fix tests and types

Author: tabergma

rasa/nlu/classifiers/diet_classifier.py

@@ -1281,9 +1281,9 @@ def _entity_loss(
 
         # should call first to build weights
         pred_ids = self._tf_layers["crf"](logits, sequence_lengths)
-        loss = self._tf_layers["crf"].loss(
-            logits, c, sequence_lengths
-        )  # pytype: disable=attribute-error
+        # pytype: disable=attribute-error
+        loss = self._tf_layers["crf"].loss(logits, c, sequence_lengths)
+        # pytype: enable=attribute-error
 
         # TODO check that f1 calculation is correct
         # calculate f1 score for train predictions

rasa/nlu/classifiers/embedding_intent_classifier.py

@@ -4,11 +4,7 @@
 from rasa.constants import DOCS_BASE_URL
 from rasa.nlu.components import any_of
 from rasa.nlu.classifiers.diet_classifier import DIETClassifier
-from rasa.nlu.constants import (
-    TEXT,
-    DENSE_FEATURE_NAMES,
-    SPARSE_FEATURE_NAMES,
-)
+from rasa.nlu.constants import TEXT, DENSE_FEATURE_NAMES, SPARSE_FEATURE_NAMES
 from rasa.utils.tensorflow.constants import (
     LABEL,
     HIDDEN_LAYERS_SIZES,
@@ -125,7 +121,7 @@ def __init__(
 
         component_config = component_config or {}
 
-        # the following properties are fixed for the EmbeddingIntentClassifier
+        # the following properties cannot be adapted for the EmbeddingIntentClassifier
         component_config[INTENT_CLASSIFICATION] = True
         component_config[ENTITY_RECOGNITION] = False
         component_config[MASKED_LM] = False

rasa/nlu/extractors/crf_entity_extractor.py

@@ -11,11 +11,7 @@
 from rasa.nlu.training_data import TrainingData, Message
 from rasa.constants import DOCS_BASE_URL
 from rasa.nlu.classifiers.diet_classifier import DIETClassifier
-from rasa.nlu.constants import (
-    TEXT,
-    ENTITIES,
-    TOKENS_NAMES,
-)
+from rasa.nlu.constants import TEXT, ENTITIES, TOKENS_NAMES
 from rasa.utils.tensorflow.constants import (
     HIDDEN_LAYERS_SIZES,
     NUM_TRANSFORMER_LAYERS,
@@ -122,7 +118,7 @@ def __init__(
     ) -> None:
         component_config = component_config or {}
 
-        # the following properties are fixed for the CRFEntityExtractor
+        # the following properties cannot be adapted for the CRFEntityExtractor
         component_config[INTENT_CLASSIFICATION] = False
         component_config[ENTITY_RECOGNITION] = True
         component_config[MASKED_LM] = False

rasa/nlu/selectors/response_selector.py

@@ -85,7 +85,7 @@ class ResponseSelector(DIETClassifier):
 
     requires = [
         any_of(DENSE_FEATURE_NAMES[TEXT], SPARSE_FEATURE_NAMES[TEXT]),
-        any_of(DENSE_FEATURE_NAMES[RESPONSE], SPARSE_FEATURE_NAMES[RESPONSE],),
+        any_of(DENSE_FEATURE_NAMES[RESPONSE], SPARSE_FEATURE_NAMES[RESPONSE]),
     ]
 
     # default properties (DOC MARKER - don't remove)
@@ -175,6 +175,30 @@ class ResponseSelector(DIETClassifier):
     }
     # end default properties (DOC MARKER - don't remove)
 
+    def __init__(
+        self,
+        component_config: Optional[Dict[Text, Any]] = None,
+        inverted_label_dict: Optional[Dict[int, Text]] = None,
+        inverted_tag_dict: Optional[Dict[int, Text]] = None,
+        model: Optional[RasaModel] = None,
+        batch_tuple_sizes: Optional[Dict] = None,
+    ) -> None:
+
+        component_config = component_config or {}
+
+        # the following properties cannot be adapted for the ResponseSelector
+        component_config[INTENT_CLASSIFICATION] = True
+        component_config[ENTITY_RECOGNITION] = False
+        component_config[BILOU_FLAG] = False
+
+        super().__init__(
+            component_config,
+            inverted_label_dict,
+            inverted_tag_dict,
+            model,
+            batch_tuple_sizes,
+        )
+
     @property
     def label_key(self) -> Text:
         return "label_ids"
@@ -224,7 +248,7 @@ def preprocess_train_data(self, training_data: TrainingData) -> RasaModelData:
         )
 
         model_data = self._create_model_data(
-            training_data.intent_examples, label_id_dict, label_attribute=RESPONSE,
+            training_data.intent_examples, label_id_dict, label_attribute=RESPONSE
         )
 
         self.check_input_dimension_consistency(model_data)
@@ -306,7 +330,7 @@ def _create_all_labels(self) -> Tuple[tf.Tensor, tf.Tensor]:
         sequence_lengths_label = self._get_sequence_lengths(mask_label)
 
         label_transformed, _, _, _ = self._create_sequence(
-            self.tf_label_data["label_features"], mask_label, self.label_name,
+            self.tf_label_data["label_features"], mask_label, self.label_name
         )
         cls_label = self._last_token(label_transformed, sequence_lengths_label)
 
@@ -339,7 +363,7 @@ def batch_loss(
         sequence_lengths_label = self._get_sequence_lengths(mask_label)
 
         label_transformed, _, _, _ = self._create_sequence(
-            tf_batch_data["label_features"], mask_label, self.label_name,
+            tf_batch_data["label_features"], mask_label, self.label_name
         )
 
         losses = []

tests/cli/test_rasa_test.py

@@ -58,19 +58,22 @@ def test_test_nlu_cross_validation(run_in_default_project: Callable[..., RunResu
     assert os.path.exists("results/confmat.png")
 
 
-def test_test_nlu_comparison(run_in_default_project: Callable[..., RunResult]):
+def test_test_nlu_comparison(
+    run_in_default_project_without_models: Callable[..., RunResult]
+):
     copyfile("config.yml", "config-1.yml")
 
-    run_in_default_project(
+    run_in_default_project_without_models(
         "test",
         "nlu",
-        "-config",
+        "--config",
         "config.yml",
         "config-1.yml",
         "--run",
         "2",
-        "-percentages",
+        "--percentages",
         "75",
+        "25",
     )
 
     assert os.path.exists("results/run_1")