> cuda11.2-cudnn8-mkl-gcc8.2-avx </td>
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<td> cuda11.2-cudnn8.1-mkl-gcc8.2-avx </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.2-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post112-cp36-cp36m-linux_x86_64.whl">
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paddlepaddle_gpu-2.2.1.post112-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/2.2.1/linux/linux-gpu-cuda11.2-cudnn8-mkl-gcc8.2-avx/paddlepaddle_gpu-2.2.1.post112-cp37-cp37m-linux_x86_64.whl">
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda10.2-cudnn7-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post102-cp39-cp39-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp39-cp39-linux_x86_64.whl</a></td>
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<td> cuda11.0-cudnn8-mkl </td>
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<td> cuda11.0-cudnn8.0-mkl </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.0-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post110-cp38-cp38-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp38-cp38-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.1-cudnn8.1-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post111-cp39-cp39-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp39-cp39-linux_x86_64.whl</a></td>
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<td> cuda11.2-cudnn8-mkl </td>
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<td> cuda11.2-cudnn8.1-mkl </td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp36-cp36m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp36-cp36m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp37-cp37m-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp37-cp37m-linux_x86_64.whl</a></td>
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<td> <a href="https://paddle-wheel.bj.bcebos.com/develop/linux/gpu-cuda11.2-cudnn8-mkl_gcc8.2/paddlepaddle_gpu-0.0.0.post112-cp38-cp38-linux_x86_64.whl"> paddlepaddle_gpu-latest-cp38-cp38-linux_x86_64.whl</a></td>

‎docs/install/compile/linux-compile.md‎

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* **Ubuntu 14.04 (不推荐，不提供编译出现问题时的官方支持)**
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* **Ubuntu 16.04 (GPU 版本支持 CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **Ubuntu 18.04 (GPU 版本支持 CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **Ubuntu 20.04 (GPU 版本支持 CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **Python 版本 3.6/3.7/3.8/3.9 (64 bit)**
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* **pip 或 pip3 版本 20.2.2或更高版本 (64 bit)**
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‎docs/install/compile/linux-compile_en.md‎

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* **Ubuntu 14.04 (not recommended, no official support for compilation problems)**
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* **Ubuntu 16.04 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **Ubuntu 18.04 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **Ubuntu 20.04 (GPU version supports CUDA 10.1/10.2/11.0/11.1/11.2)**
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* **pip or pip3 version 20.2.2 or above (64 bit)**
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‎docs/install/conda/linux-conda.md‎

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在进行PaddlePaddle安装之前请确保您的Anaconda软件环境已经正确安装。软件下载和安装参见Anaconda官网(https://www.anaconda.com/)。在您已经正确安装Anaconda的情况下请按照下列步骤安装PaddlePaddle。
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* CentOS 7 / Ubuntu16.04 / Ubuntu18.04 / Ubuntu20.04 (64bit)
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‎docs/install/conda/linux-conda_en.md‎

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Before performing PaddlePaddle installation, please make sure that your Anaconda software environment is properly installed. For software download and installation, see Anaconda's official website (https://www.anaconda.com/). If you have installed Anaconda correctly, follow these steps to install PaddlePaddle.
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‎docs/install/index_cn.rst‎

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**1. 操作系统要求：**
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* Ubuntu 16.04 / 18.04 / 20.04
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* 操作系统要求是 64 位版本
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* 不支持 **nvidia-docker** 方式安装
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* Ubuntu 16.04/18.04 支持 CUDA 10.1/10.2/11.0/11.1/11.2
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* Ubuntu 16.04/18.04/20.04 支持 CUDA 10.1/10.2/11.0/11.1/11.2
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* Ubuntu 16.04/18.04/20.04:
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‎docs/install/index_en.rst‎

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* Ubuntu 16.04 / 18.04 / 20.04
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* Ubuntu 16.04 / 18.04 / 20.04 supports CUDA 10.1/10.2/11.0/11.1/11.2
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‎docs/install/pip/linux-pip.md‎

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```
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* 如果你想安装联编`tensorrt`的Paddle包，可以通过以下命令将wheel包下载到本地，再使用`python -m pip install [name].whl`本地安装（[name]为wheel包名称）：
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```
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* 如果你想安装`avx`、`openblas`的Paddle包，可以通过以下命令将wheel包下载到本地，再使用`python -m pip install [name].whl`本地安装（[name]为wheel包名称）：
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* 如果你想安装联编`tensorrt`的Paddle包，可以参考[下载安装Linux预测库](https://paddleinference.paddlepaddle.org.cn/user_guides/download_lib.html)。
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‎docs/install/pip/linux-pip_en.md‎

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* If you want to install the Paddle package with `avx` and `openblas`, you can use the following command to download the wheel package to the local, and then use `python -m pip install [name].whl` to install locally ([name] is the name of the wheel package):
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```
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```
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