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 a92201c618ca747168ac755a150e0eb93733c519..a4f62b283563adffc725f20efae306240f30bf9d 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 @@ -84,27 +84,27 @@ Windows -- in a consistent way. 4. Run PaddlePaddle Book under Docker Container - The Jupyter Notebook is an open-source web application that allows - you to create and share documents that contain live code, equations, - visualizations and explanatory text in a single browser. + The Jupyter Notebook is an open-source web application that allows + you to create and share documents that contain live code, equations, + visualizations and explanatory text in a single browser. - PaddlePaddle Book is an interactive Jupyter Notebook for users and developers. - We already exposed port 8888 for this book. If you want to - dig deeper into deep learning, PaddlePaddle Book definitely is your best choice. + PaddlePaddle Book is an interactive Jupyter Notebook for users and developers. + We already exposed port 8888 for this book. If you want to + dig deeper into deep learning, PaddlePaddle Book definitely is your best choice. - Once you are inside the container, simply issue the command: + Once you are inside the container, simply issue the command: - .. code-block:: bash - - jupyter notebook - - Then, you would back and paste the address into the local browser: + .. code-block:: bash + + jupyter notebook - .. code-block:: text + Then, you would back and paste the address into the local browser: + + .. code-block:: text - http://localhost:8888/ + http://localhost:8888/ - That's all. Enjoy your journey! + That's all. Enjoy your journey! CPU-only and GPU Images ----------------------- @@ -116,21 +116,21 @@ automatically runs the following commands: .. code-block:: bash - docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile . - docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu . + docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile --build-arg BUILD_AND_INSTALL=ON . + docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu --build-arg BUILD_AND_INSTALL=ON . To run the CPU-only image as an interactive container: .. code-block:: bash - docker run -it --rm paddledev/paddle:cpu-latest /bin/bash + docker run -it --rm paddledev/paddle:0.10.0rc1-cpu /bin/bash or, we can run it as a daemon container .. code-block:: bash - docker run -d -p 2202:22 paddledev/paddle:cpu-latest + docker run -d -p 2202:22 paddledev/paddle:0.10.0rc1-cpu and SSH to this container using password :code:`root`: @@ -152,7 +152,7 @@ to install CUDA driver and let Docker knows about it: export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')" export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}') - docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest + docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:0.10.0rc1-gpu Non-AVX Images @@ -194,7 +194,7 @@ container: .. code-block:: bash - docker run -d --name paddle-cpu-doc paddle:cpu + docker run -d --name paddle-cpu-doc paddle:0.10.0rc1-cpu docker run -d --volumes-from paddle-cpu-doc -p 8088:80 nginx 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 60d4470e75ba9c9855ce7eb399154d79421f3fba..7054330503fb8f27495ed7d2f7cbea1877876820 100644 --- a/develop/doc/getstarted/build_and_install/docker_install_en.html +++ b/develop/doc/getstarted/build_and_install/docker_install_en.html @@ -277,8 +277,7 @@ ctest
  • Run PaddlePaddle Book under Docker Container

    -
    -

    The Jupyter Notebook is an open-source web application that allows +

    The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text in a single browser.

    PaddlePaddle Book is an interactive Jupyter Notebook for users and developers. @@ -293,7 +292,6 @@ dig deeper into deep learning, PaddlePaddle Book definitely is your best choice.

    That’s all. Enjoy your journey!

    -
  • @@ -303,16 +301,16 @@ dig deeper into deep learning, PaddlePaddle Book definitely is your best choice. CPU-only one and a CUDA GPU one. We do so by configuring dockerhub.com automatically runs the following commands:

    -
    docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile .
    -docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu .
    +
    docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile --build-arg BUILD_AND_INSTALL=ON .
    +docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu --build-arg BUILD_AND_INSTALL=ON .
     

    To run the CPU-only image as an interactive container:

    -
    docker run -it --rm paddledev/paddle:cpu-latest /bin/bash
    +
    docker run -it --rm paddledev/paddle:0.10.0rc1-cpu /bin/bash
     

    or, we can run it as a daemon container

    -
    docker run -d -p 2202:22 paddledev/paddle:cpu-latest
    +
    docker run -d -p 2202:22 paddledev/paddle:0.10.0rc1-cpu
     

    and SSH to this container using password root:

    @@ -328,7 +326,7 @@ from a laptop.

    to install CUDA driver and let Docker knows about it:

    export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
     export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
    -docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
    +docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:0.10.0rc1-gpu
     
    @@ -359,7 +357,7 @@ for users to browse and understand the C++ source code.

    As long as we give the Paddle Docker container a name, we can run an additional Nginx Docker container to serve the volume from the Paddle container:

    -
    docker run -d --name paddle-cpu-doc paddle:cpu
    +
    docker run -d --name paddle-cpu-doc paddle:0.10.0rc1-cpu
     docker run -d --volumes-from paddle-cpu-doc -p 8088:80 nginx
     
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2,47,50],paraphras:47,pass:41,perform:[36,39],pnpair_evalu:9,point:42,pool:[10,13,16,19],pooling_lay:10,power:16,power_lay:10,pre:33,precision_recall_evalu:9,predict:[5,49,50,54,55,56],prefetch:24,prepar:[25,32,37,42,47,48,49,54,56,57],preprocess:[47,49,52,54,57],prerequisit:37,pretrain:[47,57],print:9,privat:42,problem:25,profil:36,provid:[3,24,52,54,55],pull:33,push:33,pydataprovider2:3,python:[5,24,34,50,52,54],quick:52,randomnumb:39,rank:9,rank_cost:[10,16],rat:54,rate:53,reader:[20,23,24],recurr:[10,11,16,17,32,52],recurrent_group:[10,16],recurrent_lay:10,refer:[3,36,55,56],region:42,regress:[25,52,54],relu:14,reluactiv:6,render:42,repeat:16,repeat_lay:10,request:33,requir:[26,33],reshap:[10,16],resnet:50,result:[37,43,57],revis:[33,47],rmsprop:18,rmspropoptim:12,rnn:[31,32,39],role:55,rotat:16,rotate_lay:10,route53:42,run:[37,43,55],sampl:[10,16],sampling_id:16,sampling_id_lay:10,scale:16,scaling_lay:10,scaling_project:[10,16],script:43,secur:42,selective_fc:16,selective_fc_lay:10,semant:55,sentiment:[20,56],seq_concat:16,seq_concat_lay:10,seq_reshap:16,seq_reshape_lay:10,seqtext_printer_evalu:9,sequenc:32,sequence_conv_pool:[11,17],sequencesoftmax:14,sequencesoftmaxactiv:6,sequenti:3,server:[39,42],servic:42,set:[12,40],setup:[26,42],sgd:39,share:23,shuffl:24,sigmoid:14,sigmoidactiv:6,simpl:[25,32],simple_attent:[11,17],simple_gru:[11,17],simple_img_conv_pool:[11,17],simple_lstm:[11,17],singl:24,slice:[10,16],slope_intercept:16,slope_intercept_lay:10,softmax:14,softmaxactiv:6,softrelu:14,softreluactiv:6,sourc:[26,28],span:26,spars:41,specifi:[41,47],split:54,spp:16,spp_layer:10,squar:14,squareactiv:6,squarerootn:19,squarerootnpool:13,stack:56,standard:52,stanh:14,stanhactiv:6,start:[23,30,42,43,52],startup:43,structur:48,suffici:24,sum:19,sum_cost:[10,16],sum_evalu:9,sum_to_one_norm:16,sum_to_one_norm_lay:10,summar:23,summari:52,sumpool:13,system:42,table_project:[10,16],take:24,tanh:14,tanhactiv:6,tear:42,templat:42,tensor:16,tensor_lay:10,test:[34,39,41,54,55,56],text:57,text_conv_pool:[11,17],timer:36,tip:36,toi:48,tool:36,train:[22,23,24,25,37,39,41,42,43,47,48,49,52,54,55,56,57],trainer:[22,42,54],tran:16,trans_full_matrix_project:[10,16],trans_lay:10,transfer:52,tune:[36,39],tutori:[47,49,51,55,56,57],ubuntu:26,uci_h:20,unit:[34,39],updat:[23,33,42],usag:[24,35],use:24,user:[47,53,54,56,57],util:9,value_printer_evalu:9,vector:39,verifi:42,version:33,vgg_16_network:[11,17],visual:50,volum:42,vpc:42,warp_ctc:16,warp_ctc_lay:10,what:36,why:[24,36],wmt14:20,word:[47,52],workflow:57,workspac:37,wrapper:34,write:[34,52],yaml:43,your:33,zoo:[50,51]}}) \ No newline at end of file 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 78f518cfe49d81470af018685620baf83f082fbb..cf7dddd073ceb465781fcb235595788a294f5d96 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 @@ -56,6 +56,26 @@ PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Do cd /paddle/build ctest +4. 在Docker容器中运行PaddlePaddle书籍 + + Jupyter Notebook是一个开源的web程序,大家可以通过它制作和分享带有代码、公式、图表、文字的交互式文档。用户可以通过网页浏览文档。 + + PaddlePaddle书籍是为用户和开发者制作的一个交互式的Jupyter Nodebook。 + 如果您想要更深入了解deep learning,PaddlePaddle书籍一定是您最好的选择。 + + 当您进入容器内之后,只用运行以下命令: + + .. code-block:: bash + + jupyter notebook + + 然后在浏览器中输入以下网址: + + .. code-block:: text + + http://localhost:8888/ + + 就这么简单,享受您的旅程! 纯CPU和GPU的docker镜像 ---------------------- @@ -64,20 +84,20 @@ PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Do .. code-block:: bash - docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile . - docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu . + docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile --build-arg BUILD_AND_INSTALL=ON . + docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu --build-arg BUILD_AND_INSTALL=ON . 以交互容器方式运行纯CPU的镜像: .. code-block:: bash - docker run -it --rm paddledev/paddle:cpu-latest /bin/bash + docker run -it --rm paddledev/paddle:0.10.0rc1-cpu /bin/bash 或者,可以以后台进程方式运行容器: .. code-block:: bash - docker run -d -p 2202:22 paddledev/paddle:cpu-latest + docker run -d -p 2202:22 paddledev/paddle:0.10.0rc1-cpu 然后用密码 :code:`root` SSH进入容器: @@ -94,7 +114,7 @@ SSH方式的一个优点是我们可以从多个终端进入容器。比如, export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')" export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}') - docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest + docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:0.10.0rc1-gpu 非AVX镜像 @@ -128,7 +148,7 @@ Paddle的Docker镜像带有一个通过 `woboq code browser .. code-block:: bash - docker run -d --name paddle-cpu-doc paddle:cpu + docker run -d --name paddle-cpu-doc paddle:0.10.0rc1-cpu docker run -d --volumes-from paddle-cpu-doc -p 8088:80 nginx 接着我们就能够打开浏览器在 http://localhost:8088/paddle/ 浏览代码。 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 aef9cbcd04a70c1062502af5f3efaeef3f0d0b79..ea7e67d463992399b3795d524fc2d4da26e4274f 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 @@ -260,21 +260,35 @@ ctest
    +
  • 在Docker容器中运行PaddlePaddle书籍

    +

    Jupyter Notebook是一个开源的web程序,大家可以通过它制作和分享带有代码、公式、图表、文字的交互式文档。用户可以通过网页浏览文档。

    +

    PaddlePaddle书籍是为用户和开发者制作的一个交互式的Jupyter Nodebook。 +如果您想要更深入了解deep learning,PaddlePaddle书籍一定是您最好的选择。

    +

    当您进入容器内之后,只用运行以下命令:

    +
    jupyter notebook
    +
    +
    +

    然后在浏览器中输入以下网址:

    +
    http://localhost:8888/
    +
    +
    +

    就这么简单,享受您的旅程!

    +
  • 纯CPU和GPU的docker镜像

    对于每一个PaddlePaddle版本,我们都会发布两个Docker镜像:纯CPU的和GPU的。我们通过设置 dockerhub.com 自动运行以下两个命令:

    -
    docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile .
    -docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu .
    +
    docker build -t paddle:cpu -f paddle/scripts/docker/Dockerfile --build-arg BUILD_AND_INSTALL=ON .
    +docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu --build-arg BUILD_AND_INSTALL=ON .
     

    以交互容器方式运行纯CPU的镜像:

    -
    docker run -it --rm paddledev/paddle:cpu-latest /bin/bash
    +
    docker run -it --rm paddledev/paddle:0.10.0rc1-cpu /bin/bash
     

    或者,可以以后台进程方式运行容器:

    -
    docker run -d -p 2202:22 paddledev/paddle:cpu-latest
    +
    docker run -d -p 2202:22 paddledev/paddle:0.10.0rc1-cpu
     

    然后用密码 root SSH进入容器:

    @@ -285,7 +299,7 @@ docker build -t paddle:gpu -f paddle/scripts/docker/Dockerfile.gpu .

    以上方法在GPU镜像里也能用-只是请不要忘记按装CUDA驱动,以及告诉Docker:

    export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
     export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
    -docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
    +docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:0.10.0rc1-gpu
     
    @@ -308,7 +322,7 @@ docker build --build-arg WITH_AVX=文档

    Paddle的Docker镜像带有一个通过 woboq code browser 生成的HTML版本的C++源代码,便于用户浏览C++源码。

    只要在Docker里启动PaddlePaddle的时候给它一个名字,就可以再运行另一个Nginx Docker镜像来服务HTML代码:

    -
    docker run -d --name paddle-cpu-doc paddle:cpu
    +
    docker run -d --name paddle-cpu-doc paddle:0.10.0rc1-cpu
     docker run -d --volumes-from paddle-cpu-doc -p 8088:80 nginx
     
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