Base Field interface.
A field processes raw examples and produces Tensors.
setup(self, *data: np.ndarray)¶
Setup the field.
This method will be called with all the data in the dataset and it can be used to compute aggregated information (for example, vocabulary in Fields that process text).
ATTENTION: this method could be called multiple times in case the same field is used in different datasets. Take this into account and build a stateful implementation.
Parameters: *data (np.ndarray) – Multiple 2d arrays (ex: train_data, dev_data, test_data). First dimension is for the examples, second dimension for the columns specified for this specific field.
process(self, *example: Any)¶
Process an example into a Tensor or tuple of Tensor.
This method allows N to M mappings from example columns (N) to tensors (M).
Parameters: *example (Any) – Column values of the example Returns: The processed example, as a tensor or tuple of tensors Return type: Union[torch.Tensor, Tuple[torch.Tensor, ..]]