Metadata-Version: 1.1
Name: winmltools
Version: 1.5.1
Summary: Converts Machine Learning models to ONNX for use in Windows ML
Home-page: https://microsoft.com
Author: Microsoft Corporation
Author-email: winml@microsoft.com
License: MIT License
Description: WinMLTools provide following tools for Windows ML:
        
        Model Conversion
        ################
        
        WinMLTools enables you to convert models from different machine 
        learning toolkits into `ONNX <https://onnx.ai>`_ for use with Windows ML. 
        Currently the following toolkits are supported:
        
        * apple CoreML
        * keras
        * scikit-learn
        * lightgbm
        * xgboost
        * libSVM
        * tensorflow (experimental)
        
        Here is a simple example to convert a Core ML model:
        
        ::
        
            from coremltools.models.utils import load_spec
            from winmltools import convert_coreml
            model_coreml = load_spec('example.mlmodel')
            model_onnx = convert_coreml(model_coreml, 10, name='ExampleModel')
        
        Post Training Weight Quantization
        #################################
        
        WinMLTools provides quantization tool to reduce the memory footprint of the model.
        
        Here is an example to convert an ONNX model to a quantized ONNX model:
        
        ::
        
            import winmltools
        
            model = winmltools.load_model('model.onnx')
            quantized_model = winmltools.quantize(model, per_channel=True, nbits=8, use_dequantize_linear=True)
            winmltools.save_model(quantized_model, 'quantized.onnx')
        
        
        Dependencies
        ============
        
        In order to convert from different toolkits, you may have to install the following packages for different converters: 
        
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | Toolkit      | Source                                                                                                                                             |
        +==============+====================================================================================================================================================+
        | keras        | https://pypi.org/project/Keras                                                                                                                     |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | tensorflow   | https://pypi.org/project/tensorflow                                                                                                                |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | scikit-learn | https://pypi.org/project/scikit-learn                                                                                                              |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | lightgbm     | https://pypi.org/project/lightgbm                                                                                                                  |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | xgboost      | https://pypi.org/project/xgboost                                                                                                                   |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | libsvm       | You can download libsvm wheel from various web sources. One example can be found here: https://www.lfd.uci.edu/~gohlke/pythonlibs/#libsvm          |
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        | coremltools  | Currenlty coreml does not distribute coreml packaging on windows. You can install from source: pip install git+https://github.com/apple/coremltools|
        +--------------+----------------------------------------------------------------------------------------------------------------------------------------------------+
        
        
        For more information on WinMLTools, you can go to `Convert ML models to ONNX with WinMLTools
        <https://docs.microsoft.com/en-us/windows/ai/convert-model-winmltools>`_
        
        License
        =======
        
        MIT License
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
