Sinapsis Framework Converter
Templates for conversion between deep learning frameworks.
🐍 Installation • 🚀 Features 📙 Documentation • 🔍 License
The sinapsis-framework-converter module allows for the conversion between some of the most popular deep learning frameworks in the community:
- Keras -> Tensorflow
- Tensorflow -> ONNX
- Pytorch -> TensorRT
- Pytorch -> ONNX
- ONNX -> TensorRT
🐍 Installation
[!NOTE] CUDA-based templates in Sinapsis-framework-converter require NVIDIA driver version to be 550 or higher.
Install using your package manager of choice. We encourage the use of uv
Example with uv:
uv pip install sinapsis-framework-converter --extra-index-url https://pypi.sinapsis.tech
or with raw pip:
pip install sinapsis-framework-converter --extra-index-url https://pypi.sinapsis.tech
[!IMPORTANT] Templates in each package may require extra dependencies. For development, we recommend installing the package with all the optional dependencies:
Example with uv:
uv pip install sinapsis-framework-converter[all] --extra-index-url https://pypi.sinapsis.tech
or with raw pip:
pip install sinapsis-framework-converter[all] --extra-index-url https://pypi.sinapsis.tech
[!IMPORTANT] To enable tensorflow with cuda support please install
tensorflowas follows:
uv pip install tensorflow[and-cuda]==2.18.0
or
pip install tensorflow[and-cuda]==2.18.0
🚀 Features
Templates Supported
The Sinapsis Framework Converter module provides multiple templates for deep learning framework conversion.
- KerasTensorFlowConverter: Converts Keras models to TensorFlow.
- ONNXTRTConverter: Converts ONNX models to TensorRT.
- TensorFlowONNXConverter: Converts TensorFlow models to ONNX.
- TorchONNXConverter: Converts PyTorch models to ONNX.
- TorchTRTConverter: Converts PyTorch models to TensorRT.
▶️ Example Usage
The following example demonstrates how to use the TorchONNXConverter template to convert a PyTorch model into the ONNX format. The configuration sets up an agent with the necessary templates to load a model, convert it, and store the converted file. Below is the full YAML configuration, followed by a breakdown of each component.
agent:
name: conversion_agent
templates:
- template_name: InputTemplate
class_name: InputTemplate
attributes: {}
- template_name: TorchONNXConverter
class_name: TorchONNXConverter
template_input: InputTemplate
attributes:
model_name: resnet50
save_model_path: true
force_compilation: true
opset_version: 12
height: 224
width: 224
This configuration defines an agent and a sequence of templates to perform model conversion.
- Input Handling (
InputTemplate): This serves as the initial template. - Model Conversion (
TorchONNXConverter): Loads a PyTorch model (e.g.,resnet50) and converts it to ONNX format. The template:- Uses the
model_nameattribute to specify which PyTorch model to convert. - Applies the
opset_versionattribute to define the ONNX operator set version (e.g.,12). - Adjusts the input tensor dimensions using
heightandwidth. - Enables
force_compilationto ensure the model is recompiled if needed.
- Uses the
- Saving the Converted Model: The
save_model_pathattribute is set totrue, ensuring that the output ONNX model path is saved in the DataContainer.
📙 Documentation
Documentation is available on the sinapsis website
Tutorials for different projects within sinapsis are available at sinapsis tutorials page
🔍 License
This project is licensed under the AGPLv3 license, which encourages open collaboration and sharing. For more details, please refer to the LICENSE file.
For commercial use, please refer to our official Sinapsis website for information on obtaining a commercial license.
Metadata
Release files for sinapsis-framework-converter 0.1.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sinapsis_framework_converter-0.1.11.tar.gz | 29.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sinapsis_framework_converter-0.1.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 64.2 kB
Release files / sinapsis_framework_converter-0.1.11.tar.gz
| Download URL | sinapsis_framework_converter-0.1.11.tar.gz |
|---|---|
| Size | 29.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
65bfbd5a24530b1139ea6d571d0683c9d424d4302b1a195423ce769e6a340e2e
|
|
BLAKE2b-256 checksum How to use checksums |
cf976f100e563893903efb39386e48bb1a71dbee5960ddb242f1daf9157af108
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.5.16
|
Release files / sinapsis_framework_converter-0.1.11-py3-none-any.whl
| Download URL | sinapsis_framework_converter-0.1.11-py3-none-any.whl |
|---|---|
| Size | 35.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
933fbebcd5837d93a4efb59254592605a49db25b5a9f229345a9f5c28f7a1cba
|
|
BLAKE2b-256 checksum How to use checksums |
07f8d27b1ea4ad6074381d7b6f0379bb245107292e6fd12238e9adf2683d2093
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.5.16
|