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])
- ResNet18 - CIFAR10 - 83.9% - Download
- Deep Residual Learning for Image Recognition He et al. Paper
- Identity Mappings in Deep Residual Networks He et al. Paper
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.