Package: pystm32ai
PySTM32.AIA python wrapper for thestm32aicommand-line tool to analyse deep learning models for STM32 microcontrollers.Disclaimer: This project is not related to STMicroelecronics, it is as a wrapper around a component ofX-CUBE-AIproperty of STMicroelecronics and licensed under SLA0048 (see more below).How it worksThe API provide two functions :analyseandgenerate, the first one gives information about the size of a model and the second one can be used to generate C files to link with X-CUBE-AI runtime library (Not provided in this package).The package doesn't include stm32ai executable so it will download and install it automatically on first call.A command line utility is also provided (pystm32ai), however it currently doesn't match the full functionality provided by the originalstm32aiexecutable.InstallationWith pip:pip3installpystm32aiFrom wheel:Download wheel from Releases and install with pip:pip3installpystm32ai-*.whlUsagePython APIThe goal of this tool is to use stm32ai in a deep learning training pipeline, where it can give information about the final model running on STM32frompystm32aiimportstm32aireport=stm32ai.analyse('path/to/model.tflite')print(report)stm32ai.generate('path/to/model.tflite')# C files are generated in the current directoryCommand line toolThe project can also be used as a command line tool:pystm32aianalysepath/to/model.tflite
pystm32aigeneratepath/to/model.tfliteHere is the full usage :usage: pystm32ai [-h] [--allocate-inputs] [--allocate-outputs] [--full-report] [--output_dir OUTPUT_DIR] [--name NAME] {analyse,generate} model_path

Python wrapper around stm32ai command line tool

positional arguments:
  {analyse,generate}    Action to run on stm32ai
  model_path            Path to model

optional arguments:
  -h, --help            show this help message and exit
  --allocate-inputs
  --allocate-outputs
  --full-report
  --output_dir OUTPUT_DIR
  --name NAME           Name of the modelFull API specificationdefanalyse(model_path,allocate_inputs=True,allocate_outputs=False,full_report=False):"""Analyse a model with CubeAI to get info about RAM, ROM and MACCParams:model_path: path to a model (ONNX, h5 or TFLITE)allocate_inputs: whether to allocate input tensor with activationsallocate_outputs: whether to allocate output tensor with activationsfull_report: Get a full report with per-layers informationReturns:A report as a dictionary"""defgenerate(model_path,allocate_inputs=True,allocate_outputs=False,name=None,output_dir="."):"""Generate a model C files to use in a STM32 applicationParams:model_path: path to a model (ONNX, h5 or TFLITE)allocate_inputs: whether to allocate input tensor with activationsallocate_outputs: whether to allocate output tensor with activationsoutput_dir: Path to output directory (default current working directory)"""LicenseThe pystm32ai project is under theMIT LicenseIt's using part of the X-CUBE-AI software which is under SLA0048 license, hence, by using this software you agree to the terms and condition of the SLA048 license. A copy of the license for X-CUBE-AI is provided below:SLA0048 Rev4/March 2018

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