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modify docs #1759

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5 changes: 4 additions & 1 deletion docs/en_US/TrainingService/LocalMode.md
Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ This command will be filled in the YAML configure file below. Please refer to [h

**Prepare configure file**: Since you have already known which trial code you are going to run and which tuner you are going to use, it is time to prepare the YAML configure file. NNI provides a demo configure file for each trial example, `cat ~/nni/examples/trials/mnist-annotation/config.yml` to see it. Its content is basically shown below:

```
```yaml
authorName: your_name
experimentName: auto_mnist

Expand All @@ -112,6 +112,9 @@ maxTrialNum: 100
# choice: local, remote
trainingServicePlatform: local

# search space file
searchSpacePath: nni_search_space.json

# choice: true, false
useAnnotation: true
tuner:
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2 changes: 2 additions & 0 deletions docs/en_US/TrainingService/PaiMode.md
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Expand Up @@ -19,6 +19,8 @@ maxExecDuration: 3h
maxTrialNum: 100
# choice: local, remote, pai
trainingServicePlatform: pai
# search space file
searchSpacePath: nni_search_space.json
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# choice: true, false
useAnnotation: true
tuner:
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2 changes: 2 additions & 0 deletions docs/en_US/TrainingService/RemoteMachineMode.md
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Expand Up @@ -28,6 +28,8 @@ maxExecDuration: 1h
maxTrialNum: 10
#choice: local, remote, pai
trainingServicePlatform: remote
# search space file
searchSpacePath: nni_search_space.json
#choice: true, false
useAnnotation: true
tuner:
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57 changes: 30 additions & 27 deletions docs/zh_CN/TrainingService/LocalMode.md
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Expand Up @@ -98,33 +98,36 @@
*builtinTunerName* 用来指定 NNI 中的 Tuner,*classArgs* 是传入到 Tuner的参数(内置 Tuner 在[这里](../Tuner/BuiltinTuner.md)),*optimization_mode* 表明需要最大化还是最小化 Trial 的结果。

**准备配置文件**:实现 Trial 的代码,并选择或实现自定义的 Tuner 后,就要准备 YAML 配置文件了。 NNI 为每个 Trial 样例都提供了演示的配置文件,用命令`cat ~/nni/examples/trials/mnist-annotation/config.yml` 来查看其内容。 大致内容如下:

authorName: your_name
experimentName: auto_mnist

# 并发运行数量
trialConcurrency: 2

# Experiment 运行时间
maxExecDuration: 3h

# 可为空,即数量不限
maxTrialNum: 100

# 可选值为: local, remote
trainingServicePlatform: local

# 可选值为: true, false
useAnnotation: true
tuner:
builtinTunerName: TPE
classArgs:
optimize_mode: maximize
trial:
command: python mnist.py
codeDir: ~/nni/examples/trials/mnist-annotation
gpuNum: 0

```yaml
authorName: your_name
experimentName: auto_mnist

# 并发运行数量
trialConcurrency: 2

# Experiment 运行时间
maxExecDuration: 3h

# 可为空,即数量不限
maxTrialNum: 100

# 可选值为: local, remote
trainingServicePlatform: local

# 搜索空间文件
searchSpacePath: nni_search_space.json

# 可选值为: true, false
useAnnotation: true
tuner:
builtinTunerName: TPE
classArgs:
optimize_mode: maximize
trial:
command: python mnist.py
codeDir: ~/nni/examples/trialsmnist-annotation
gpuNum: 0
```

因为这个 Trial 代码使用了 NNI Annotation 的方法(参考[这里](../Tutorial/AnnotationSpec.md) ),所以*useAnnotation* 为 true。 *command* 是运行 Trial 代码所需要的命令,*codeDir* 是 Trial 代码的相对位置。 命令会在此目录中执行。 同时,也需要提供每个 Trial 进程所需的 GPU 数量。

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2 changes: 2 additions & 0 deletions docs/zh_CN/TrainingService/PaiMode.md
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,8 @@ maxExecDuration: 3h
maxTrialNum: 100
# 可选项: local, remote, pai
trainingServicePlatform: pai
# 搜索空间文件
searchSpacePath: nni_search_space.json
# 可选项: true, false
useAnnotation: true
tuner:
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2 changes: 2 additions & 0 deletions docs/zh_CN/TrainingService/RemoteMachineMode.md
Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,8 @@ maxExecDuration: 1h
maxTrialNum: 10
#可选项: local, remote, pai
trainingServicePlatform: remote
# 搜索空间文件
searchSpacePath: nni_search_space.json
#可选项: true, false
useAnnotation: true
tuner:
Expand Down