| Name | milatools JSON |
| Version |
0.1.8
JSON |
| download |
| home_page | None |
| Summary | Tools to work with the Mila cluster |
| upload_time | 2025-07-08 14:44:29 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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No coveralls.
|
# milatools
The milatools package provides the `mila` command, which is meant to help with connecting to and interacting with the Mila cluster.
---
**Warning**
The `mila` command is meant to be used on your local machine. Trying to run it on the cluster will fail with an error
---
## Install
Requires Python >= 3.8
We recommend using [`uv`](https://docs.astral.sh/uv/) in order to use `milatools` in its own isolated environment instead of alterring your default Python environment or creating and activating a new one manually.
```bash
uv tool install milatools
```
_Alternatively_:
```bash
pip install milatools
```
Or, for bleeding edge version:
```bash
uv tool install git+https://github.com/mila-iqia/milatools.git
# OR
pip install git+https://github.com/mila-iqia/milatools.git
```
After installing `milatools`, start with `mila init`:
```bash
mila init
```
## Commands
### mila init
Set up your access to the mila cluster interactively. Have your username and password ready!
* Set up your SSH config for easy connection with `ssh mila`
* Set up your public key if you don't already have them
* Copy your public key over to the cluster for passwordless auth
* Set up a public key on the login node to enable ssh into compute nodes
* **new**: Add a special SSH config for direct connection to a **compute node** with `ssh mila-cpu`
### mila docs/intranet
* Use `mila docs <search terms>` to search the Mila technical documentation
* Use `mila intranet <search terms>` to search the Mila intranet
Both commands open a browser window. If no search terms are given you are taken to the home page.
### mila code
Connect a VSCode instance to a compute node. `mila code` first allocates a compute node using slurm (you can pass slurm options as well using `--alloc`), and then calls the `code` command with the appropriate options to start a remote coding session on the allocated node.
You can simply Ctrl+C the process to end the session.
```
usage: mila code [-h] [--cluster {mila,cedar,narval,beluga,graham}] [--alloc ...]
[--command VALUE] [--job VALUE] [--node VALUE] [--persist]
PATH
positional arguments:
PATH Path to open on the remote machine
options:
-h, --help show this help message and exit
--alloc ... Extra options to pass to slurm
--cluster {mila,cedar,narval,beluga,graham}
Which cluster to connect to.
--command VALUE Command to use to start vscode (defaults to "code" or the value
of $MILATOOLS_CODE_COMMAND)
--job VALUE Job ID to connect to
--node VALUE Node to connect to
--persist Whether the server should persist or not
```
For example:
```bash
mila code path/to/my/experiment
```
The `--alloc` option may be used to pass extra arguments to `salloc` when allocating a node (for example, `--alloc --gres=gpu:1` to allocate 1 GPU). `--alloc` should be at the end, because it will take all of the arguments that come after it.
If you already have an allocation on a compute node, you may use the `--node NODENAME` or `--job JOBID` options to connect to that node.
### mila serve
The purpose of `mila serve` is to make it easier to start notebooks, logging servers, etc. on the compute nodes and connect to them.
```
usage: mila serve [-h] {connect,kill,list,lab,notebook,tensorboard,mlflow,aim} ...
positional arguments:
{connect,kill,list,lab,notebook,tensorboard,mlflow,aim}
connect Reconnect to a persistent server.
kill Kill a persistent server.
list List active servers.
lab Start a Jupyterlab server.
notebook Start a Jupyter Notebook server.
tensorboard Start a Tensorboard server.
mlflow Start an MLFlow server.
aim Start an AIM server.
optional arguments:
-h, --help show this help message and exit
```
For example, to start jupyterlab with one GPU, you may write:
```bash
mila serve lab --alloc --gres gpu:1
```
You can of course write any SLURM arguments after `--alloc`.
Ending the connection will end the server, but the `--persist` flag can be used to prevent that. In that case you would be able to write `mila serve connect jupyter-lab` in order to reconnect to your running instance. Use `mila serve list` and `mila serve kill` to view and manage any running instances.
Raw data
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"description": "\n# milatools\n\nThe milatools package provides the `mila` command, which is meant to help with connecting to and interacting with the Mila cluster.\n\n---\n\n**Warning**\n\nThe `mila` command is meant to be used on your local machine. Trying to run it on the cluster will fail with an error\n\n---\n\n\n## Install\n\nRequires Python >= 3.8\n\nWe recommend using [`uv`](https://docs.astral.sh/uv/) in order to use `milatools` in its own isolated environment instead of alterring your default Python environment or creating and activating a new one manually.\n\n```bash\nuv tool install milatools\n```\n\n_Alternatively_:\n\n```bash\npip install milatools\n```\n\nOr, for bleeding edge version:\n\n```bash\nuv tool install git+https://github.com/mila-iqia/milatools.git\n# OR\npip install git+https://github.com/mila-iqia/milatools.git\n```\n\nAfter installing `milatools`, start with `mila init`:\n\n```bash\nmila init\n```\n\n\n## Commands\n\n### mila init\n\nSet up your access to the mila cluster interactively. Have your username and password ready!\n\n* Set up your SSH config for easy connection with `ssh mila`\n* Set up your public key if you don't already have them\n* Copy your public key over to the cluster for passwordless auth\n* Set up a public key on the login node to enable ssh into compute nodes\n* **new**: Add a special SSH config for direct connection to a **compute node** with `ssh mila-cpu`\n\n\n### mila docs/intranet\n\n* Use `mila docs <search terms>` to search the Mila technical documentation\n* Use `mila intranet <search terms>` to search the Mila intranet\n\nBoth commands open a browser window. If no search terms are given you are taken to the home page.\n\n\n### mila code\n\nConnect a VSCode instance to a compute node. `mila code` first allocates a compute node using slurm (you can pass slurm options as well using `--alloc`), and then calls the `code` command with the appropriate options to start a remote coding session on the allocated node.\n\nYou can simply Ctrl+C the process to end the session.\n\n```\nusage: mila code [-h] [--cluster {mila,cedar,narval,beluga,graham}] [--alloc ...]\n [--command VALUE] [--job VALUE] [--node VALUE] [--persist]\n PATH\n\npositional arguments:\n PATH Path to open on the remote machine\n\noptions:\n -h, --help show this help message and exit\n --alloc ... Extra options to pass to slurm\n --cluster {mila,cedar,narval,beluga,graham}\n Which cluster to connect to.\n --command VALUE Command to use to start vscode (defaults to \"code\" or the value\n of $MILATOOLS_CODE_COMMAND)\n --job VALUE Job ID to connect to\n --node VALUE Node to connect to\n --persist Whether the server should persist or not\n```\n\nFor example:\n\n```bash\nmila code path/to/my/experiment\n```\n\nThe `--alloc` option may be used to pass extra arguments to `salloc` when allocating a node (for example, `--alloc --gres=gpu:1` to allocate 1 GPU). `--alloc` should be at the end, because it will take all of the arguments that come after it.\n\nIf you already have an allocation on a compute node, you may use the `--node NODENAME` or `--job JOBID` options to connect to that node.\n\n\n### mila serve\n\nThe purpose of `mila serve` is to make it easier to start notebooks, logging servers, etc. on the compute nodes and connect to them.\n\n```\nusage: mila serve [-h] {connect,kill,list,lab,notebook,tensorboard,mlflow,aim} ...\n\npositional arguments:\n {connect,kill,list,lab,notebook,tensorboard,mlflow,aim}\n connect Reconnect to a persistent server.\n kill Kill a persistent server.\n list List active servers.\n lab Start a Jupyterlab server.\n notebook Start a Jupyter Notebook server.\n tensorboard Start a Tensorboard server.\n mlflow Start an MLFlow server.\n aim Start an AIM server.\n\noptional arguments:\n -h, --help show this help message and exit\n```\n\nFor example, to start jupyterlab with one GPU, you may write:\n\n```bash\nmila serve lab --alloc --gres gpu:1\n```\n\nYou can of course write any SLURM arguments after `--alloc`.\n\nEnding the connection will end the server, but the `--persist` flag can be used to prevent that. In that case you would be able to write `mila serve connect jupyter-lab` in order to reconnect to your running instance. Use `mila serve list` and `mila serve kill` to view and manage any running instances.\n",
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