DatasetInterface class removal- refactored as torch.DataLoader objects configured by src/training/recipes, using super_gradients.dataloaders.get() (see new updated tutorials and snippets).

Trainer.build_model() removal- models initialisation refactored with super_gradients.models.get() (see updated tutorials and notebooks).

Coded DDP launch (no need for python -m torch.distributed.launch ...), see new snippets here .

Updated notebooks, tutorials and code snippets in readme.md.

Extract recipes training hyper_params config with super_gradients.training_hyperparams.get() (see updated tutorials and notebooks).

Simplfied resume- now passed through train_params in SgTrainer.train() (see updated snippets in readme.md).

Removal of "loss_loggging_items_names" from train_params in Trainer.train().

Trainer.init old, unnecessary args removed.

Add support for getting models from Deci's platform using super_gradients.models.get(), more info regarding Deci's platform in readme.md.