semvec/pypi-packages huggingface dataset:
vitis-quantizer 0.1.3
A standalone package to do the vitis quantization step.
License: Apache 2.0
Keywords: vitis quantize machine learning xilinx

# Vitis Quantizer

**THIS IS NOT AN OFFICIAL XILINX PACKAGE**

A pip installable package to do the vitis model quantization for tensorflow 2.

This is a migration of the code [here](https://github.com/Xilinx/Vitis-AI/tree/master/tools/Vitis-AI-Quantizer/vai_q_tensorflow2.x/tensorflow_model_optimization/python/core/quantization/keras/vitis)
to a standalone pip package that won't conflict with the `tensorflow-model-optimization` package.

Working in the docker image is annoying and this code should be standalone.

## Install

```bash
pip install vitis-quantizer
```

Build from source:

```bash
python3 setup.py bdist_wheel
pip install dist/vitis_quantizer-0.1.0-py3-none-any.whl
```

## Usage

Usage is the same as Vitis AI models.

```python
import tensorflow as tf
import vitis_quantizer

# Train/Get/Make a keras model somehow
model = tf.keras.models.load_model("/path/to/keras/model")
quantizer = vitis_quantizer.VitisQuantizer(model)
with vitis_quantizer.quantize_scope():
    quantized_model = quantizer.quantize_model(calib_dataset=dataset)
    quantized_model.save("/path/to/save/quantized/model")
```

After you have the quantized model saved, use vitis compile.sh script.