bugifx sentiment training
@@ -290,7 +290,7 @@ def resolve_component_from_parsed_query_data(language, component_type, dataset,
nlp_ref = NameSpace.trainable_models[nlu_ref]
logger.info(f'Found Spark NLP reference in trainable models namespace = {nlp_ref}')
resolved = True
-
+ trainable=True
# 1. check if pipeline references for resolution
if resolved == False and language in NameSpace.pretrained_pipe_references.keys():
if nlu_ref in NameSpace.pretrained_pipe_references[language].keys():
@@ -373,7 +373,7 @@ def resolve_component_from_parsed_query_data(language, component_type, dataset,
f"NLU will ignore this error and continue running, but you will encounter errors most likely. ")
- if nlp_ref =='' and not recurisve_resolve:
+ if nlp_ref == '' and not recurisve_resolve and not trainable and 'en.' not in nlu_ref and language in ['','en']:
# logger.info('')
#Search again but with en. prefixed, enables all refs to work withouth en prefix
return resolve_component_from_parsed_query_data(language, component_type, dataset, component_embeddings, 'en.'+nlu_ref,trainable,path,authenticated,True)
