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Sep 28, 2022
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add tensorrt in docs #5315

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e712558
add tensorrt in docs
JZZ-NOTE Sep 28, 2022
0cb8627
Merge branch 'release/2.4' into jzz_2.4rc_docs
JZZ-NOTE Sep 28, 2022
cab5223
add tensorrt install
JZZ-NOTE Sep 28, 2022
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2 changes: 1 addition & 1 deletion docs/install/compile/linux-compile.md
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* **CUDA 工具包 11.7 配合 cuDNN v8.4.1(如需多卡支持，需配合 NCCL2.7 及更高；如需使用 PaddleTensorRT 推理，需配合 TensorRT8.4.2.4)**
* **GPU 运算能力超过 3.5 的硬件设备**

您可参考 NVIDIA 官方文档了解 CUDA 和 CUDNN 的安装流程和配置方法，请见[CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，
您可参考 NVIDIA 官方文档了解 CUDA 和 CUDNN 的安装流程和配置方法，请见[CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)


## 安装步骤
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13 changes: 7 additions & 6 deletions docs/install/compile/linux-compile_en.md
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* If your computer has NVIDIA® GPU, and the following conditions are met，GPU version of PaddlePaddle is recommended.

* **CUDA toolkit 10.1/10.2 with cuDNN 7 (cuDNN version>=7.6.5, for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 11.1 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 11.2 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 11.6 with cuDNN v8.4.0(for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 11.7 with cuDNN v8.4.1(for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 10.1 with cuDNN 7 (cuDNN version>=7.6.5, for multi card support, NCCL2.7 or higher)**
* **CUDA toolkit 10.2 with cuDNN 7 (cuDNN version>=7.6.5, for multi card support, NCCL2.7 or higher；for PaddleTensorRT deployment, TensorRT7.0.0.11)**
* **CUDA toolkit 11.1 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher；for PaddleTensorRT deployment, TensorRT7.2.3.4)**
* **CUDA toolkit 11.2 with cuDNN v8.1.1(for multi card support, NCCL2.7 or higher；for PaddleTensorRT deployment, TensorRT8.0.3.4)**
* **CUDA toolkit 11.6 with cuDNN v8.4.0(for multi card support, NCCL2.7 or higher；for PaddleTensorRT deployment, TensorRT8.4.0.6)**
* **CUDA toolkit 11.7 with cuDNN v8.4.1(for multi card support, NCCL2.7 or higher；for PaddleTensorRT deployment, TensorRT8.4.2.4)**
* **Hardware devices with GPU computing power over 3.5**

You can refer to NVIDIA official documents for installation process and configuration method of CUDA and cudnn. Please refer to[CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)
You can refer to NVIDIA official documents for installation process and configuration method of CUDA, cuDNN and TensorRT. Please refer to [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)


## Installation steps
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2 changes: 1 addition & 1 deletion docs/install/pip/linux-pip_en.md
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* **Hardware devices with GPU computing power over 3.5**

You can refer to NVIDIA official documents for installation process and configuration method of CUDA and cudnn. Please refer to [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)
You can refer to NVIDIA official documents for installation process and configuration method of CUDA, cuDNN and TensorRT. Please refer to [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)

* If you need to use a multi-card environment, please make sure that you have installed nccl2 correctly, or install nccl2 according to the following instructions (here are the installation instructions of nccl2 under CUDA10.2 and cuDNN7. For more version installation information, please refer to NVIDIA [Official Website](https://developer.nvidia.com/nccl)):

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## **三、验证安装**

安装完成后您可以使用 `python` 进入 python 解释器，输入`import paddle` ，再输入 `paddle.utils.run_check()`
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2 changes: 1 addition & 1 deletion docs/install/pip/windows-pip_en.md
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* **GPU CUDA capability over 3.5**

You can refer to NVIDIA official documents for installation process and configuration method of CUDA and cudnn. Please refer to [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)
You can refer to NVIDIA official documents for installation process and configuration method of CUDA, cuDNN and TensorRT. Please refer to [CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/)，[cuDNN](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/)，[TensorRT](https://developer.nvidia.com/nvidia-tensorrt-download)


## Installation Step
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