v1.2.1

• Upgraded to transformers==2.9.0 which has many performance improvements + bug fixes
• Using common loop for training/evaluation/testing to remove duplicate code
• Added support for specifying decoupling function in train_model() (and get_all_predictions()) to define how to extract the inputs (and targets) from a batch
  • This may be useful in case this process deviates from the typical behavior, but the training paradigm is otherwise the same, and hence train_model() can still be used
• Removed dependency on vrdscommon
  • The timing decorator was being imported from vrdscommon; now one is defined in the package itself
  • As a result of this, added support for defining decorators
• Added/improved util functions:
  • get_total_grad_norm()
  • compare_tensors_or_arrays()
  • is_batch_on_gpu()
  • is_model_on_gpu()
  • is_model_parallelized()
  • remove_dir()
  • save_object() now also supports saving YAML files
• Minor cleanup and linting