{
    "info": {
        "author": "CHEN Si Yu",
        "author_email": "sychen@zju.edu.cn",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
        ],
        "description": "# TorchFun (originally Torchure)\n\n##for those who expect more convenient features from torch\n<!-- ### -- for those who suffer from torch -->\n\n### Functionality\n\n* flatten(tensor)\n* imshow(tensor_batch)\n* load\n\n## Install TorchFun\n\n```bash\npip install torchfun\n```\n\n## API\n\n### Flatten (Module)\nused to reshape outputs\n\nUsage:\n\n    flat = Flatten()\n    out = flat(x)\n\n\n### flatten (function)\n\nUsage:\n\n    out = flatten(x)\n\n\n### imshow (function)\n\nonly deal with torch channel-first image batch,\n\nArguements:\n\n* x: input data cube, torch tensor or numpy array.\n* title: add title to plot. (Default None)\n    * title can be string, or any string-able object.\n* auto_close: (default True) \n    * Close the pyplot session afterwards. \n    * Clean the environment just like you had never used matplotlib here.\n    * if set to False, the plot will remain in the memory for further drawings.\n\nUsage:\n\nimshow(batch)\nimshow(batch,title=[a,b,c])\nimshow(batch,title='title')\nimshow(batch,auto_close=False) \n\n### load (function)\nArguements:\n* arbitrary arguemnts named : `a` and `b`\nLoad weight `a` into model `b`, or load model `b` using weight `a`\nThe order of the arguments doesn't matter.\nExample:\n\n    >load('weights.pts',model)\n\nor\n\n    >load(model,'weights.pts')\n\nor\n\n    >f = open('weight.pts')\n    >load(f,model)\n\nor\n\n    >load(model,f)\n\nReturn value:\n* None\n\n",
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        "home_page": "https://github.com/sorenchiron/torchfun",
        "keywords": "",
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        "maintainer": "",
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        "name": "torchure",
        "package_url": "https://pypi.org/project/torchure/",
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        "project_url": "https://pypi.org/project/torchure/",
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        "requires_dist": [
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            "torch",
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        "summary": "A collection of small functions that supplements torch functionality",
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