Pytorch-metric-learning

Fixed some module import issues.

Features

- Added the [Datasets](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets) module for easy downloading of common datasets:
- [CUB200](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cub-200-2011)
- [Cars196](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#cars196)
- [INaturalist 2018](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#inaturalist2018)
- [Stanford Online Products](https://kevinmusgrave.github.io/pytorch-metric-learning/datasets/#stanfordonlineproducts)

Thanks ir2718!

Features

- Added [ThresholdConsistentMarginLoss](https://kevinmusgrave.github.io/pytorch-metric-learning/losses/#thresholdconsistentmarginloss).

Thank you ir2718!

Improvement + small breaking change to `DistributedLossWrapper`

- Changed the `emb` argument of `DistributedLossWrapper.forward` to `embeddings` to be consistent with the rest of the library.
- Added a warning and early-return when `DistributedLossWrapper` is being used in a non-distributed setting.
- Thank you elisim!

Improvements

- [Allow scaling up the memory and batch size when using TripletMarginMiner](https://github.com/KevinMusgrave/pytorch-metric-learning/issues/688)
- Pull request: https://github.com/KevinMusgrave/pytorch-metric-learning/pull/689

Thanks mkmenta !

This is identical to v2.4.0, but includes the LICENSE file which was missing from v2.4.0.