Constructs a Res2Net-50_14w_8s model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a Res2Net-50_26w_4s model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a Res2Net-50_26w_4s model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a Res2Net-50_26w_4s model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

Constructs a Res2Net-50_48w_2s model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrai

r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrai

r"""ResNet-18 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrain

r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_. Args: pretrain

r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_.

r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_. A

Save checkpoint to file. The checkpoint will have 3 fields: ``meta``, ``state_dict`` and ``optimizer``. By default ``meta`` will contain vers

r"""Wide ResNet-101-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. The model is the same as ResNet excep

r"""Wide ResNet-50-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_. The model is the same as ResNet except