Merge pull request #194 from hls-fpga-machine-learning/pypi

Update for PyPI

.github/workflows/pypi-publish.yml

@@ -0,0 +1,23 @@
+name: 📦 Packaging release to PyPI
+on: 
+  release:
+    types: [released]
+
+jobs:
+  release:
+    name: Upload new release to PyPI
+    runs-on: ubuntu-latest
+    steps:
+    - name: Checkout source
+      uses: actions/checkout@v2
+    - uses: actions/setup-python@v2
+      with:
+        python-version: '3.x' # Version range or exact version of a Python version to use, using SemVer's version range syntax
+    - name: Install dependencies
+      run: python3 -m pip install --user --upgrade setuptools wheel
+    - name: Build package
+      run: python3 setup.py sdist bdist_wheel
+    - name: Publish 📦 to PyPI
+      uses: pypa/gh-action-pypi-publish@master
+      with:
+        password: ${{ secrets.PYPI_PASSWORD }}

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "example-models"]
+	path = example-models
+	url = https://github.com/hls-fpga-machine-learning/example-models.git

README.md

@@ -1,10 +1,57 @@
-<img src="https://hls-fpga-machine-learning.github.io/hls4ml/img/logo.jpg" alt="hls4ml" width="400">
+<p float="left">
+   <img src="https://hls-fpga-machine-learning.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: [email protected]
+**Contact:** [email protected]
 
-For more information visit the webpage: [https://hls-fpga-machine-learning.github.io/hls4ml/](https://hls-fpga-machine-learning.github.io/hls4ml/)
+# 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/thesps/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')
+```