https://pypi.org/project/pytorchautoforge/ Recent updates to the Python Package Index for pyTorchAutoForge en https://pypi.org/project/pytorchautoforge/0.6.0/ 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. petercalifano.gs@gmail.com Fri, 06 Mar 2026 12:40:23 GMT https://pypi.org/project/pytorchautoforge/0.5.0/ 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. petercalifano.gs@gmail.com Wed, 04 Mar 2026 08:42:07 GMT https://pypi.org/project/pytorchautoforge/0.4.3/ 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. petercalifano.gs@gmail.com Sat, 21 Feb 2026 18:29:25 GMT https://pypi.org/project/pytorchautoforge/0.4.2/ 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. petercalifano.gs@gmail.com Sat, 21 Feb 2026 11:51:33 GMT https://pypi.org/project/pytorchautoforge/0.4.1/ 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. petercalifano.gs@gmail.com Mon, 16 Feb 2026 09:24:46 GMT https://pypi.org/project/pytorchautoforge/0.4.0/ 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. petercalifano.gs@gmail.com Sat, 07 Feb 2026 12:35:08 GMT https://pypi.org/project/pytorchautoforge/0.3.0/ 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. petercalifano.gs@gmail.com Sat, 03 Jan 2026 09:09:54 GMT https://pypi.org/project/pytorchautoforge/0.3.1.dev0/ 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. petercalifano.gs@gmail.com Sat, 03 Jan 2026 09:07:43 GMT https://pypi.org/project/pytorchautoforge/0.2.1/ 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. petercalifano.gs@gmail.com Tue, 09 Sep 2025 20:46:40 GMT https://pypi.org/project/pytorchautoforge/0.2.0/ 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. petercalifano.gs@gmail.com Sun, 07 Sep 2025 18:52:03 GMT https://pypi.org/project/pytorchautoforge/0.2.1.dev0/ 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. petercalifano.gs@gmail.com Sun, 07 Sep 2025 18:51:03 GMT https://pypi.org/project/pytorchautoforge/0.2.1.dev10/ 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. petercalifano.gs@gmail.com Sun, 07 Sep 2025 18:50:02 GMT https://pypi.org/project/pytorchautoforge/0.1.3/ 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. petercalifano.gs@gmail.com Fri, 18 Apr 2025 08:31:10 GMT https://pypi.org/project/pytorchautoforge/0.1.2.post1.dev1/ 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. petercalifano.gs@gmail.com Thu, 03 Apr 2025 18:10:40 GMT https://pypi.org/project/pytorchautoforge/0.1.2.post1.dev0/ 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. petercalifano.gs@gmail.com Thu, 03 Apr 2025 17:36:23 GMT https://pypi.org/project/pytorchautoforge/0.1.0b1/ PyTorchAutoForge library is based on raw PyTorch and designed 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. petercalifano.gs@gmail.com Sun, 23 Mar 2025 10:58:39 GMT https://pypi.org/project/pytorchautoforge/0.1.0a1/ PyTorchAutoForge library is based on raw PyTorch and designed 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. petercalifano.gs@gmail.com Sat, 15 Feb 2025 21:27:00 GMT https://pypi.org/project/pytorchautoforge/0.1.0a0/ PyTorchAutoForge library is based on raw PyTorch and designed to automate DNN development, model tracking and deployment, tightly integrated with MLflow and Optuna. It also supports spiking networks libraries (WIP). Model optimization and deployment can be performed using ONNx, pyTorch facilities or TensorRT (WIP). The library also aims to be compatible with Jetson Orin Nano Jetpack rev6.1. petercalifano.gs@gmail.com Mon, 27 Jan 2025 15:14:43 GMT