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    "info": {
        "author": "Rui Wang",
        "author_email": "wangrui_key@163.com",
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        "description": "# Pytorch Light\nPytorch Light is a Python package that provides several tools about modelling and applications.\n\nThere are some features as follows:\n\n- [Model](#model)\n- [Data](#data)\n- [Log](#log)\n- [Visualization](#visualization)\n\n[requirements.txt](requirements.txt) is also provided.\n\nNext feature is going to be achieved as soon as possible.\n\n- Adversarial Learning\n\nAnd some applications are coming:\n\n- Computer Vision\n- Natural Language\n- Rereinforcement Learning\n\n**Note** that these features are only validated on cpu.\n\n## Model\n\nApplication for model.\n\nFeatures:\n\n1. train\n2. evaluate\n3. batch loss and batch metric\n4. model wrapper\n\n## Data\n\nApplication for data.\n\nFeatures:\n\n1. Numpy.ndarray to/from Torch.tensor\n2. Numpy.ndarray to/from Torch.Dataset\n3. Numpy.ndarray to/from Torch.DataLoader\n\n## Log\n\nApplication for log.\n\nFeatures:\n\n1. debug\n2. info\n3. warn\n4. error\n5. critical\n\n## Visualization\n\nApplication for visualization based on numpy.ndarray.\n\nRequire:\n\n- In the notebook mode, `%matplotlib inline` should be implement first.\n\nFeatures:\n\n1. learning curves\n2. batch curves\n3. one or multi images\n\n\n",
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        "keywords": "",
        "license": "BSD",
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        "name": "pytorchlight",
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