NNI supports running an experiment on multiple machines, called remote machine mode. Let's say you have multiple machines with the account `bob` (Note: the account is not necessarily the same on multiple machines):
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.
e.g. Three machines and you login in with account `bob` (Note: the account is not necessarily the same on different machine):
| IP | Username| Password |
| -------- |---------|-------|
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@@ -8,7 +10,7 @@ NNI supports running an experiment on multiple machines, called remote machine m
| 10.1.1.2 | bob | bob123 |
| 10.1.1.3 | bob | bob123 |
## Setup environment
## Setup NNI environment
Install NNI on each of your machines following the install guide [here](GetStarted.md).
For remote machines that are used only to run trials but not the nnictl, you can just install python SDK:
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@@ -17,40 +19,38 @@ For remote machines that are used only to run trials but not the nnictl, you can
python3 -m pip install --user --upgrade nni-sdk
* __Install python SDK through source code__
git clone https://github.com/Microsoft/nni.git
cd src/sdk/pynni
python3 setup.py install
## Run an experiment
Still using `examples/trials/mnist-annotation` as an example here. The yaml file you need is shown below:
Install NNI on another machine which has network accessibility to those three machines above, or you can just use any machine above to run nnictl command line tool.
We use `examples/trials/mnist-annotation` as an example here. `cat ~/nni/examples/trials/mnist-annotation/config_remote.yml` to see the detailed configuration file:
to start the experiment. This command can be executed on one of those three machines above, and can also be executed on another machine which has NNI installed and has network accessibility to those three machines.