refactored variable names

Author: dakshvar22

tests/nlu/featurizers/test_lm_featurizer.py

@@ -5,11 +5,11 @@
 from rasa.nlu.featurizers.dense_featurizer.lm_featurizer import LanguageModelFeaturizer
 from rasa.nlu.utils.hugging_face.hf_transformers import HFTransformersNLP
 from rasa.nlu.constants import (
-    TEXT_ATTRIBUTE,
+    TEXT,
     DENSE_FEATURE_NAMES,
     TOKENS_NAMES,
-    RESPONSE_ATTRIBUTE,
-    INTENT_ATTRIBUTE,
+    RESPONSE,
+    INTENT,
     LANGUAGE_MODEL_DOCS,
 )
 from rasa.nlu.training_data import Message
@@ -206,7 +206,7 @@ def test_lm_featurizer_shape_values(
 
     for index in range(len(texts)):
 
-        computed_feature_vec = messages[index].get(DENSE_FEATURE_NAMES[TEXT_ATTRIBUTE])
+        computed_feature_vec = messages[index].get(DENSE_FEATURE_NAMES[TEXT])
         computed_sequence_vec, computed_sentence_vec = (
             computed_feature_vec[:-1],
             computed_feature_vec[-1],
@@ -226,6 +226,6 @@ def test_lm_featurizer_shape_values(
             computed_sentence_vec[:5], expected_cls_vec[index], atol=1e-5
         )
 
-        intent_vec = messages[index].get(DENSE_FEATURE_NAMES[INTENT_ATTRIBUTE])
+        intent_vec = messages[index].get(DENSE_FEATURE_NAMES[INTENT])
 
         assert intent_vec is None

tests/nlu/tokenizers/test_lm_tokenizer.py

@@ -1,7 +1,7 @@
 import pytest
 
 from rasa.nlu.training_data import Message, TrainingData
-from rasa.nlu.constants import TEXT_ATTRIBUTE, INTENT_ATTRIBUTE, TOKENS_NAMES
+from rasa.nlu.constants import TEXT, INTENT, TOKENS_NAMES
 from rasa.nlu.tokenizers.lm_tokenizer import LanguageModelTokenizer
 from rasa.nlu.utils.hugging_face.hf_transformers import HFTransformersNLP
 
@@ -306,7 +306,7 @@ def test_lm_tokenizer_edge_cases(model_name, texts, expected_tokens, expected_in
 
         message = Message.build(text=text)
         transformers_nlp.process(message)
-        tokens = lm_tokenizer.tokenize(message, TEXT_ATTRIBUTE)
+        tokens = lm_tokenizer.tokenize(message, TEXT)
 
         assert [t.text for t in tokens] == gt_tokens
         assert [t.start for t in tokens] == [i[0] for i in gt_indices]
@@ -330,13 +330,11 @@ def test_lm_tokenizer_custom_intent_symbol(text, expected_tokens):
     lm_tokenizer = LanguageModelTokenizer(component_config)
 
     message = Message(text)
-    message.set(INTENT_ATTRIBUTE, text)
+    message.set(INTENT, text)
 
     td = TrainingData([message])
 
     transformers_nlp.train(td)
     lm_tokenizer.train(td)
 
-    assert [
-        t.text for t in message.get(TOKENS_NAMES[INTENT_ATTRIBUTE])
-    ] == expected_tokens
+    assert [t.text for t in message.get(TOKENS_NAMES[INTENT])] == expected_tokens