Add the SWAG pre-trained weights in TorchVision

[datumbox]

🚀 The feature

It would be great to add support of the pre-trained weights from the Supervised Weakly from hashtAGs (SWAG) to TorchVision. We will focus on porting the weights developed by @lauragustafson @mannatsingh and @aadcock.

There are two sets of weights to add for each model variant:

1. The original frozen trunk SWAG weights with a linear classifier learnt on ImageNet1K
2. The end-to-end fine-tuned weights on ImageNet1K

We will focus on the variants that are currently supported by TorchVision (regnet_y_16gf, regnet_y_32gf, vit_b_16 and vit_l_16). We should also investigate if the larger variants can be added (regnet_y_128gf and vit_h_14) or if they cause issues on our CI (memory, increased execution times etc).

This task includes the following subtasks:

• Convert the weights to be compatible with TorchVision's implementation
• Add the weight entries with the right transform configuration and meta-data
• Add the necessary licensing info (name, URL etc) in the meta-data; update the README to clarify they are offered under CC-BY-NC 4.0
• Verify that the accuracies reported by our reference scripts match the ones reports on the SWAG repo
• Confirm that our CI works well and the additions don't bring significant slowdowns or breakages. If there are such effects, take actions to mitigate