Fix slicing such that left and right context are of equal length

flair/models/relation_classifier_model.py

@@ -256,7 +256,7 @@ def __init__(
         encoding_strategy: EncodingStrategy = TypedEntityMarker(),
         zero_tag_value: str = "O",
         allow_unk_tag: bool = True,
-        max_allowed_tokens_between_entities: int = 50,
+        max_allowed_tokens_between_entities: int = 20,
         max_surrounding_context_length: int = 10,
         **classifierargs,
     ) -> None:
@@ -456,6 +456,8 @@ def _encode_sentence(
         if abs(head_idx - tail_idx) > self._max_allowed_tokens_between_entities:
             return None
 
+        print(head_idx, tail_idx)
+
         # remove excess tokens left and right of entity pair to make encoded sentence shorter
         encoded_sentence_tokens = self._slice_encoded_sentence_to_max_allowed_length(
             encoded_sentence_tokens, head_idx, tail_idx
@@ -480,8 +482,8 @@ def _slice_encoded_sentence_to_max_allowed_length(self, encoded_sentence_tokens,
         padding_amount = self._max_surrounding_context_length
         begin_slice = begin_slice - padding_amount if begin_slice - padding_amount > 0 else 0
         end_slice = (
-            end_slice + padding_amount
-            if end_slice + padding_amount < len(encoded_sentence_tokens)
+            end_slice + padding_amount + 1
+            if end_slice + padding_amount + 1 < len(encoded_sentence_tokens)
             else len(encoded_sentence_tokens)
         )
 
@@ -689,7 +691,9 @@ def predict(
                 )
             )
 
-            sentences_with_relation_reference = [item for item in sentences_with_relation_reference if item[0] is not None]
+            sentences_with_relation_reference = [
+                item for item in sentences_with_relation_reference if item[0] is not None
+            ]
 
             encoded_sentences = [x[0] for x in sentences_with_relation_reference]
             loss = super().predict(