@@ -15,40 +15,25 @@ Use ``examples/trials/mnist-tfv1`` as an example. The NNI config YAML file's con
...
@@ -15,40 +15,25 @@ Use ``examples/trials/mnist-tfv1`` as an example. The NNI config YAML file's con
.. code-block:: yaml
.. code-block:: yaml
authorName: default
experimentName: MNIST
experimentName: example_mnist
searchSpaceFile: search_space.json
trialCommand: python3 mnist.py
trialCodeDirectory: .
trialConcurrency: 2
trialConcurrency: 2
maxExecDuration: 1h
trialGpuNumber: 0
maxTrialNum: 10
maxExperimentDuration: 24h
trainingServicePlatform: hybrid
maxTrialNumber: 100
searchSpacePath: search_space.json
#choice: true, false
useAnnotation: false
tuner:
tuner:
builtinTunerName: TPE
name: TPE
classArgs:
classArgs:
#choice: maximize, minimize
optimize_mode: maximize
optimize_mode: maximize
trial:
trainingService:
command: python3 mnist.py
- platform: remote
codeDir: .
machineList:
gpuNum: 1
- host: 127.0.0.1
hybridConfig:
user: bob
trainingServicePlatforms:
password: bob
- local
- platform: local
- remote
remoteConfig:
To use hybrid training services, users should set training service configurations as a list in `trainingService` field.
reuse: true
Currently, hybrid support setting `local`, `remote`, `pai` and `aml` training services.
machineList:
- ip: 10.1.1.1
username: bob
passwd: bob123
Configurations for hybrid mode:
hybridConfig:
* trainingServicePlatforms. required key. This field specify the platforms used in hybrid mode, the values using yaml list format. NNI support setting ``local``, ``remote``, ``aml``, ``pai`` in this field.
.. Note:: If setting a platform in trainingServicePlatforms mode, users should also set the corresponding configuration for the platform. For example, if set ``remote`` as one of the platform, should also set ``machineList`` and ``remoteConfig`` configuration.
