diff --git a/docs/install/compile/linux-compile.md b/docs/install/compile/linux-compile.md index 64e82f0b831..0b38415d5be 100644 --- a/docs/install/compile/linux-compile.md +++ b/docs/install/compile/linux-compile.md @@ -24,7 +24,7 @@ * **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 diff --git a/docs/install/compile/linux-compile_en.md b/docs/install/compile/linux-compile_en.md index 57214a36669..70448cf14a0 100644 --- a/docs/install/compile/linux-compile_en.md +++ b/docs/install/compile/linux-compile_en.md @@ -16,14 +16,15 @@ * 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 diff --git a/docs/install/pip/linux-pip_en.md b/docs/install/pip/linux-pip_en.md index 4678d9163aa..2932aaa6119 100644 --- a/docs/install/pip/linux-pip_en.md +++ b/docs/install/pip/linux-pip_en.md @@ -91,7 +91,7 @@ If you installed Python via Homebrew or the Python website, `pip` was installed * **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)): diff --git a/docs/install/pip/windows-pip.md b/docs/install/pip/windows-pip.md index 41d850ee542..ae7fd2933e5 100644 --- a/docs/install/pip/windows-pip.md +++ b/docs/install/pip/windows-pip.md @@ -167,6 +167,7 @@ + ## **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()` diff --git a/docs/install/pip/windows-pip_en.md b/docs/install/pip/windows-pip_en.md index 8d74b04cfc5..b830696b417 100644 --- a/docs/install/pip/windows-pip_en.md +++ b/docs/install/pip/windows-pip_en.md @@ -64,7 +64,7 @@ If you installed Python via Homebrew or the Python website, `pip` was installed * **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