docs/source/models/resnet.rst
.. currentmodule:: torchvision.models
The ResNet model is based on the Deep Residual Learning for Image Recognition <https://arxiv.org/abs/1512.03385>_ paper.
.. note::
The bottleneck of TorchVision places the stride for downsampling to the second 3x3
convolution while the original paper places it to the first 1x1 convolution.
This variant improves the accuracy and is known as ResNet V1.5 <https://ngc.nvidia.com/catalog/model-scripts/nvidia:resnet_50_v1_5_for_pytorch>_.
The following model builders can be used to instantiate a ResNet model, with or
without pre-trained weights. All the model builders internally rely on the
torchvision.models.resnet.ResNet base class. Please refer to the source code <https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>_ for
more details about this class.
.. autosummary:: :toctree: generated/ :template: function.rst
resnet18
resnet34
resnet50
resnet101
resnet152