diff --git a/develop/doc/_sources/getstarted/build_and_install/docker_install_en.rst.txt b/develop/doc/_sources/getstarted/build_and_install/docker_install_en.rst.txt
index 5a46c598f2248c7912169a9e77b16851230c1d2e..06012bf65e75c32957516f6b7f62e09480871b84 100644
--- a/develop/doc/_sources/getstarted/build_and_install/docker_install_en.rst.txt
+++ b/develop/doc/_sources/getstarted/build_and_install/docker_install_en.rst.txt
@@ -137,7 +137,7 @@ GPU driver installed before move on.
AVX is a kind of CPU instruction can accelerate PaddlePaddle's calculations.
The latest PaddlePaddle Docker image turns AVX on by default, so, if your
computer doesn't support AVX, you'll probably need to
-`build <./build_from_source_en.rst>`_ with :code:`WITH_AVX=OFF`.
+`build <./build_from_source_en.html>`_ with :code:`WITH_AVX=OFF`.
The following command will tell you whether your computer supports AVX.
diff --git a/develop/doc/getstarted/build_and_install/docker_install_en.html b/develop/doc/getstarted/build_and_install/docker_install_en.html
index d0bb64618414141a48fcfa3c294dd01dfd127575..7e461fc4ac8125fda4f9a2af737b77dd6d9cc4a9 100644
--- a/develop/doc/getstarted/build_and_install/docker_install_en.html
+++ b/develop/doc/getstarted/build_and_install/docker_install_en.html
@@ -331,7 +331,7 @@ docker run ${CUDA_SOAVX is a kind of CPU instruction can accelerate PaddlePaddle’s calculations.
The latest PaddlePaddle Docker image turns AVX on by default, so, if your
computer doesn’t support AVX, you’ll probably need to
-build with WITH_AVX=OFF
.
WITH_AVX=OFF
.
The following command will tell you whether your computer supports AVX.
if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi diff --git a/develop/doc_cn/_sources/getstarted/build_and_install/docker_install_cn.rst.txt b/develop/doc_cn/_sources/getstarted/build_and_install/docker_install_cn.rst.txt index 1eb06e4182d40c3be20d71e37b34009905eaf9d6..fa1b6a372728ccac128d2e6e79a6514b8884ea3f 100644 --- a/develop/doc_cn/_sources/getstarted/build_and_install/docker_install_cn.rst.txt +++ b/develop/doc_cn/_sources/getstarted/build_and_install/docker_install_cn.rst.txt @@ -128,7 +128,7 @@ PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Note AVX是一种CPU指令集,可以加速PaddlePaddle的计算。最新的PaddlePaddle Docker镜像默认 是开启AVX编译的,所以,如果您的电脑不支持AVX,需要单独 -`编译 <./build_from_source_cn.rst>`_ PaddlePaddle为no-avx版本。 +`编译 <./build_from_source_cn.html>`_ PaddlePaddle为no-avx版本。 以下指令能检查Linux电脑是否支持AVX: diff --git a/develop/doc_cn/_sources/howto/usage/cluster/k8s_distributed_cn.md.txt b/develop/doc_cn/_sources/howto/usage/cluster/k8s_distributed_cn.md.txt index 701a9a75d78b53d7dab94529dbd1be382ff0d04e..167089b8074b33e3b094fa3ec8e377630cec42ac 100644 --- a/develop/doc_cn/_sources/howto/usage/cluster/k8s_distributed_cn.md.txt +++ b/develop/doc_cn/_sources/howto/usage/cluster/k8s_distributed_cn.md.txt @@ -2,8 +2,6 @@ 前一篇文章介绍了如何在Kubernetes集群上启动一个单机PaddlePaddle训练作业 (Job)。在这篇文章里,我们介绍如何在Kubernetes集群上进行分布式PaddlePaddle训练作业。关于PaddlePaddle的分布式训练,文章 [Cluster Training](http://www.paddlepaddle.org/docs/develop/documentation/zh/howto/usage/cluster/cluster_train_cn.html)介绍了一种通过SSH远程分发任务,进行分布式训练的方法,与此不同的是,本文将介绍在Kubernetes容器管理平台上快速构建PaddlePaddle容器集群,进行分布式训练的方案。 -有关Kubernetes相关概念以及如何搭建和配置Kubernetes集群,可以参考[k8s_basis](./k8s_basis_cn.md)。 - ## 整体方案 在训练之前,用户将配置与训练数据切分好放在分布式文件系统预先分配好的目录中(不同的分布式文件系统,需要使用其制定的方式挂载后并导入数据),训练时,程序从此目录拷贝文件到容器内进行训练,将结果保存到此目录里。整体的结构图如下: diff --git a/develop/doc_cn/getstarted/build_and_install/docker_install_cn.html b/develop/doc_cn/getstarted/build_and_install/docker_install_cn.html index bb5d2a290ddde7bfe0274b5a3f6a6d246a40ee45..b7948d30a500a156c82db945b028f6c956ebb0c6 100644 --- a/develop/doc_cn/getstarted/build_and_install/docker_install_cn.html +++ b/develop/doc_cn/getstarted/build_and_install/docker_install_cn.html @@ -336,7 +336,7 @@ docker run ${CUDA_SO关于AVX:AVX是一种CPU指令集,可以加速PaddlePaddle的计算。最新的PaddlePaddle Docker镜像默认 是开启AVX编译的,所以,如果您的电脑不支持AVX,需要单独 -编译 PaddlePaddle为no-avx版本。
+编译 PaddlePaddle为no-avx版本。以下指令能检查Linux电脑是否支持AVX:
if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi diff --git a/develop/doc_cn/howto/usage/cluster/k8s_distributed_cn.html b/develop/doc_cn/howto/usage/cluster/k8s_distributed_cn.html index bbbbcdd827e8e8ea4f1e74f5288eec2803bd0749..c5e4d47df40d0ab707ea577eeb5a3cd79496f81e 100644 --- a/develop/doc_cn/howto/usage/cluster/k8s_distributed_cn.html +++ b/develop/doc_cn/howto/usage/cluster/k8s_distributed_cn.html @@ -231,7 +231,6 @@Kubernetes分布式训练¶
前一篇文章介绍了如何在Kubernetes集群上启动一个单机PaddlePaddle训练作业 (Job)。在这篇文章里,我们介绍如何在Kubernetes集群上进行分布式PaddlePaddle训练作业。关于PaddlePaddle的分布式训练,文章 Cluster Training介绍了一种通过SSH远程分发任务,进行分布式训练的方法,与此不同的是,本文将介绍在Kubernetes容器管理平台上快速构建PaddlePaddle容器集群,进行分布式训练的方案。
-有关Kubernetes相关概念以及如何搭建和配置Kubernetes集群,可以参考k8s_basis。
整体方案¶
在训练之前,用户将配置与训练数据切分好放在分布式文件系统预先分配好的目录中(不同的分布式文件系统,需要使用其制定的方式挂载后并导入数据),训练时,程序从此目录拷贝文件到容器内进行训练,将结果保存到此目录里。整体的结构图如下:
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