training bug-fix
@@ -130,7 +130,10 @@ class PipelineQueryVerifier():
is_trainable = PipeUtils.is_trainable_pipe(pipe)
conversion_candidates = PipelineQueryVerifier.extract_sentence_embedding_conversion_candidates(pipe)
pipe.has_trainable_components = is_trainable
- if is_trainable : required_features_ref = [] # special case, if training we can reset this
+ if is_trainable and len(provided_features_ref) ==0 :
+ required_features_ref = [] # ['sentence_embedding@u'] # special case, if training we can reset this
+ required_features_no_ref.append('sentence_embeddings') # special case, if training we can reset this
+
components_for_ner_conversion = [] # todo?
missing_features_no_ref = set(required_features_no_ref) - set(provided_features_no_ref)# - set(['text','label'])
