ResNet

In this repository, I have duplicated the ResNet paper. Each of the modules of the ResNet is seperated in a file so users can utilize each block of the resnet seperately and use the ResNet Blocks in their architectures. The link to the paper can be found here: https://arxiv.org/pdf/1512.03385.pdf

The Repository contains the code to create all 5 ResNet architectures:

• ResNet18
• ResNet34
• ResNet50
• ResNet101
• ResNet152

>>> # To get the ResNet18 use
>>> ResNet(nc, ResNetBlock2L, [2, 2, 2, 2])
>>>
>>> # To get the ResNet34 use
>>> ResNet(nc, ResNetBlock2L, [3, 4, 6, 3])
>>>
>>> # To get the ResNet50 use
>>> ResNet(nc, ResNetBlock3L, [3, 4, 6, 3])
>>>
>>> # To get the ResNet101 use
>>> ResNet(nc, ResNetBlock3L, [3, 4, 23 3])
>>>
>>> To get the ResNet152 use
>>> ResNet(nc, ResNetBlock3L, [3, 8, 36, 3])

Pretrained Models

1. ResNet18 - CIFAR10 - 83.9% - Download

References

1. Deep Residual Learning for Image Recognition He et al. Paper
2. Identity Mappings in Deep Residual Networks He et al. Paper

License

The code in this repository is free to use and modify for both commercial and non-commercial use. If possible, just refer back to this repository.