From 5423b0b07fe8e3dda00bcb5514d3857b90c3acaf Mon Sep 17 00:00:00 2001
From: James Dunham <james@jdunham.io>
Date: Sun, 3 Sep 2017 16:47:42 -0400
Subject: [PATCH] add corresponding changes to neuroner.py

---
 src/neuroner.py | 12 ++++++++----
 1 file changed, 8 insertions(+), 4 deletions(-)

diff --git a/src/neuroner.py b/src/neuroner.py
index cb25314a..f5c96cdb 100644
--- a/src/neuroner.py
+++ b/src/neuroner.py
@@ -79,6 +79,7 @@ def _load_parameters(self, parameters_filepath, arguments={}, verbose=True):
                       'reload_token_lstm':True,
                       'remap_unknown_tokens_to_unk':True,
                       'spacylanguage':'en',
+                      'split_discontinuous':False,
                       'tagging_format':'bioes',
                       'token_embedding_dimension':100,
                       'token_lstm_hidden_state_dimension':100,
@@ -114,7 +115,8 @@ def _load_parameters(self, parameters_filepath, arguments={}, verbose=True):
                 parameters[k] = float(v)
             elif k in ['remap_unknown_tokens_to_unk', 'use_character_lstm', 'use_crf', 'train_model', 'use_pretrained_model', 'debug', 'verbose',
                      'reload_character_embeddings', 'reload_character_lstm', 'reload_token_embeddings', 'reload_token_lstm', 'reload_feedforward', 'reload_crf',
-                     'check_for_lowercase', 'check_for_digits_replaced_with_zeros', 'freeze_token_embeddings', 'load_only_pretrained_token_embeddings', 'load_all_pretrained_token_embeddings']:
+                     'check_for_lowercase', 'check_for_digits_replaced_with_zeros', 'freeze_token_embeddings', 'load_only_pretrained_token_embeddings', 'load_all_pretrained_token_embeddings',
+                     'split_discontinuous']:
                 parameters[k] = distutils.util.strtobool(v)
         # If loading pretrained model, set the model hyperparameters according to the pretraining parameters 
         if parameters['use_pretrained_model']:
@@ -147,7 +149,7 @@ def _get_valid_dataset_filepaths(self, parameters, dataset_types=['train', 'vali
                 if os.path.exists(dataset_brat_folders[dataset_type]) and len(glob.glob(os.path.join(dataset_brat_folders[dataset_type], '*.txt'))) > 0:
     
                     # Check compatibility between conll and brat files
-                    brat_to_conll.check_brat_annotation_and_text_compatibility(dataset_brat_folders[dataset_type])
+                    brat_to_conll.check_brat_annotation_and_text_compatibility(dataset_brat_folders[dataset_type], parameters['split_discontinuous'])
                     if os.path.exists(dataset_compatible_with_brat_filepath):
                         dataset_filepaths[dataset_type] = dataset_compatible_with_brat_filepath
                     conll_to_brat.check_compatibility_between_conll_and_brat_text(dataset_filepaths[dataset_type], dataset_brat_folders[dataset_type])
@@ -168,7 +170,8 @@ def _get_valid_dataset_filepaths(self, parameters, dataset_types=['train', 'vali
                         conll_to_brat.check_compatibility_between_conll_and_brat_text(dataset_filepath_for_tokenizer, dataset_brat_folders[dataset_type])
                     else:
                         # Populate conll file based on brat files
-                        brat_to_conll.brat_to_conll(dataset_brat_folders[dataset_type], dataset_filepath_for_tokenizer, parameters['tokenizer'], parameters['spacylanguage'])
+                        brat_to_conll.brat_to_conll(dataset_brat_folders[dataset_type],
+                                dataset_filepath_for_tokenizer, parameters['tokenizer'], parameters['spacylanguage'], parameters['split_discontinuous'])
                     dataset_filepaths[dataset_type] = dataset_filepath_for_tokenizer
     
                 # Brat text files do not exist
@@ -238,6 +241,7 @@ def __init__(self,
                  reload_token_lstm=argument_default_value,
                  remap_unknown_tokens_to_unk=argument_default_value,
                  spacylanguage=argument_default_value,
+                 split_discontinuous=argument_default_value,
                  tagging_format=argument_default_value,
                  token_embedding_dimension=argument_default_value,
                  token_lstm_hidden_state_dimension=argument_default_value,
@@ -475,7 +479,7 @@ def predict(self, text):
         # Print and output result
         text_filepath = os.path.join(self.stats_graph_folder, 'brat', 'deploy', os.path.basename(dataset_brat_deploy_filepath))
         annotation_filepath = os.path.join(self.stats_graph_folder, 'brat', 'deploy', '{0}.ann'.format(utils.get_basename_without_extension(dataset_brat_deploy_filepath)))
-        text2, entities = brat_to_conll.get_entities_from_brat(text_filepath, annotation_filepath, verbose=True)
+        text2, entities = brat_to_conll.get_entities_from_brat(text_filepath, annotation_filepath, split_discontinuous, verbose=True)
         assert(text == text2)
         return entities