A PyTorch Converter for SimCLR Checkpoints

This is a converter to convert TensorFlow checkpoints provided in SimCLR repo to PyTorch format, to facilitate related research.

Usage

1. Firstly, download and unzip the checkpoints from SimCLR repo, you will get 3 folders: ResNet50_1x, ResNet50_2x, and ResNet50_4x.

2. Run the following commands to convert the 3 checkpoints:

   python convert.py ResNet50_1x/model.ckpt-225206 resnet50-1x.pth
   python convert.py ResNet50_2x/model.ckpt-225206 resnet50-2x.pth
   python convert.py ResNet50_4x/model.ckpt-225206 resnet50-4x.pth

   You will get 3 PyTorch checkpoints, resnet50-1x.pth, resnet50-2x.pth, resnet50-4x.pth. The model definition is in resent_wider.py.

Performance

To validate the correctness of the conversion, I tested the performance of the models using PyTorch standard augmentation on ImageNet (but without normalization, as the original TF models were not trained with normalization), using commands:

python eval.py /path/to/imagenet -a resnet50-1x/resnet50-2x/resnet50-4x

The performance is:

There is a slight degradation, which should be due to the difference in data pre-processing (e.g., resize) in two frameworks.