Add SupportTrainingService.md #1401

SparkSnail · 2019-08-02T02:31:55Z

scarlett2018 · 2019-08-02T03:16:01Z

docs/en_US/TrainingService/SupportTrainingService.md

+# Support TrainingService
+
+TrainingService is a concept of training platform that run trial jobs on the corresponding platform. NNI support [local](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/LocalMode.md), [remote](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/RemoteMachineMode.md), [pai](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/PaiMode.md), [kubeflow](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/KubeflowMode.md) and [frameworkcontroller](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/FrameworkControllerMode.md) training service. 
+


NNI not only provides few built-in training service options, but also provides a method for customers to build their own training service easily.

xuehui1991 · 2019-08-02T06:41:49Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService
+
+TrainingService is a concept of service that matain the training platform on which trial jobs run. NNI support [local](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/LocalMode.md), [remote](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/RemoteMachineMode.md), [pai](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/PaiMode.md), [kubeflow](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/KubeflowMode.md) and [frameworkcontroller](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/FrameworkControllerMode.md) built-in training service.   


shall we use a relative path here?

xuehui1991 · 2019-08-02T06:43:02Z

docs/en_US/TrainingService/SupportTrainingService.md

+|[__Kubeflow__](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/KubeflowMode.md)|NNI supports running experiment on [Kubeflow](https://github.com/kubeflow/kubeflow), called kubeflow mode. Before starting to use NNI kubeflow mode, you should have a Kubernetes cluster, either on-premises or [Azure Kubernetes Service(AKS)](https://azure.microsoft.com/en-us/services/kubernetes-service/), a Ubuntu machine on which [kubeconfig](https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig/) is setup to connect to your Kubernetes cluster. If you are not familiar with Kubernetes, [here](https://kubernetes.io/docs/tutorials/kubernetes-basics/) is a good start. In kubeflow mode, your trial program will run as Kubeflow job in Kubernetes cluster.|
+|[__FrameworkController__](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/FrameworkControllerMode.md)|NNI supports running experiment using [FrameworkController](https://github.com/Microsoft/frameworkcontroller), called frameworkcontroller mode. FrameworkController is built to orchestrate all kinds of applications on Kubernetes, you don't need to install Kubeflow for specific deep learning framework like tf-operator or pytorch-operator. Now you can use FrameworkController as the training service to run NNI experiment.|
+
+## Implement TrainingService


TrainingService Implementation?

QuanluZhang · 2019-08-05T06:50:31Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService
+
+TrainingService is a concept of service that matain the training platform on which trial jobs run. NNI support [local](./LocalMode.md), [remote](./RemoteMachineMode.md), [pai](./PaiMode.md), [kubeflow](./KubeflowMode.md) and [frameworkcontroller](./FrameworkControllerMode.md) built-in training service.   


changed to maintain

…rainingServiceDoc

rabbit008 · 2019-08-05T08:23:23Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService
+
+TrainingService is a concept of service that maintain the training platform on which trial jobs run. NNI support [local](./LocalMode.md), [remote](./RemoteMachineMode.md), [pai](./PaiMode.md), [kubeflow](./KubeflowMode.md) and [frameworkcontroller](./FrameworkControllerMode.md) built-in training service.   


"TrainingService is a concept of service that maintain the training platform on which trial jobs run." -->"TrainingService is a concept of service that used to maintain a training platform for running trial jobs." Maybe there can change like this? I first thought that run.NNI was connected.

rabbit008 · 2019-08-05T08:24:44Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService
+
+TrainingService is a concept of service that maintain the training platform on which trial jobs run. NNI support [local](./LocalMode.md), [remote](./RemoteMachineMode.md), [pai](./PaiMode.md), [kubeflow](./KubeflowMode.md) and [frameworkcontroller](./FrameworkControllerMode.md) built-in training service.   


"NNI support [local]" -->" NNI supports [local] "

"built-in training service" --> "built-in training services"

rabbit008 · 2019-08-05T08:28:58Z

docs/en_US/TrainingService/SupportTrainingService.md

+## Built-in TrainingService
+|TrainingService|Brief Introduction|
+|---|---|
+|[__local__](./LocalMode.md)|NNI supports running an experiment on local machine, called local mode. Local mode means that NNI will run the trial jobs and nniManager process in same machine, and support gpu schedule function for trial jobs.|


local --> Local

rabbit008 · 2019-08-05T08:29:33Z

docs/en_US/TrainingService/SupportTrainingService.md

+|TrainingService|Brief Introduction|
+|---|---|
+|[__local__](./LocalMode.md)|NNI supports running an experiment on local machine, called local mode. Local mode means that NNI will run the trial jobs and nniManager process in same machine, and support gpu schedule function for trial jobs.|
+|[__remote__](./RemoteMachineMode.md)|NNI supports running an experiment on multiple machines through SSH channel, called remote mode. NNI assumes that you have access to those machines, and already setup the environment for running deep learning training code. NNI will submit the trial jobs in remote machine, and schedule suitable machine with enouth gpu resource if specified.|


remote --> Remote
pai --> PAI

scarlett2018

approved with minor suggestions.

scarlett2018 · 2019-08-06T05:16:01Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService


Change the title to TrainingService, as this is a page for Training Service root.

scarlett2018 · 2019-08-06T05:21:25Z

docs/en_US/TrainingService/SupportTrainingService.md

@@ -0,0 +1,36 @@
+# Support TrainingService
+
+TrainingService is a concept of service that used to maintain a training platform for running trial jobs. NNI supports [local](./LocalMode.md), [remote](./RemoteMachineMode.md), [pai](./PaiMode.md), [kubeflow](./KubeflowMode.md) and [frameworkcontroller](./FrameworkControllerMode.md) built-in training services.   


NNI TrainingService provides the training platform for running NNI trial jobs.

* Update filter description and fix typo * fix comments * change node to result * Add SupportTrainingService.md (#1401) * fix nnictl schema * Eject from react-scripts-ts-antd and bump webui dependencies version (#1412) * Eject from react-scripts-ts-antd * test whether it can pass CI without ugilfy * temporarily disable uglify * Try to fix security alert (#1429) * fix bug of hyper-parameter broken when have not succeeded trial * update * update

…lt (#1472) * Update filter description and fix typo * fix comments * change node to result * Add SupportTrainingService.md (#1401) * fix nnictl schema * Eject from react-scripts-ts-antd and bump webui dependencies version (#1412) * Eject from react-scripts-ts-antd * test whether it can pass CI without ugilfy * temporarily disable uglify * Try to fix security alert (#1429) * fix bug of detail page broken when trial is succeed but not report final result

SparkSnail added 3 commits August 1, 2019 22:08

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SparkSnail requested review from rabbit008, scarlett2018, xuehui1991 and QuanluZhang August 2, 2019 02:55

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SparkSnail requested review from QuanluZhang and chicm-ms and removed request for QuanluZhang August 2, 2019 08:18

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SparkSnail added 2 commits August 5, 2019 15:53

Merge branch 'master' of https://github.com/SparkSnail/nni into dev-t…

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…rainingServiceDoc

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scarlett2018 approved these changes Aug 6, 2019

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suiguoxin changed the base branch from master to v1.0 August 6, 2019 09:19

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SparkSnail merged commit 6c9d370 into microsoft:v1.0 Aug 6, 2019

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Add SupportTrainingService.md #1401

Add SupportTrainingService.md #1401

SparkSnail commented Aug 2, 2019 •

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SparkSnail Aug 6, 2019

		# Support TrainingService

		TrainingService is a concept of training platform that run trial jobs on the corresponding platform. NNI support [local](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/LocalMode.md), [remote](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/RemoteMachineMode.md), [pai](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/PaiMode.md), [kubeflow](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/KubeflowMode.md) and [frameworkcontroller](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/FrameworkControllerMode.md) training service.

		@@ -0,0 +1,36 @@
		# Support TrainingService

		TrainingService is a concept of service that matain the training platform on which trial jobs run. NNI support [local](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/LocalMode.md), [remote](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/RemoteMachineMode.md), [pai](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/PaiMode.md), [kubeflow](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/KubeflowMode.md) and [frameworkcontroller](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/FrameworkControllerMode.md) built-in training service.

Add SupportTrainingService.md #1401

Add SupportTrainingService.md #1401

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SparkSnail commented Aug 2, 2019 • edited

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SparkSnail commented Aug 2, 2019 •

edited