PyTorch CNN Trainer
A simple package to fine-tune CNNs from torchvision and Pytorch Image models by Ross Wightman.
torchvision convolutional-neural-networks pytorch training fine-tuning code computer-vision demo library

Trainer

A simple package to fine tune CNNs from torchvision and Pytorch Image models from Ross Wightman.

It is very annoying to write training loop and training code for CNN training. Also to support all the training features it takes massive time.

Usually we don't need distributed training and it is very uncomfortable to use argparse and get the job done.

This simplifies the training. It provide you a powerful engine.py which can do lot of training functionalities. Also a dataset.py to load dataset in common scenarios.

It has documentation and examples for common to advanced training scenarios too.

Features: -

  • Support PyTorch image models (timm) training and transfer learning.
  • Quantization Aware training example.
  • Early stopping with patience.
  • Support torchvision models trainging and transfer learning.
  • Support torchvision quantized models transfer learning.
  • Support for Mixed Precision Training.
  • L2 Norm Gradient Penalty.
  • SWA Stochastic weighted Averaging support for training.
  • Keras Like fit method.
  • Customizable Train Step and Validation Step Method
  • Sanity Check method.

Don't forget to tag @oke-aditya in your comment, otherwise they may not be notified.

Authors original post
Deep Learning | Computer Vision
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