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Author:
None
License:
MIT
Summary:
PyTorchAutoForge library is based on raw PyTorch and designed to automate DNN development, model tracking and deployment, tightly integrated with MLflow and Optuna. It supports Spiking networks libraries (WIP). Deployment can be performed using ONNX, pyTorch facilities or TensorRT (WIP). The library is designed to be compatible with Jetson Orin Nano Jetpack rev6.1, with bash script to automatically configure virtualenv.
Latest version:
0.6.0
Required dependencies:
albumentations
|
captum
|
colorama
|
dacite
|
expelliarmus
|
inputimeout
|
kornia
|
matplotlib
|
mlflow
|
msgpack
|
mypy
|
norse
|
numpy
|
onnx
|
onnxruntime
|
onnxscript
|
optuna
|
pynvml
|
pytest
|
scikit-learn
|
scipy
|
seaborn
|
statsmodels
|
tonic
|
torch
|
torch-tb-profiler
|
torchinfo
|
torchvision
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