From c67ab37b39140bffd669874253e0bd36b27fb319 Mon Sep 17 00:00:00 2001 From: Chi Song Date: Thu, 7 Mar 2019 16:13:05 +0800 Subject: [PATCH] Refine document for new user to submit job (#2278) 1. add new guidance to submit job for beginners. 2. refine homepage to connect with new guidance. 3. reorganize content of troubleshooting for next refactoring. 4. fix links in md files. --- .github/ISSUE_TEMPLATE/bug-report.md | 2 +- README.md | 40 ++--- contrib/pai_vscode/VSCodeExt.md | 22 +-- docs/images/PAI_submit_online_1.png | Bin 294283 -> 0 bytes docs/images/PAI_submit_online_2.png | Bin 45866 -> 0 bytes docs/images/PAI_submit_online_3.png | Bin 298638 -> 0 bytes docs/images/PAI_submit_online_4.png | Bin 343966 -> 0 bytes docs/job_log.md | 45 ++--- docs/job_tutorial.md | 136 ++++----------- docs/rest-server/API.md | 6 +- docs/submit_from_webportal.md | 20 --- docs/user/imgs/web_click_submit_job.png | Bin 0 -> 50374 bytes docs/user/imgs/web_dashboard.png | Bin 0 -> 126992 bytes docs/user/imgs/web_job_details.png | Bin 0 -> 27275 bytes docs/user/imgs/web_job_list.png | Bin 0 -> 86430 bytes docs/user/imgs/web_paste_json.png | Bin 0 -> 56986 bytes docs/user/imgs/web_submit_job.png | Bin 0 -> 68614 bytes docs/user/training.md | 161 ++++++++++++++++++ docs/user/troubleshooting_job.md | 67 ++++++++ docs/webportal/README.md | 2 +- examples/README.md | 70 ++------ examples/XGBoost/README.md | 2 +- .../README.md | 4 +- examples/caffe/README.md | 3 +- examples/caffe2/README.md | 2 +- examples/chainer/README.md | 2 +- examples/cntk/README.md | 2 +- .../README.md | 4 +- examples/horovod/README.md | 2 +- examples/jupyter/README.md | 2 +- examples/keras/README.md | 2 +- examples/mpi/README.md | 13 +- examples/mxnet/README.md | 11 +- examples/ocr-serving/README.md | 10 +- examples/pytorch/README.md | 11 +- examples/scikit-learn/README.md | 11 +- examples/serving/README.md | 3 +- examples/tensorflow/README.md | 16 +- 38 files changed, 380 insertions(+), 291 deletions(-) delete mode 100644 docs/images/PAI_submit_online_1.png delete mode 100644 docs/images/PAI_submit_online_2.png delete mode 100644 docs/images/PAI_submit_online_3.png delete mode 100644 docs/images/PAI_submit_online_4.png delete mode 100644 docs/submit_from_webportal.md create mode 100644 docs/user/imgs/web_click_submit_job.png create mode 100644 docs/user/imgs/web_dashboard.png create mode 100644 docs/user/imgs/web_job_details.png create mode 100644 docs/user/imgs/web_job_list.png create mode 100644 docs/user/imgs/web_paste_json.png create mode 100644 docs/user/imgs/web_submit_job.png create mode 100644 docs/user/training.md create mode 100644 docs/user/troubleshooting_job.md diff --git a/.github/ISSUE_TEMPLATE/bug-report.md b/.github/ISSUE_TEMPLATE/bug-report.md index 831f4746f3..915fa80001 100644 --- a/.github/ISSUE_TEMPLATE/bug-report.md +++ b/.github/ISSUE_TEMPLATE/bug-report.md @@ -23,7 +23,7 @@ Please fill this for deployment related issues: **How to reproduce it**: diff --git a/README.md b/README.md index e4699b33b6..a078a75afd 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ OpenPAI is an open source platform that provides complete AI model training and 1. [Why choose OpenPAI](#why-choose-openpai) 1. [Get started](#get-started) 1. [Deploy OpenPAI](#deploy-openpai) -1. [Train model](#train-models) +1. [Train models](#train-models) 1. [Administration](#administration) 1. [Reference](#reference) 1. [Get involved](#get-involved) @@ -93,9 +93,9 @@ As various hardware environments and different use scenarios, default configurat ### Validate deployment -After deployment, it's recommended to [validate key components of OpenPAI](docs/pai-management/doc/validate-deployment.md) in health status. After validation is success, [submit a "hello world" job](examples/README.md#quickstart) and check if it works end-to-end. +After deployment, it's recommended to [validate key components of OpenPAI](docs/pai-management/doc/validate-deployment.md) in health status. After validation is success, [submit a hello-world job](docs/user/training.md) and check if it works end-to-end. -### Train users before "train model" +### Train users before "train models" The common practice on OpenPAI is to submit job requests, and wait jobs got computing resource and executed. It's different experience with assigning dedicated servers to each one. People may feel computing resource is not in control and the learning curve may be higher than run job on dedicated servers. But shared resource on OpenPAI can improve productivity significantly and save time on maintaining environments. @@ -109,41 +109,23 @@ If FAQ doesn't resolve it, refer to [here](#get-involved) to ask question or sub ## Train models -Like all machine learning platforms, OpenPAI is a production tool. To maximize utilization, it's recommended to submit training jobs and OpenPAI will allocate resource to run it. If there are too many jobs, some jobs may wait in the queue. This is different with training models on dedicated servers for each person, and it needs a bit more knowledge about how to submit/manage training jobs on OpenPAI. +Like all machine learning platforms, OpenPAI is a productive tool. To maximize utilization, it's recommended to submit training jobs and let OpenPAI to allocate resource and run it. If there are too many jobs, some jobs may be queued until enough resource available, and OpenPAI choose some server(s) to run a job. This is different with run code on dedicated servers, and it needs a bit more knowledge about how to submit/manage training jobs on OpenPAI. -OpenPAI also supports to allocate on demand resource to users, and users can use SSH or Jupyter like on a physical server, refer to [here](examples/jupyter/README.md) about how to use OpenPAI like this way. Though it's not efficient to resources, but it also saves cost on setup and managing environments on physical servers. +Note, OpenPAI also supports to allocate on demand resource besides queuing jobs. Users can use SSH or Jupyter to connect like on a physical server, refer to [here](examples/jupyter/README.md) about how to use OpenPAI like this way. Though it's not efficient to resources, but it also saves cost on setup and managing environments on physical servers. -### Train first model on OpenPAI +### Submit training jobs -Follow [here](examples/README.md#quickstart) to create the first job definition. Then [submit the job via web portal](docs/submit_from_webportal.md). It's a very simple job, as it downloads data and code from internet, and doesn't copy model back. It's used to understand OpenPAI job definition and familiar with Web portal. +Follow [submitting a hello-world job](docs/user/training.md), and learn more about training models on OpenPAI. It's a very simple job and used to understand OpenPAI job definition and familiar with Web portal. -### Learn deeper on job definition +### OpenPAI VS Code Client -* Choose training environment. OpenPAI uses [Docker](https://www.docker.com/) to provide runtime environment. - - Refer to [here](https://hub.docker.com/r/ufoym/deepo) to find more deep learning environments, for example, `ufoym/deepo:pytorch-py36-cu90`. - - Note, this docker doesn't include openssh-server, curl. So, if SSH is necessary with those docker images, it needs to add `apt install openssh-server curl` in command field. - -* Put code and data in. OpenPAI creates a clean environment as docker image. The data and code may not be in the docker. So it needs to use command field to copy data and code into docker before training. The command field supports to join multiple commands with `&&`. If extra system or Python components are needed, they can be installed in the command by `apt install` or `python -m pip install` as well. - - There are some suggested approach to exchange data with running environment, but it's better to check with administrators of OpenPAI, which kind of storage is supported, and recommended approach to access it. - -* Copy model back. It's similar with above topic, if code and data can copy into docker, model can also be copied back. - -* Running distributed training job. OpenPAI can allocate multiple environments to one job to support distributed training. - -Learn more about job definition, refer to [here](docs/job_tutorial.md#write-a-job-json-configuration-file-). - -### OpenPAI client - -Rather than web portal, and [RESTful API](docs/rest-server/API.md), OpenPAI have a friendly client tool for user. It's an extension of Visual Studio Code, called [OpenPAI VS Code Client](contrib/pai_vscode/VSCodeExt.md). It can submit job, simulate job running locally, manage multiple OpenPAI environments, and so on. +[OpenPAI VS Code Client](contrib/pai_vscode/VSCodeExt.md) is a friendly, GUI based client tool of OpenPAI. It's an extension of Visual Studio Code. It can submit job, simulate job running locally, manage multiple OpenPAI environments, and so on. ### Troubleshooting job failure Web portal and job log are helpful to analyze job failure, and OpenPAI supports SSH into environment for debugging. -Refer to [here](docs/job_tutorial.md#how-to-debug-the-job-) for more information of troubleshooting job failure on OpenPAI. It's recommended to get code succeeded locally, then submit to OpenPAI. So that it doesn't need to troubleshoot code problems remotely. +Refer to [here](docs/user/troubleshooting_job.md) for more information about troubleshooting job failure. It's recommended to get code succeeded locally, then submit to OpenPAI. It reduces posibility to troubleshoot remotely. ## Administration @@ -152,7 +134,7 @@ Refer to [here](docs/job_tutorial.md#how-to-debug-the-job-) for more information ## Reference -* [Job definition](docs/job_tutorial.md#write-a-job-json-configuration-file-) +* [Job definition](docs/job_tutorial.md) * [RESTful API](docs/rest-server/API.md) * Design documents could be found [here](docs). diff --git a/contrib/pai_vscode/VSCodeExt.md b/contrib/pai_vscode/VSCodeExt.md index 221c255c32..2f05d80622 100644 --- a/contrib/pai_vscode/VSCodeExt.md +++ b/contrib/pai_vscode/VSCodeExt.md @@ -1,20 +1,22 @@ # OpenPAI VS Code Client -## Installation +OpenPAI VS Code Client can submit AI jobs, simulate job running locally, manage HDFS files, and etc. It's an extension of Visual Studio Code. + +Visual Studio Code is a popular, free, lightweight but powerful source code editor which runs on your desktop and is available for Windows, macOS and Linux. -Visual Studio Code is a free, lightweight but powerful source code editor which runs on your desktop and is available for Windows, macOS and Linux. Go to [Visual Studio Code Official Site](https://code.visualstudio.com/) to install and learn more. +## Installation -OpenPAI Client is a VS Code extension to connect PAI clusters, submit AI jobs, and manage files on HDFS, etc. You need to install the extension in VS code before using it. +1. Download and install [Visual Studio Code](https://code.visualstudio.com/) by several clicks. -To install the OpenPAI Client: +2. Install **OpenPAI Client**. -1. Launch VS Code. -2. Click the "Extensions" icon in Activity Bar or press **Ctrl+Shift+X** to bring up the Extensions view. -3. Input **openpai** in the text box, the OpenPAI VS Code Client will appear in the result list. -4. Click the **Install** button. The extension will be installed. -5. After a successful installation, you will see an introduction page. Follow the instructions there and try the PAI client. + 1. Launch VS Code. + 2. Click the "Extensions" icon in Activity Bar or press **Ctrl+Shift+X** to bring up the Extensions view. + 3. Input **openpai** in the text box, the OpenPAI VS Code Client will appear in the result list. + 4. Click the **Install** button. The extension will be installed. + 5. After a successful installation, you will see an introduction page. Follow the instructions there and try the PAI client. -![Extension](./assets/ext-install-1.png) + ![Extension](./assets/ext-install-1.png) ## Next step diff --git a/docs/images/PAI_submit_online_1.png b/docs/images/PAI_submit_online_1.png deleted file mode 100644 index eb745774ef464a7431a0df97968a8443ea52fff6..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 294283 zcmYhi1z6Kj`vy!(mw?phMmk5A(o!lNA}t`@T_YVJElfa4lm-E57%;k}YfQRBBnJED z`@aA0`*vM$UE9u1Jm-Gy-}5~8ISKl@>Li5pgcukYB$^t}3^6e9=rJ&`rSKnNU|@z; z+E=5$!1Oj$SHY+r2kfEW;5aJ3P{zQhOCdtq;G*9Xcxae-DGf+scTecRhc&KIkyZkqvbhmAjrHpHeZlTK0k ze{zEj1L9_KBJ>nQdN4O)f8y{vhLKz(w)lbrp& z9k;`8HEx!38?PT8z&Dg6sDhFwbM83q+QIZ$^I`xohv-0uCD+Te#p0;q^FoQ$AOY_k z{5dv9y@4Mnl1TRmP3V4m&{NK`z82x#AbrMJ7KGDd;0XXjub)xS;~p#7*_9ArVq%_> zp-#!j0RY!0+gg`F@^J{^m1$N*`f9g0 zCFU46@Di1{theXY+apUp*F^ZcXv$-^8(<>u4g66q03;Dn*sAru*SYQL#HY66N;hys zs`^8wL@4TB#{Uevmsx4^CnIH)!8uy`QQQFG8P$eY@b8!vo9!Y@rLD;7E8&X0*1WvEnCRFcP=To*-mSKFkhsHvw~ z;#GHaq*O6=L*V;#iLdIH#%J`LJ!Sp{-r)+|VmM z=Z)%7MaW3nNV=}z?9tH)`z#0pJOG~ehB76ZJ!I+@egIrF$bEygR^-}{fy)6;7)p6Ug6 zMofgC%SS|8&wfosFDYsyTL=n`BeUs^Ay5m})g|>6RX&@mG{wfoBQ4>}g+NHe9LHna zmYb%Ij4Mr)5ixObFXw8k$qojGdfZ|zablt_E-s4Wi70!%-)^v~jvfMbSh@X84VOFb z@pd0i(8)-xCBS2i@QwL0XF)c!+`__>w4m$Z=&zKUtz@P&vbp3SKc58%_N&?IUwb{) zHuyA~grn?iQFkAgR_jS_8Vc@{Wr{GYruyL3&&(nKV0lmNI3Guo*g^OLQM2cuQ0H|N z)cG<;`uA$h$tPs?^U_?TKUL+ZC-4JFvFfA!FYrSMObw3!KQZE^@s+aHjXuyPhzPLm zTrkg&MJ`J9jDG1Y*8ROa7AvY!7>qc(Jf}H#|B{N?s!z%7$)y6CHZ)`bHU6sf9GFnN zpKTE&!v9JNEw}4!<*2l`Dbmd8AU~fV^rq>&MtZlp&NcG#*omgsautNCjZkKfeG)H{ zWEK*_?=JuN@!UuK(DcD-ERSIxZAa(FTp1Ku2?Z%BnkJ#-=O=z{8s-^iQwVO4t^L

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[1 Diagnostic job failure reason](#job) - - [1.1 View job's launcher AM log](#amlog) - - [1.2 View job's each task container log](#tasklog) - - [1.3 Job exitStatus Convention](#exit) -- [2 Diagnostic job retried many times reason](#retry) +- [How to diagnose job problems through logs](#how-to-diagnose-job-problems-through-logs) + - [1 Diagnose job failure reason](#1-diagnose-job-failure-reason) + - [1.1 View job launcher AM log](#11-view-job-launcher-am-log) + - [1.2 View job each task container log](#12-view-job-each-task-container-log) + - [1.3 Job exitStatus Convention](#13-job-exitstatus-convention) + - [2 Diagnostic job retried many times reason](#2-diagnostic-job-retried-many-times-reason) + - [Note:](#note) -## 1 Diagnose job failure reason +## 1 Diagnose job failure reason OpenPAI job is launched by [famework launcher](../subprojects/frameworklauncher/yarn/README.md), and each task container is managed by launcher application master. @@ -16,7 +17,7 @@ LauncherAM will manage each job's tasks by customized feature requirement. You c When we diagnose job problems through logs, we shoud pay attention to job launcher AM log (get the main reason) or zoom in job task container log. -### 1.1 View job launcher AM log +### 1.1 View job launcher AM log Check the summary, and pay attention to the highlights. @@ -105,16 +106,16 @@ Log example: Please pay attention to these lines to diagnostic job failure reason -| line head | above example log info | -| --- | --- | -| [ExitDiagnostics] | ExitStatus undefined in Launcher, maybe UserApplication itself failed.| -| [ExitCode] | 134| -| Exception message | No such object: cntk-test-4621-17223-container_e9878_1532412068340_0018_01_000002. | -| Shell output | [DEBUG] EXIT signal received in yarn container, exiting ...[DEBUG] cntk-test-4621-17223-container_e9878_1532412068340_0018_01_000002 does not exist.| -|ContainerLogHttpAddress| ```http://10.151.40.165:8042/node/containerlogs/container_e9878_1532412068340_0018_01_000002/core/ ```| -|AppCacheNetworkPath|10.151.40.165:/var/lib/hadoopdata/nm-local-dir/usercache/core/appcache/application_1532412068340_0018| -|ContainerLogNetworkPath|10.151.40.165:/var/lib/yarn/userlogs/application_1532412068340_0018/container_e9878_1532412068340_0018_01_000002| -|[ApplicationCompletionReason]| [g2p_train]: FailedTaskCount 1 has reached MinFailedTaskCount 1.| +| line head | above example log info | +| ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | +| [ExitDiagnostics] | ExitStatus undefined in Launcher, maybe UserApplication itself failed. | +| [ExitCode] | 134 | +| Exception message | No such object: cntk-test-4621-17223-container_e9878_1532412068340_0018_01_000002. | +| Shell output | [DEBUG] EXIT signal received in yarn container, exiting ...[DEBUG] cntk-test-4621-17223-container_e9878_1532412068340_0018_01_000002 does not exist. | +| ContainerLogHttpAddress | ```http://10.151.40.165:8042/node/containerlogs/container_e9878_1532412068340_0018_01_000002/core/ ``` | +| AppCacheNetworkPath | 10.151.40.165:/var/lib/hadoopdata/nm-local-dir/usercache/core/appcache/application_1532412068340_0018 | +| ContainerLogNetworkPath | 10.151.40.165:/var/lib/yarn/userlogs/application_1532412068340_0018/container_e9878_1532412068340_0018_01_000002 | +| [ApplicationCompletionReason] | [g2p_train]: FailedTaskCount 1 has reached MinFailedTaskCount 1. | we could get information: 1. UserApplication itself failed. @@ -122,7 +123,7 @@ we could get information: 3. Then we could visit ```http://10.151.40.165:8042/node/containerlogs/container_e9878_1532412068340_0018_01_000002/core/``` at step 1.2 to detect task failure reason. -### 1.2 View job each task container log +### 1.2 View job each task container log - Check the failed task log who triggered the whole attempt failed, i.e. @@ -134,11 +135,11 @@ ContainerLogHttpAddress: ![PAI_job_retry](./images/PAI_job_retry.png) -### 1.3 Job exitStatus Convention +### 1.3 Job exitStatus Convention You can check all the defined ExitStatus by: ExitType, ExitDiagnostics from framework launcher [USERMANUAL.md](../subprojects/frameworklauncher/yarn/doc/USERMANUAL.md#ExitStatus_Convention) -## 2 Diagnostic job retried many times reason +## 2 Diagnostic job retried many times reason If the Framework retried many times, check other attempts by searching the FrameworkName in the YARN Web: diff --git a/docs/job_tutorial.md b/docs/job_tutorial.md index 73c31de6d0..375cdb7bf1 100644 --- a/docs/job_tutorial.md +++ b/docs/job_tutorial.md @@ -17,42 +17,28 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. --> - -# How to Run a Deep Learning Job +# Job reference OpenPAI supports major deep learning frameworks, including CNTK and TensorFlow, etc. It also supports other type of job through a customized docker image. Users need to prepare a config file and submit it for a job submission. This guide introduces the details of job submission. -## Table of Contents: - -- [Quick start: how to write and submit a CIFAR-10 job](#quickstart) -- [Write a customized job](#writejob) - - [Prerequisites](#prerequisites) - - [Use docker to package the job environment dependencies](#docker) - - [Write a job json configuration file](#jobjson) - - [Job runtime environmental variable](#envvar) - - [A deep learning job example](#example) - - [Job submission steps](#submission) -- [How to debug Job](#debug) -- [Learn more job examples](#moreexample) - -## Quick start: how to write and submit a CIFAR-10 job - -Please refer to this [document](../examples/README.md#quickstart) for how to write and submit a CIFAR-10 job. +- [Job reference](#job-reference) + - [Quick start: submit a hello-world job](#quick-start-submit-a-hello-world-job) + - [Job configuration](#job-configuration) + - [Specification](#specification) + - [Environment variables](#environment-variables) + - [A complete example](#a-complete-example) + - [Learn more job examples](#learn-more-job-examples) -## Write a customized job +## Quick start: submit a hello-world job -### Prerequisites +Refer to [submit a hello-world job](user/training.md#submit-a-hello-world-job) firstly. It's a good start for beginners. -This guide assumes the system has already been deployed properly and a docker registry is available to store docker images. +## Job configuration -### Use docker to package the job environment dependencies - -OpenPAI packaged the docker env required by the job for user to use. User could refer to [job_docker_env.md](./job_docker_env.md) to customize example's docker env. If user have built a customized image and pushed it to Docker Hub, replace our pre-built image in following example `"image": "your_docker_registry/pai.run.tensorflow"` with your own. OpenPAI has many pre-built images for different frameworks. In [Learn more job examples](#moreexample) section, each example folder will contain a pre-build docker env. - -### Write a job json configuration file +### Specification A json file describe detailed configuration required for a job submission. The detailed format is shown as below: @@ -131,7 +117,7 @@ For more details on explanation, please refer to [frameworklauncher usermanual]( If you're using a private Docker registry which needs authentication for image pull and is different from the registry used during deployment, please create an authentication file in the following format, upload it to HDFS and specify the path in `authFile` parameter in config file. -``` +```text docker_registry_server username password @@ -143,7 +129,7 @@ password - Only **codeDir** will created to your job container local environment and could be accessed inner job container. dataDir & outputDir are environmental variable (For example, the file link url of hdfs) which will be used by your job inner training code to read data from the storage link. -### Job runtime environmental variable +### Environment variables Each task in a job runs in one Docker container. For a multi-task job, one task might communicate with others. @@ -154,24 +140,23 @@ Those environment variables can also be used in the job config file. Below we show a complete list of environment variables accessible in a Docker container: -| Category | Environment Variable Name | Description | -| :---------------- | :---------------------------------------- | :---------------------------------------------------------- | -| Job level | PAI_JOB_NAME | `jobName` in config file | -| | PAI_USER_NAME | User who submit the job | -| | PAI_DEFAULT_FS_URI | Default file system uri in PAI | -| Task role level | PAI_TASK_ROLE_COUNT | Total task roles' number in config file | -| | PAI_TASK_ROLE_LIST | Comma separated all task role names in config file | -| | PAI_TASK_ROLE_TASK_COUNT\_`$taskRole` | Task count of the task role | -| | PAI_HOST_IP\_`$taskRole`\_`$taskIndex` | The host IP for `taskIndex` task in `taskRole` | -| | PAI_PORT_LIST\_`$taskRole`\_`$taskIndex`\_`$portType` | The `$portType` port list for `taskIndex` task in `taskRole` | -| | PAI_RESOURCE\_`$taskRole` | Resource requirement for the task role in "gpuNumber,cpuNumber,memMB,shmMB" format | -| | PAI_MIN_FAILED_TASK_COUNT\_`$taskRole` | `taskRole.minFailedTaskCount` of the task role | -| | PAI_MIN_SUCCEEDED_TASK_COUNT\_`$taskRole` | `taskRole.minSucceededTaskCount` of the task role | -| Current task role | PAI_CURRENT_TASK_ROLE_NAME | `taskRole.name` of current task role | -| Current task | PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX | Index of current task in current task role, starting from 0 | - - -### A deep learning job example +| Category | Environment Variable Name | Description | +| :---------------- | :---------------------------------------------------- | :--------------------------------------------------------------------------------- | +| Job level | PAI_JOB_NAME | `jobName` in config file | +| | PAI_USER_NAME | User who submit the job | +| | PAI_DEFAULT_FS_URI | Default file system uri in PAI | +| Task role level | PAI_TASK_ROLE_COUNT | Total task roles' number in config file | +| | PAI_TASK_ROLE_LIST | Comma separated all task role names in config file | +| | PAI_TASK_ROLE_TASK_COUNT\_`$taskRole` | Task count of the task role | +| | PAI_HOST_IP\_`$taskRole`\_`$taskIndex` | The host IP for `taskIndex` task in `taskRole` | +| | PAI_PORT_LIST\_`$taskRole`\_`$taskIndex`\_`$portType` | The `$portType` port list for `taskIndex` task in `taskRole` | +| | PAI_RESOURCE\_`$taskRole` | Resource requirement for the task role in "gpuNumber,cpuNumber,memMB,shmMB" format | +| | PAI_MIN_FAILED_TASK_COUNT\_`$taskRole` | `taskRole.minFailedTaskCount` of the task role | +| | PAI_MIN_SUCCEEDED_TASK_COUNT\_`$taskRole` | `taskRole.minSucceededTaskCount` of the task role | +| Current task role | PAI_CURRENT_TASK_ROLE_NAME | `taskRole.name` of current task role | +| Current task | PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX | Index of current task in current task role, starting from 0 | + +### A complete example A distributed TensorFlow job is listed below as an example: @@ -244,63 +229,6 @@ A distributed TensorFlow job is listed below as an example: } ``` -### Job submission steps - -1. Put the code and data on [HDFS](../docs/hadoop/hdfs.md) - -- Option-1: Use [WebHDFS](../docs/hadoop/hdfs.md#WebHDFS-) to upload your code and data to HDFS on the system. -- Option-2: Use [HDFS cmd](../docs/hadoop/hdfs.md#hdfs-command-) to upload your code and data to HDFS on the system. We upload a [Docker image](https://hub.docker.com/r/paiexample/pai.example.hdfs/) to DockerHub with built-in HDFS support. - Please refer to the [HDFS commands guide](https://hadoop.apache.org/docs/r2.7.2/hadoop-project-dist/hadoop-hdfs/HDFSCommands.html) for details. - -2. Prepare a job config file - - Prepare the [config file](#jobjson) for your job. - -3. [Submit the job through web portal](submit_from_webportal.md) - - Open web portal in a browser, click "Submit Job" and upload your config file. - - Note: For other job submission methods. Please refer [doc](../README.md#how-to-train-jobs) - -## How to debug the job - -### (1) From OpenPAI web page to debug job - -Please refer doc [How to diagnose job problems through logs](job_log.md) - -### (2) SSH to job container and debug job -You can ssh connect to a specified container either from outside or inside container. - -#### SSH connect from outside - -1. Get job ssh connect info by invoking [Get job SSH info](rest-server/API.md#get-userusernamejobsjobnamessh) api or clicking the job detail page on webportal. - -2. Open a Bash shell terminal. - -3. Download the corresponding private key from HDFS. - For example, with [wget](http://www.gnu.org/software/wget/), you can execute below command line: - ```sh - wget http://host:port/webhdfs/v1/Container/userName/jobName/ssh/keyFiles/userName~jobName?op=OPEN -O userName~jobName - ``` -4. Use `chmod` command to set correct permission for the key file. - ```sh - chmod 400 userName~jobName - ``` -5. Use `ssh` command to connect into container. for example - ```sh - ssh -i userName~jobName -p ssh_port root@container_ip - ``` -#### SSH connect inside containers - -You can use `ssh $PAI_CURRENT_TASK_ROLE_NAME-$PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX` command to connect into another containers which belong to the same job. For example, if there are two taskRoles: master and worker, you can connect to worker-0 container directly with below command line: -```sh -ssh worker-0 -``` - -### (3) Job Profiling - -Users can view the resource cost and bottlenecks of various metrics of the job by following the [job profiling doc](job_profiling.md). - -## Learn more job examples +## Learn more job examples For more examples, please refer to [job examples directory](../examples). diff --git a/docs/rest-server/API.md b/docs/rest-server/API.md index 5995dd9788..9356b7bfa9 100644 --- a/docs/rest-server/API.md +++ b/docs/rest-server/API.md @@ -2,7 +2,7 @@ 1. Job config file - Prepare a job config file as described in [examples/README.md](../job_tutorial.md#json-config-file-for-job-submission), for example, `exampleJob.json`. + Prepare a job config file as described [here](../user/training.md), for example, `exampleJob.json`. 2. Authentication @@ -508,7 +508,7 @@ Authorization: Bearer *Parameters* -[job config json](../job_tutorial.md#json-config-file-for-job-submission) +[job config json](../job_tutorial.md) *Response if succeeded* ``` @@ -1019,4 +1019,4 @@ the version upgrade, which has no namespaces. They are called "legacy jobs", whi but cannot be created. To figure out them, there is a "legacy: true" field of them in list apis. In the next versions, all operations of legacy jobs may be disabled, so please re-create them as namespaced -job as soon as possible. \ No newline at end of file +job as soon as possible. diff --git a/docs/submit_from_webportal.md b/docs/submit_from_webportal.md deleted file mode 100644 index e70c1337a7..0000000000 --- a/docs/submit_from_webportal.md +++ /dev/null @@ -1,20 +0,0 @@ -# Submit a job in web portal - -1. At PAI home page, click the top right corner to login: - -![](./images/PAI_submit_online_1.png) - - -2. At the left sidebar, click "Submit Job": - -![](./images/PAI_submit_online_2.png) - - -3. You can import your job configuration json file, or you can fill the job configurations in the webportal's table online. How to write the configuration please refer to [write job from scratch](./job_tutorial.md#json-config-file-for-job-submission). - -![image.png](./images/PAI_submit_online_3.png) - - -4. 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zcPe_F#A{_#itZTAj<)jQDBOeH<_o-kesuNnv9HLreMnS_ZVmw!bt0%oDo zH8q}2A{f-Z5Ys(ThqT4I^TIFE|AWCU^pQ4twl6viYJIJT9>d5opZqh@FhwTtE`I74 zr0@1$#1j6M#RGaafU*CeFKj>=pKi4TlX!smi~j5X4X1QT+TCyZRXUTwRlW4PkMj?| z<;EnSapfcQa}X6cs0Z<<41!mTKNc1icI%1BA1Vw1dufy&25QtfK!g79L&{%)Kuwdy zi{6fL_%dZss!15&Px|wI1Khj9G`!wx1Mu+SU;k9`r*HoCtpa}F) z?X?P%NT@(qx&o$n@Ngy7BB(f9WJMfKZ^HI~Vmq}>UllXaN{KE6WII4J_*r2CCq$mj zFnQi$P%dXV-6%*-`%vvI{Ee1rDQrElH4GR$hR^men9U{a17AM+QUrp+k#Y!b?KG6u zHMQ6E4p7oLH@kM!TCQ#GM9n9_dTNBAZBpM$3W~S4^7$z(UmILX1-H+;xy<$oKJ5Yy xwzRL7Q7n^tv5$>sai`gKuNiW2@htU#@%$W{)g9H_0rWZ0RMWeUy!R;Ne*g{HG=u;E literal 0 HcmV?d00001 diff --git a/docs/user/training.md b/docs/user/training.md new file mode 100644 index 0000000000..f7756063e4 --- /dev/null +++ b/docs/user/training.md @@ -0,0 +1,161 @@ + + +# Train models on OpenPAI + +- [Train models on OpenPAI](#train-models-on-openpai) + - [Submit a hello-world job](#submit-a-hello-world-job) + - [Understand job](#understand-job) + - [Learn hello-world job](#learn-hello-world-job) + - [Exchange data](#exchange-data) + - [Job workflow](#job-workflow) + - [Reference](#reference) + +This document is for beginners, who use OpenPAI to train machine learning models or execute other commands. + +It assumes that you know IP address or domain name and have an account of OpenPAI. If there isn't an OpenPAI cluster yet, refer to [here](../../README.md#deploy-openpai) to deploy one. + +## Submit a hello-world job + +The **job** of OpenPAI defines how to execute command(s) in specified environment(s). A job can be model training, other kinds of commands, or distributed on multiple servers. + +Following this section to submit a very simple job like hello-world during learning a program language. It trains a model, which is implemented by TensorFlow, on CIFAR-10 dataset. It downloads data and code from internet and doesn't copy model out. It helps getting started with OpoenPAI. Next sections include more details to help on submitting real jobs. + +1. Navigate to OpenPAI web portal. Input IP address or domain name of OpenPAI, which is from administrator of the OpenPAI cluster. If it doesn't require to login, click *login* link at top right side and input user/password. + + After that, OpenPAI will show dashboard as below. + + ![dashboard](imgs/web_dashboard.png) + +2. Click **Submit Job** on the left pane and reach this page. + + ![submit job](imgs/web_submit_job.png) + +3. Click **JSON** button. Clear existing content and paste below content in the popped text box, then click save. + + The content is introduced in next sections. + + ```json + { + "jobName": "tensorflow-cifar10", + "image": "ufoym/deepo:tensorflow-py36-cu90", + "taskRoles": [ + { + "name": "default", + "taskNumber": 1, + "cpuNumber": 4, + "memoryMB": 8192, + "gpuNumber": 1, + "command": "git clone https://github.com/tensorflow/models && cd models/research/slim && python download_and_convert_data.py --dataset_name=cifar10 --dataset_dir=/tmp/data && python train_image_classifier.py --dataset_name=cifar10 --dataset_dir=/tmp/data --max_number_of_steps=1000" + } + ] + } + ``` + + ![paste job](imgs/web_paste_json.png) + +4. It will show as below. Click **Submit** button to submit the job to OpenPAI platform. + + ![click submit job](imgs/web_click_submit_job.png) + + **Note**, Web portal is one of ways to submit jobs. It's not most efficient way, but simplest way to begin. [OpenPAI VS Code Client](../../contrib/pai_vscode/VSCodeExt.md) is recommended to work with OpenPAI. + +5. After submitted, the page redirects to job list, and the submitted job is in list as **waiting** status. Click **Jobs** on right pane can also reach this page. + + ![job list](imgs/web_job_list.png) + +6. Click job name to view job details. Keep refreshing the details page, until job status is changed to *Running*, and IP address is assigned in below pane of task role. There are more details and actions, like status, tracking log and so on. + + ![job list](imgs/web_job_details.png) + +## Understand job + +With submitting a hello-world job, this section introduces more knowledge about job, so that you can write your own job configuration easily. + +### Learn hello-world job + +The **job configuration** is a JSON file, which is posted to OpenPAI. Here uses the hello-world job configuration to understand key fields. + +The JSON file of job has two levels entries. The top level includes shared information of the job, including job name, docker image, task roles, and so on. The second level is taskRoles, it's an array. Each item in the array specifies commands and the corresponding running environment. + +Below is key part of all fields and [full spec of job configuration](../job_tutorial.md) is here. + +- **jobName** is the unique name of current job, displays in web also. A meaningful name helps managing jobs well. + +- **image** + + OpenPAI uses [docker](https://www.docker.com/why-docker) to provide runtime environments. Docker is a popular technology to provide isolated environments on the same server. So that OpenPAI can serve multiple resource requests on the same server and provides consistent clean environments. + + The **image** field is the identity of docker image, which includes customized Python and system packages, to provide a clean and consistent environment for each running. + + Administrator may set a private docker repository. The hub.docker.com is a public docker repository with a lot of docker images. The [ufoym/deepo](https://hub.docker.com/r/ufoym/deepo) on hub.docker.com is recommended for deep learning. In the hello-world example, it uses a TensorFlow image, *ufoym/deepo:tensorflow-py36-cu90*, from ufoym/deepo. + + If an appropriate docker image isn't found, it's not difficult to [build a docker image](../job_docker_env.md) from scratch. + + Note, if a docker image doesn't include *openssh-server* and *curl* components by default, it cannot use SSH feature of OpenPAI. If SSH is needed, another docker image can be built on top of this image and includes *openssh-server* and *curl*. + +- **taskRoles** defines different roles in a job. + + For single machine jobs, there is only one item in taskRoles. + + For distributed jobs, there may be multiple roles in taskRoles. For example, when TensorFlow is used to running distributed job, it has two roles, including parameter server and worker. There are two task roles in the corresponding job configuration, refer to [an example](../job_tutorial.md#a-complete-example). + +- **taskRoles/name** is the name of current task role and it's used in environment variables for communication in distributed jobs. + +- **taskRoles/taskNumber** is number of current task instances. For single server jobs, it should be 1. For distributed jobs, it depends on how many instances are needed for this task role. For example, if it's 8 in a worker role of TensorFlow. It means there should be 8 docker containers as workers should be instantiated for this task. + +- **taskRoles/cpuNumber**, **taskRoles/memoryMB**, **taskRoles/gpuNumber** are easy to understand. They specify corresponding hardware resources including count of CPU core, MB of memory, and count of GPU. + +- **taskRoles/command** is what user want to run in this task role. It can be multiple commands, which are joint by `&&` like in terminal. In the hello-world job configuration, it clones code from GitHub, downloads data and then executes the training progress within one line. + + Like the hello-world job, user needs to construct command(s) to get code, data and trigger executing. + +### Exchange data + +The data here doesn't only mean *dataset* of machine learning, also includes all files and information, like code, scripts, trained model, and so on. Most model training and other kinds of jobs need to exchange data between docker container and outside. + +OpenPAI creates a clean docker container. Some data can be built into docker image directly if it's changed rarely. + +If it needs to exchange data on runtime, the command, which passes to docker in job configuration, needs to initiate the data exchange progress. For example, use `git`, `wget`, `scp`, `sftp` or other commands to copy data in and out. If some command is not built in docker, it can be installed in the command by `apt install` or `python -m pip install`. + +It's better to check with administrator of the OpenPAI cluster, since there may be suggested approaches and examples already. + +### Job workflow + +Once job configuration is ready, next step is to submit it to OpenPAI. To submit a job, the recommended way is to use [Visual Studio Code extension for OpenPAI](../../contrib/pai_vscode/VSCodeExt.md). Both web UI and extension through [RESTful API of OpenPAI](../rest-server/API.md) to manage jobs. So, it's possible to implement your own script or tool. + +After received job configuration, OpenPAI processes it as below steps. + +1. Wait to allocate resource. As job configuration, OpenPAI waits enough resources including CPU, memory, and GPU are allocated. If there is enough resource, the job starts to run very soon. If there is not enough resource, job is queued and wait previous job to complete. + + Note, distributed jobs start to run when first environment is ready. But user code can still wait until enough container(s) are running to execute actual progress. The job status is set to *Running* on OpenPAI as well, once one container is running. + +2. Initialize docker container. OpenPAI pulls the docker image, which is specified in configuration, if it doesn't exist locally. After docker container started, OpenPAI executes some initialization and then run user's command(s). + +3. Execute user commands. During user command executing, OpenPAI outputs [stdout and stderr](troubleshooting_job.md) near real-time. There also are metrics to [monitor workload](../job_profiling.md). + +4. Finalize job running. Once user's command completed. OpenPAI use latest exit code as signal to decide the job is success or not. 0 means success, others mean failure. Then OpenPAI recycles resource for next job. + +When job is submitted to OpenPAI, user can see job's status changing from waiting, to running, then to succeeded or failed. It may be stopped if the job is interrupted by user or system. + +## Reference + +- [Full spec of job configuration](../job_tutorial.md) +- [Examples](../../examples) +- [Troubleshooting job failure](troubleshooting_job.md) diff --git a/docs/user/troubleshooting_job.md b/docs/user/troubleshooting_job.md new file mode 100644 index 0000000000..c4efecef44 --- /dev/null +++ b/docs/user/troubleshooting_job.md @@ -0,0 +1,67 @@ + + +# Troubleshoot job failure + +## How to debug a job + +1. From OpenPAI web page to debug job + + Please refer doc [How to diagnose job problems through logs](../job_log.md) + +1. SSH to job container and debug job + + You can ssh connect to a specified container either from outside or inside container. + + - SSH connect from outside + + 1. Get job ssh connect info by invoking [Get job SSH info](../rest-server/API.md#get-userusernamejobsjobnamessh) api or clicking the job detail page on webportal. + + 2. Open a Bash shell terminal. + + 3. Download the corresponding private key from HDFS. + For example, with [wget](http://www.gnu.org/software/wget/), you can execute below command line: + + ```sh + wget http://host:port/webhdfs/v1/Container/userName/jobName/ssh/keyFiles/userName~jobName?op=OPEN -O userName~jobName + ``` + + 4. Use `chmod` command to set correct permission for the key file. + + ```sh + chmod 400 userName~jobName + ``` + + 5. Use `ssh` command to connect into container. for example + + ```sh + ssh -i userName~jobName -p ssh_port root@container_ip + ``` + + - SSH connect inside containers + + You can use `ssh $PAI_CURRENT_TASK_ROLE_NAME-$PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX` command to connect into another containers which belong to the same job. For example, if there are two taskRoles: master and worker, you can connect to worker-0 container directly with below command line: + + ```sh + ssh worker-0 + ``` + +1. Job Profiling + + Users can view the resource cost and bottlenecks of various metrics of the job by following the [job profiling doc](../job_profiling.md). diff --git a/docs/webportal/README.md b/docs/webportal/README.md index f7f0e4ac9d..0f111bff66 100644 --- a/docs/webportal/README.md +++ b/docs/webportal/README.md @@ -101,7 +101,7 @@ To run web portal on system, a [Node.js](https://nodejs.org/) 6+ runtime is requ ### Submit a job -Click the tab "Submit Job" to show a button asking you to select a json file for the submission. The job config file must follow the format shown in [job tutorial](../job_tutorial.md). +Click the tab "Submit Job" to show a button asking you to select a json file for the submission. The job config file must follow the format shown in [submit a hello-world job](../user/training.md). ### View job status diff --git a/examples/README.md b/examples/README.md index b29e2d45d2..25daabb3f3 100644 --- a/examples/README.md +++ b/examples/README.md @@ -1,59 +1,15 @@ # OpenPAI Job Examples -## Table of Contents -- [Quick start: how to write and submit a CIFAR-10 job](#quickstart) -- [List of off-the-shelf examples](#offtheshelf) -- [List of customized job template](#customize) -- [What if the example is failed](#debug) -- [Contributing](#contributing) - -## Quick start: how to write and submit a CIFAR-10 job - -#### (1) Prepare a job json file - -In this section, we will use CIFAR-10 training job as an example to explain how to write and submit a job in OpenPAI. - -[CIFAR-10](http://www.cs.toronto.edu/~kriz/cifar.html) is an established computer-vision dataset used for image classification. - -- Full example for tensorflow cifar10 image classification training on OpenPAI: - -```js -{ - // Name for the job, need to be unique - "jobName": "tensorflow-cifar10", - // URL pointing to the Docker image for all tasks in the job - "image": "openpai/pai.example.tensorflow", - // Data directory existing on HDFS - "dataDir": "/tmp/data", - // Output directory on HDFS, - "outputDir": "/tmp/output", - // List of taskRole, one task role at least - "taskRoles": [ - { - // Name for the task role - "name": "cifar_train", - // Number of tasks for the task role, no less than 1 - "taskNumber": 1, - // CPU number for one task in the task role, no less than 1 - "cpuNumber": 8, - // Memory for one task in the task role, no less than 100 - "memoryMB": 32768, - // GPU number for one task in the task role, no less than 0 - "gpuNumber": 1, - // Executable command for tasks in the task role, can not be empty - "command": "git clone https://github.com/tensorflow/models && cd models/research/slim && python download_and_convert_data.py --dataset_name=cifar10 --dataset_dir=$PAI_DATA_DIR && python train_image_classifier.py --batch_size=64 --model_name=inception_v3 --dataset_name=cifar10 --dataset_split_name=train --dataset_dir=$PAI_DATA_DIR --train_dir=$PAI_OUTPUT_DIR" - } - ] -} -``` - -- Save content to a file. Name this file as cifar10.json - -- [Job configuration items introduction](../docs/job_tutorial.md#json-config-file-for-job-submission) - -#### (2) Submit job json file from OpenPAI webportal - -Users can refer to this tutorial [submit a job in web portal](https://github.com/Microsoft/pai/blob/master/docs/submit_from_webportal.md) for job submission from OpenPAI webportal. +- [OpenPAI Job Examples](#openpai-job-examples) + - [Quick start: submit a hello-world job](#quick-start-submit-a-hello-world-job) + - [List of off-the-shelf examples ](#list-of-off-the-shelf-examples-a-name%22offtheshelf%22a) + - [List of customized job template ](#list-of-customized-job-template-a-name%22customize%22a) + - [What if the example is failed ](#what-if-the-example-is-failed-a-name%22debug%22a) + - [Contributing](#contributing) + +## Quick start: submit a hello-world job + +Refer to [how to submit a hello-world job](../docs/user/training.md#submit-a-hello-world-job). It's a good start for beginners. ## List of off-the-shelf examples @@ -108,7 +64,7 @@ The example in the folder could be failed due to the following reasons: 3. If the example you submit contains a prepare.sh script shell, it may fail due to the source of the data or code changed or been unstable. You may get error in your job tracking page. Check and try to fix it. 4. The version of the code, tools or library. You may get this error if you rebuild the docker image. Some example doesn't fix the version of its dependency, so, you should check the version. -## Contributing +## Contributing If you want to contribute a job example that can be run on PAI, please open a new pull request. @@ -124,7 +80,3 @@ If you want to contribute a job example that can be run on PAI, please open a ne 2. Dockerfile: Example's dependencies 3. Pai job json file: Example's OpenPAI job json template 4. [Optional] Code file: Example's code file - - - - diff --git a/examples/XGBoost/README.md b/examples/XGBoost/README.md index e0e66c2038..0ea770599e 100644 --- a/examples/XGBoost/README.md +++ b/examples/XGBoost/README.md @@ -50,4 +50,4 @@ Here's one configuration file example to train a model on the [forest cover type } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/azure-rdma-inte-mpi-benchmark-with-horovod-image/README.md b/examples/azure-rdma-inte-mpi-benchmark-with-horovod-image/README.md index 768fe8fbd4..38ee9673e7 100644 --- a/examples/azure-rdma-inte-mpi-benchmark-with-horovod-image/README.md +++ b/examples/azure-rdma-inte-mpi-benchmark-with-horovod-image/README.md @@ -65,11 +65,11 @@ Users should prepare their own intel mpi licences to build the docker image. Whe } ``` -- For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +- For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). - Sleep 1000 in ```master-0``` is a hack to ensure that all work containers are ready. You could optimize it in a better way. For example try to ssh all the work containers with the hostanme ```${taskname}-${taskid}``` until sccessful. - If user wanna a AZ-RDMA capable container. The following parameter is necessary. ```bash "jobEnvs": { "paiAzRDMA": true } -``` \ No newline at end of file +``` diff --git a/examples/caffe/README.md b/examples/caffe/README.md index 7a21355209..7370a2d2de 100644 --- a/examples/caffe/README.md +++ b/examples/caffe/README.md @@ -49,5 +49,4 @@ Here's one configuration file example: ] } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). - +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/caffe2/README.md b/examples/caffe2/README.md index 38587add32..043a91a888 100644 --- a/examples/caffe2/README.md +++ b/examples/caffe2/README.md @@ -49,4 +49,4 @@ Here's one configuration file example: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/chainer/README.md b/examples/chainer/README.md index 69fa252a0c..5c46855a01 100644 --- a/examples/chainer/README.md +++ b/examples/chainer/README.md @@ -54,4 +54,4 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/cntk/README.md b/examples/cntk/README.md index 5aff4dfd5e..f81dcb32b8 100644 --- a/examples/cntk/README.md +++ b/examples/cntk/README.md @@ -66,4 +66,4 @@ Here're some configuration file examples, pay attention to the codeDir/dataDir/o When the job finished and succeeded, you can get the output of the example from HDFS:`hdfs dfs -get hdfs://ip:port/examples/cntk/output`. -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/horovod-with-azure-rdma-intel-mpi/README.md b/examples/horovod-with-azure-rdma-intel-mpi/README.md index a097f0d391..1a214f3e73 100644 --- a/examples/horovod-with-azure-rdma-intel-mpi/README.md +++ b/examples/horovod-with-azure-rdma-intel-mpi/README.md @@ -65,11 +65,11 @@ Users should prepare their own intel mpi licences to build the docker image. Whe } ``` -- For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +- For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). - Sleep 1000 in ```master-0``` is a hack to ensure that all work containers are ready. You could optimize it in a better way. For example try to ssh all the work containers with the hostanme ```${taskname}-${taskid}``` until sccessful. - If user wanna a AZ-RDMA capable container. The following parameter is necessary. ```bash "jobEnvs": { "paiAzRDMA": true } -``` \ No newline at end of file +``` diff --git a/examples/horovod/README.md b/examples/horovod/README.md index e83dedcf91..e3b1cca0a3 100644 --- a/examples/horovod/README.md +++ b/examples/horovod/README.md @@ -78,4 +78,4 @@ Here is a configuration file example: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/jupyter/README.md b/examples/jupyter/README.md index 83f5ee573d..4a62ce1362 100644 --- a/examples/jupyter/README.md +++ b/examples/jupyter/README.md @@ -59,7 +59,7 @@ Here's one configuration file example to use Jupyter Notebook as a tutorial to r } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ### Access Jupyter Notebook diff --git a/examples/keras/README.md b/examples/keras/README.md index f9f9cf8172..b907c275e1 100644 --- a/examples/keras/README.md +++ b/examples/keras/README.md @@ -70,7 +70,7 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ### Note: diff --git a/examples/mpi/README.md b/examples/mpi/README.md index 9d1f55effc..f7d6bd40b5 100644 --- a/examples/mpi/README.md +++ b/examples/mpi/README.md @@ -27,8 +27,15 @@ The following contents show some basic Open MPI examples, other customized MPI c ## Contents -1. [Open MPI TensorFlow CIFAR-10 example](#open-mpi-tensorflow-cifar-10-example) -2. [Open MPI CNTK grapheme-to-phoneme conversion example](#open-mpi-cntk-grapheme-to-phoneme-conversion-example) +- [Note](#note) +- [MPI on OpenPAI](#mpi-on-openpai) + - [Contents](#contents) +- [Open MPI TensorFlow / CNTK CIFAR-10 example](#open-mpi-tensorflow--cntk-cifar-10-example) + - [Prepare work](#prepare-work) + - [Open MPI TensorFlow CIFAR-10 example](#open-mpi-tensorflow-cifar-10-example) + - [TensorFlow cifar10 benchmark](#tensorflow-cifar10-benchmark) + - [Open MPI CNTK grapheme-to-phoneme conversion example](#open-mpi-cntk-grapheme-to-phoneme-conversion-example) + - [CNTK G2P example](#cntk-g2p-example) # Open MPI TensorFlow / CNTK CIFAR-10 example @@ -129,4 +136,4 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/mxnet/README.md b/examples/mxnet/README.md index bb82824287..ad6469c09f 100644 --- a/examples/mxnet/README.md +++ b/examples/mxnet/README.md @@ -25,8 +25,13 @@ The following contents show some basic MXNet examples, other customized MXNet co ## Contents -1. [MXNet autoencoder examples](#mxnet-autoencoder-examples) -2. [MXNet image classification examples](#mxnet-image-classification-examples) +- [Apache MXNet on PAI](#apache-mxnet-on-pai) + - [Contents](#contents) + - [MXNet autoencoder examples](#mxnet-autoencoder-examples) + - [autoencoder](#autoencoder) + - [MXNet image classification examples](#mxnet-image-classification-examples) + - [image classification](#image-classification) + - [Note:](#note) ## MXNet autoencoder examples @@ -75,7 +80,7 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ### Note: diff --git a/examples/ocr-serving/README.md b/examples/ocr-serving/README.md index 4c8dd2fe9b..9e5ca081cd 100644 --- a/examples/ocr-serving/README.md +++ b/examples/ocr-serving/README.md @@ -90,7 +90,7 @@ The full OCR job description is shown as below: } ``` *For more details on how to write a job configuration file, -please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission).* +please refer to [job tutorial](../../docs/user/training.md).* After submitting this job, it might take few mins for OpenPAI to load docker image and deploy the service. @@ -99,11 +99,3 @@ After submitting this job, it might take few mins for OpenPAI to load docker ima OpenPAI will dynamic allocate resources, IP and Port for jobs. Dynamic allocated IP and Port can be found in the job detail page, with which users could access the web-server - - - - - - - - diff --git a/examples/pytorch/README.md b/examples/pytorch/README.md index 26a6456c51..ab501f1304 100644 --- a/examples/pytorch/README.md +++ b/examples/pytorch/README.md @@ -26,8 +26,13 @@ The following contents show some basic PyTorch examples, other customized PyTorc ## Contents -1. [PyTorch MNIST digit recognition](#pytorch-mnist-digit-recognition-examples) -2. [PyTorch regression examples](#pytorch-regression-examples) +- [PyTorch on OpenPAI](#pytorch-on-openpai) + - [Contents](#contents) + - [PyTorch MNIST digit recognition examples](#pytorch-mnist-digit-recognition-examples) + - [mnist](#mnist) + - [PyTorch regression examples](#pytorch-regression-examples) + - [regression](#regression) + - [Note:](#note) ## PyTorch MNIST digit recognition examples @@ -75,7 +80,7 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ## Note: diff --git a/examples/scikit-learn/README.md b/examples/scikit-learn/README.md index b519a6f003..27db151515 100644 --- a/examples/scikit-learn/README.md +++ b/examples/scikit-learn/README.md @@ -26,8 +26,13 @@ The following contents show some basic scikit-learn examples, other customized s ## Contents -1. [scikit-learn MNIST digit recognition example](#scikit-learn-mnist-digit-recognition-example) -2. [scikit-learn text-vectorizers example](#scikit-learn-text-vectorizers-example) +- [scikit-learn on OpenPAI](#scikit-learn-on-openpai) + - [Contents](#contents) + - [scikit-learn MNIST digit recognition example](#scikit-learn-mnist-digit-recognition-example) + - [mnist](#mnist) + - [scikit-learn text-vectorizers example](#scikit-learn-text-vectorizers-example) + - [text-vectorizers](#text-vectorizers) + - [Note:](#note) ## scikit-learn MNIST digit recognition example @@ -75,7 +80,7 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ### Note: diff --git a/examples/serving/README.md b/examples/serving/README.md index 9b9de3a177..5ab9f22b81 100644 --- a/examples/serving/README.md +++ b/examples/serving/README.md @@ -58,5 +58,4 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). - +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). diff --git a/examples/tensorflow/README.md b/examples/tensorflow/README.md index 72ab8d2020..ab5bb52d4b 100644 --- a/examples/tensorflow/README.md +++ b/examples/tensorflow/README.md @@ -26,11 +26,15 @@ The following contents show some basic TensorFlow examples, other customized Ten ## Contents -1. [TensorFlow CIFAR-10 image classification](#tensorflow-cifar-10-image-classification) -2. [TensorFlow ImageNet image classification](#tensorflow-imagenet-image-classification) -3. [Distributed TensorFlow CIFAR-10 image classification](#distributed-tensorflow-cifar-10-image-classification ) -4. [TensorFlow Tensorboard](#tensorflow-tensorboard) -5. [Note](#Note) +- [TensorFlow on OpenPAI](#tensorflow-on-openpai) + - [Contents](#contents) +- [TensorFlow examples](#tensorflow-examples) + - [Prepare work](#prepare-work) + - [TensorFlow CIFAR-10 image classification](#tensorflow-cifar-10-image-classification) + - [TensorFlow ImageNet image classification](#tensorflow-imagenet-image-classification) + - [Distributed TensorFlow CIFAR-10 image classification](#distributed-tensorflow-cifar-10-image-classification) + - [TensorFlow Tensorboard](#tensorflow-tensorboard) + - [Note](#note) # TensorFlow examples @@ -166,7 +170,7 @@ Here're some configuration file examples: } ``` -For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/job_tutorial.md#json-config-file-for-job-submission). +For more details on how to write a job configuration file, please refer to [job tutorial](../../docs/user/training.md). ### Note

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