Metadata-Version: 2.1
Name: hls4ml
Version: 0.5.0b0
Summary: Machine learning in FPGAs using HLS
Home-page: https://github.com/hls-fpga-machine-learning/hls4ml
Author: HLS4ML Team
Author-email: hls4ml.help@gmail.com
License: Apache 2.0
Description: <p float="left">
           <img src="https://fastmachinelearning.github.io/hls4ml/img/logo.jpg" alt="hls4ml" width="400"/>
        </p>
        
        [![DOI](https://zenodo.org/badge/108329371.svg)](https://zenodo.org/badge/latestdoi/108329371)
        [![PyPI version](https://badge.fury.io/py/hls4ml.svg)](https://badge.fury.io/py/hls4ml)
        [![Supported Python versions](https://img.shields.io/pypi/pyversions/hls4ml.svg)](https://pypi.org/project/hls4ml/)
        
        A package for machine learning inference in FPGAs. We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source machine learning package models into HLS that can be configured for your use-case!
        
        **Contact:** hls4ml.help@gmail.com
        
        # Documentation & Tutorial
        
        For more information visit the webpage: [https://fastmachinelearning.org/hls4ml/](https://fastmachinelearning.org/hls4ml/)
        
        Detailed tutorials on how to use `hls4ml`'s various functionalities can be found [here](https://github.com/hls-fpga-machine-learning/hls4ml-tutorial).
        
        # Installation
        ```
        pip install hls4ml
        ```
        
        To install the extra dependencies for profiling: 
        
        ```
        pip install hls4ml[profiling]
        ```
        
        # Getting Started
        ### Creating an HLS project
        ```Python
        import hls4ml
        
        #Fetch a keras model from our example repository
        #This will download our example model to your working directory and return an example configuration file
        config = hls4ml.utils.fetch_example_model('KERAS_3layer.json')
        
        print(config) #You can print the configuration to see some default parameters
        
        #Convert it to a hls project
        hls_model = hls4ml.converters.keras_to_hls(config)
        
        # Print full list of example models if you want to explore more
        hls4ml.utils.fetch_example_list()
        ```
        
        ### Building a project with Xilinx Vitis (after downloading and installing from [here](https://www.xilinx.com/support/download/index.html/content/xilinx/en/downloadNav/vitis.html))
        
        ```Python
        #Use Vivado HLS to synthesize the model
        #This might take several minutes
        hls_model.build()
        
        #Print out the report if you want
        hls4ml.report.read_vivado_report('my-hls-test')
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
Provides-Extra: profiling
