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        "author": "Victor Zhong",
        "author_email": "victor@victorzhong.com",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Build Tools"
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        "description": "# autotune\nHyperparameter tuning on GPUs\n\n[![Build Status](https://travis-ci.org/vzhong/autotune.svg?branch=master)](https://travis-ci.org/vzhong/autotune)\n\n## Installation\n\n```bash\npip install git+git://github.com/vzhong/autotune.git\n\n# Or get it straight from PyPI\n\npip install autotune\n```\n\n## Usage\n\nYou can use the binary:\n\n```bash\nautotune -h\n```\n\nOr use it programmatically:\n\n```python\nfrom autotune.tuner import RandomSearch\nfrom autotune.spec import Spec\n\nconfig = Spec.load('myconf.json')\ntuner = RandomSearch('myprog.bin', config)\ntuner.tune(2, out='output')\n```\n\nwhere `myconf.json` looks something like:\n\n```json\n{\n  \"foo\": [-1, 1],\n  \"bar\": [2.0, 3.0]\n}\n```\n\nThis will run 2 commands `myprog.bin --foo $FOO --bar $BAR` where `$FOO` is an integer sampled between `-1` and `1` and `$BAR` is a float sampled between `2.0` and `3.0`.\nYou can pass in an optional parameter `name='nickname'`, which will add to the command `--nickname $HASH`, where `$HASH` is a hash of the specific parameters used for this command.\nYou can also pass in an optional parameter `gpu=True`, which will queue jobs onto aavailable GPUs.\nThe command then becomes `CUDA_VISIBLE_DEVICES=$GPU myprog.bin --foo $FOO --bar $BAR --gpu 0`, where `$GPU` is a free GPU (e.g. no memory usage).\n\n\n",
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        "name": "autotune",
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        "summary": "Hyperparameter tuning",
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