1) Inferring tables from columns predicted 2) Mix them with the predicted tables if any 3) Inferring conditions based on tab

Saving best-practices: if you use default names for the model, you can reload it using from_pretrained(). Will only save fro

Scan the index of 'as' and build the map for all alias

Shift input ids one token to the right, and wrap the last non pad token (usually <eos>).

Shift input ids one token to the right, and wrap the last non pad token (usually <eos>).

Main training entry point. Args: model_path: (Optional) Local path to model if model to train has been i

Checks that `node` conforms to the current ASDL.

Trainer is a simple but feature-complete training and eval loop for PyTorch, optimized for Transformers. Args: p

Trainer is a simple but feature-complete training and eval loop for PyTorch, optimized for Transformers. Args: p