Bugfix nlu comparison persist/load nlg responses

changelog/5201.bugfix.rst

@@ -0,0 +1,9 @@
+Fix bug encountering:
+``Error: No response phrases found for <out_of_scope/other>. 
+Check training data files for a possible wrong intent name in NLU/NLG file`` 
+during NLU pipeline comparison with ``ResponseSelector`` and NLG
+
+When NLU training data is split before NLU pipeline comparison, 
+NLG responses were not also persisted and therefore training for a pipeline including the ``ResponseSelector`` would fail.
+
+NLG responses are now persisted along with NLU data to a ``/train`` directory in the ``run_x/xx%_exclusion`` folder.

rasa/constants.py

@@ -14,6 +14,7 @@
 
 TEST_DATA_FILE = "test.md"
 TRAIN_DATA_FILE = "train.md"
+NLG_DATA_FILE = "responses.md"
 RESULTS_FILE = "results.json"
 NUMBER_OF_TRAINING_STORIES_FILE = "num_stories.json"
 PERCENTAGE_KEY = "__percentage__"

rasa/nlu/test.py

@@ -20,7 +20,7 @@
 
 import rasa.utils.io as io_utils
 
-from rasa.constants import TEST_DATA_FILE, TRAIN_DATA_FILE
+from rasa.constants import TEST_DATA_FILE, TRAIN_DATA_FILE, NLG_DATA_FILE
 from rasa.nlu.constants import (
     DEFAULT_OPEN_UTTERANCE_TYPE,
     RESPONSE_SELECTOR_PROPERTY_NAME,
@@ -1442,9 +1442,16 @@ def compare_nlu(
             training_examples_per_run.append(len(train.training_examples))
 
             model_output_path = os.path.join(run_path, percent_string)
-            train_split_path = os.path.join(model_output_path, TRAIN_DATA_FILE)
-            io_utils.create_path(train_split_path)
-            write_to_file(train_split_path, train.nlu_as_markdown())
+            train_split_path = os.path.join(model_output_path, "train")
+            train_nlu_split_path = os.path.join(
+                model_output_path, "train", TRAIN_DATA_FILE
+            )
+            train_nlg_split_path = os.path.join(
+                model_output_path, "train", NLG_DATA_FILE
+            )
+            io_utils.create_path(train_nlu_split_path)
+            write_to_file(train_nlu_split_path, train.nlu_as_markdown())
+            write_to_file(train_nlg_split_path, train.nlg_as_markdown())
 
             for nlu_config, model_name in zip(configs, model_names):
                 logger.info(