Skip to main content

No project description provided

Project description

nshrunner

nshrunner is a Python library that provides a unified way to run functions in various environments, such as local dev machines, cloud VMs, SLURM clusters, and LSF clusters. It was created to simplify the process of running ML training jobs across multiple machines and environments.

Motivation

When running ML training jobs on different machines and environments, it can be challenging to manage the specifics of each environment. nshrunner was developed to address this issue by providing a single function that can be used to run jobs on any supported environment without having to worry about the details of each environment.

Features

  • Supports running functions locally, on SLURM clusters, and on LSF clusters
  • Provides a unified interface for running functions across different environments
  • Allows for easy configuration of job options, such as resource requirements and environment variables
  • Supports snapshotting the environment to ensure reproducibility, using the nshsnap library
  • Provides utilities for logging, seeding, and signal handling

Installation

nshrunner can be installed using pip:

pip install nshrunner

Usage

Here's a simple example of how to use nshrunner to run a function locally:

import nshrunner as R

def run_fn(x: int):
    return x + 5

runs = [(1,)]

runner = R.Runner(run_fn)
list(runner.local(runs))

To run the same function on a SLURM cluster:

runner.submit_slurm(
    runs,
    {
        "partition": "learnaccel",
        "nodes": 4,
        "ntasks_per_node": 8,  # Change this to limit # of GPUs
        "gpus_per_task": 1,
        "cpus_per_task": 1,
    },
    snapshot=True,
)

And on an LSF cluster:

runner.submit_lsf(
    runs,
    {
        "summit": True,
        "queue": "learnaccel",
        "nodes": 4,
        "rs_per_node": 8,  # Change this to limit # of GPUs
    },
    snapshot=True,
)

For more detailed usage examples, please refer to the documentation.

Acknowledgements

nshrunner is heavily inspired by submitit. It builds on submitit's design and adds support for LSF clusters, snapshotting, and other features.

Contributing

Contributions are welcome! For feature requests, bug reports, or questions, please open an issue on GitHub. If you'd like to contribute code, please submit a pull request with your changes.

License

nshrunner is released under the MIT License. See LICENSE for more information.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nshrunner-0.18.0.tar.gz (24.9 kB view details)

Uploaded Source

Built Distribution

nshrunner-0.18.0-py3-none-any.whl (33.5 kB view details)

Uploaded Python 3

File details

Details for the file nshrunner-0.18.0.tar.gz.

File metadata

  • Download URL: nshrunner-0.18.0.tar.gz
  • Upload date:
  • Size: 24.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.8.0-45-generic

File hashes

Hashes for nshrunner-0.18.0.tar.gz
Algorithm Hash digest
SHA256 582132d895d257d4c8d07b81205960f45896cffa7e16174bc4b1a44ea3a763be
MD5 54a29c33c8bbe20ea13d7ee86d382858
BLAKE2b-256 417577aeeace87647cd6518f791bdae3bd7a61269df7f2ac024ab29d33ad8d4b

See more details on using hashes here.

File details

Details for the file nshrunner-0.18.0-py3-none-any.whl.

File metadata

  • Download URL: nshrunner-0.18.0-py3-none-any.whl
  • Upload date:
  • Size: 33.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.8.0-45-generic

File hashes

Hashes for nshrunner-0.18.0-py3-none-any.whl
Algorithm Hash digest
SHA256 14f15fbdce4dfa9a48e43b8e6429361f0ca5cf894ea55360631411b06c8cec92
MD5 b2563b4029eae1605c28192219b1fe12
BLAKE2b-256 bce29cd261257fb44fcde72b24a8c04f0badda3132a0b42c072bc0e40bbc6a06

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page