Initial restructuring

.gitignore

@@ -1,5 +1,9 @@
 *.pyc
 __pycache__
+build/
+dist/
+sdist/
+*.egg-info/
 vivado_prj
 .vscode
 my-hls-test

MANIFEST.in

@@ -0,0 +1,6 @@
+include LICENSE
+include README.md
+graft example-prjs
+graft example-models
+graft test
+recursive-include hls4ml/hls-templates *

hls4ml/__init__.py

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+from __future__ import absolute_import
+
+from . import converters

hls4ml/converters/__init__.py

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+from __future__ import absolute_import
+
+from .keras_to_hls import keras_to_hls
+#from .pytorch_to_hls import pytorch_to_hls
+from .onnx_to_hls import onnx_to_hls

hls4ml/model/__init__.py

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+from __future__ import absolute_import
+
+from .hls_model import HLSModel, HLSConfig

scripts/hls4ml

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+#!/usr/bin/env python
+from __future__ import absolute_import
+
+__version__ = '0.2.0'
+
+import argparse
+import os
+import sys
+import yaml
+import hls4ml
+
+def parse_config(config_file):
+    print("Loading configuration from", config_file)
+    config = open(config_file, 'r')
+    return yaml.load(config, Loader=yaml.SafeLoader)
+
+def main():
+    parser = argparse.ArgumentParser(description='HLS4ML - Machine learning inference in FPGAs')
+    subparsers = parser.add_subparsers()
+
+    config_parser = subparsers.add_parser("config", help='Create a conversion configuration file')
+    convert_parser = subparsers.add_parser("convert", help='Convert Keras or ONNX model to HLS')
+    build_parser = subparsers.add_parser("build")
+
+    config_parser.add_argument('-m', '--model', help='Model file to convert (Keras .h5 or .json, or ONNX .onnx file)', default=None)
+    config_parser.add_argument('-w', '--weights', help='Optional weights file (if Keras .json file is provided))', default=None)
+    config_parser.add_argument('-o', '--output', help='Output file name', default=None)
+    config_parser.set_defaults(func=config)
+
+    convert_parser.add_argument('-c', '--config', help='Configuration file', default=None)
+    convert_parser.set_defaults(func=convert)
+
+    build_parser.add_argument('-p', '--project', help='Project directory', default=None)
+    build_parser.add_argument('-c', '--simulation', help='Run C simulation', action='store_true', default=False)
+    build_parser.add_argument('-s', '--synthesis', help='Run C/RTL synthesis', action='store_true', default=False)
+    build_parser.add_argument('-r', '--co-simulation', help='Run C/RTL co-simulation (implies -c and -s)', action='store_true', default=False)
+    build_parser.add_argument('-e', '--export', help='Export IP (implies -s)', action='store_true', default=False)
+    build_parser.add_argument('-a', '--all', help='Run C simulation, C/RTL synthesis and co-simulation', action='store_true')
+    build_parser.set_defaults(func=build)
+
+    parser.add_argument('--version', action='version', version='%(prog)s {version}'.format(version=__version__))
+
+    args = parser.parse_args()
+    if hasattr(args, 'func'):
+        args.func(args)
+    else:
+        parser.print_usage()
+
+def config(args):
+    raise NotImplementedError
+
+def convert(args):
+    yamlConfig = parse_config(args.config)
+    if 'OnnxModel' in yamlConfig:
+        hls4ml.converters.onnx_to_hls(yamlConfig)
+    elif 'PytorchModel' in yamlConfig:
+        hls4ml.converters.pytorch_to_hls(yamlConfig)
+    else:
+        hls4ml.converters.keras_to_hls(yamlConfig)
+
+def build(args):
+    if args.project is None:
+        print('Project directory (-p or --project) must be provided.')
+        sys.exit(1)
+
+    csim = synth = cosim = export = 0
+    if args.simulation:
+        csim = 1
+    if args.synthesis:
+        synth = 1
+    if args.co_simulation:
+        synth = cosim = 1
+    if args.export:
+        synth = export = 1
+    if args.all:
+        csim = synth = cosim = export = 1
+
+    # Check if vivado_hls is available
+    if 'linux' in sys.platform or 'darwin' in sys.platform:
+        found = os.system('command -v vivado_hls > /dev/null')
+        if found is not 0:
+            print('Vivado HLS installation not found. Make sure "vivado_hls" is on PATH.')
+            sys.exit(1)
+
+    os.system('cd {dir} && vivado_hls -f build_prj.tcl "csim={csim} synth={synth} cosim={cosim} export={export}"'.format(dir=args.project, csim=csim, synth=synth, cosim=cosim, export=export))
+
+if __name__== "__main__":
+    main()

setup.cfg

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+[metadata]
+description-file = README.md

setup.py

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+from setuptools import setup
+from setuptools import find_packages
+
+long_description = '''
+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!
+
+For more information visit the webpage:
+https://hls-fpga-machine-learning.github.io/hls4ml/
+'''
+
+setup(name='hls4ml',
+      version='0.2.0',
+      description='Machine learning in FPGAs using HLS',
+      long_description=long_description,
+      author='HLS4ML Team',
+      author_email='[email protected]',
+      url='https://github.com/hls-fpga-machine-learning/hls4ml',
+      license='Apache 2.0',
+      install_requires=['numpy',
+                        'six',
+                        'pyyaml',
+                        'h5py',
+                        'onnx>=1.4.0'],
+      scripts=['scripts/hls4ml'],
+      include_package_data=True,
+      classifiers=[
+          'Development Status :: 3 - Alpha',
+          'Intended Audience :: Developers',
+          'Intended Audience :: Science/Research',
+          'License :: OSI Approved :: Apache Software License',
+          'Programming Language :: C++',
+          'Programming Language :: Python :: 2',
+          'Programming Language :: Python :: 2.7',
+          'Programming Language :: Python :: 3',
+          'Programming Language :: Python :: 3.6',
+          'Topic :: Software Development :: Libraries',
+          'Topic :: Software Development :: Libraries :: Python Modules'
+      ],
+      packages=find_packages())