medcat.rel_cat

Module Contents

Classes

RelCAT

The RelCAT class used for training 'Relation-Annotation' models, i.e., annotation of relations
class medcat.rel_cat.RelCAT(cdb, tokenizer, config=ConfigRelCAT(), task='train', init_model=False)

Bases: medcat.pipeline.pipe_runner.PipeRunner

The RelCAT class used for training ‘Relation-Annotation’ models, i.e., annotation of relations

between clinical concepts.

Parameters:

  • cdb (CDB) – cdb, this is used when creating relation datasets.

  • tokenizer (TokenizerWrapperBERT) – The Huggingface tokenizer instance. This can be a pre-trained tokenzier instance from a BERT-style model. For now, only BERT models are supported.

  • config (ConfigRelCAT) – the configuration for RelCAT. Param descriptions available in ConfigRelCAT docs.

  • task (str, optional) – What task is this model supposed to handle. Defaults to “train”

  • init_model (bool, optional) – loads default model. Defaults to False.

name = 'rel_cat'
log
__init__(cdb, tokenizer, config=ConfigRelCAT(), task='train', init_model=False)
Parameters:
save(save_path)
Saves model and its dependencies to specified save_path folder.

The CDB is obviously not saved, it is however necessary to save the tokenizer used.

Parameters:

save_path (str) – folder path in which to save the model & deps.

Return type:

None

_get_model()

Used only for model initialisation.

classmethod load(load_path='./')
Parameters:

load_path (str) –

Return type:

RelCAT

_create_test_train_datasets(data, split_sets=False)
Parameters:

  • data (Dict) –

  • split_sets (bool) –

train(export_data_path='', train_csv_path='', test_csv_path='', checkpoint_path='./')
Parameters:

  • export_data_path (str) –

  • train_csv_path (str) –

  • test_csv_path (str) –

  • checkpoint_path (str) –

evaluate_(output_logits, labels, ignore_idx)
evaluate_results(data_loader, pad_id)
pipe(stream, *args, **kwargs)
Parameters:

stream (Iterable[spacy.tokens.Doc]) –

Return type:

Iterator[spacy.tokens.Doc]

__call__(doc)
Parameters:

doc (spacy.tokens.Doc) –

Return type:

spacy.tokens.Doc