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        "description": "# GPU Utils\n\nA few small functions/scripts for working with GPUs.\n\n## Requirements\n\n* Python 3.6+\n* Linux OS for full functionality (only tested on Ubuntu; I use `subprocess.run` for `kill` and `lsof`)\n  * Everything except `kill_interrupted_processes` should work on any OS\n\n## Installation\n\n```\npip install gpu-utils\n```\n\nThe PyPI page is [here][pypi page].\n\n## Usage\n\n```python\nfrom gpu_utils import gpu_init\n\n# sets GPU ids to use nvidia-smi ordering (CUDA_DEVICE_ORDER = PCI_BUS_ID)\n# finds the gpu with the most free utilization or memory\n# hides all other GPUs so you only use this one (CUDA_VISIBLE_DEVICES = <gpu_id>)\ngpu_id = gpu_init(best_gpu_metric=\"util\") # could also use \"mem\"\n```\n\nIf you use TensorFlow or PyTorch, `gpu_init` can take care of another couple of steps for you:\n\n```python\n# a torch.device for the selected GPU\ndevice = gpu_init(ml_library=\"torch\")\n```\n\n```python\nimport tensorflow as tf\n# a tf.ConfigProto to allow soft placement + GPU memory growth\nconfig = gpu_init(ml_library=\"tensorflow\")\nsession = tf.Session(config=config)\n```\n\n## Command Line Scripts\n\n`gpu` is a more concise and prettier version of `nvidia-smi`. It is similar to [`gpustat`][gpustat] but with more control over the color configuration and the ability to show the full processes running on each GPU.\n\n`kill_interrupted_processes` is useful if you interrupt a process using a GPU but find that, even though `nvidia-smi` no longer shows the process, the memory is still being held. It will send `kill -9` to all such processes so you can reclaim your GPU memory.\n\n`tmux_gpu_info.py` just prints a list of the percent utilization of each GPU; you can, e.g., show this in the status bar of `tmux` to keep an eye on your GPUs.\n\n## Acknowledgements\n* Using `pynvml` instead of parsing `nvidia-smi` with regular expressions made this library a bit faster and much more robust than my previous regex parsing of `nivida-smi`'s output; thanks to [`gpustat`][gpustat] for showing me this library and some ideas about the output format for the `gpu` script.\n\n[pypi page]: https://pypi.org/project/gpu-utils/\n[gpustat]: https://github.com/wookayin/gpustat\n\n",
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