Merge branch 'master' into filter-grads

RasaHQ · Apr 22, 2020 · 620cea8 · 620cea8
2 parents 8da3fbb + c3bbc31
commit 620cea8
Show file tree

Hide file tree

Showing 5 changed files with 17 additions and 28 deletions.
diff --git a/.github/ISSUE_TEMPLATE/ask_question.md b/.github/ISSUE_TEMPLATE/ask_question.md
diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -2,7 +2,7 @@
 name: Bug report
 about: Create a report to help us improve
 title: ''
-labels: 'type:bug :bug:'
+labels: 'area:rasa-oss :ferris_wheel:,type:bug :bug:'
 assignees: ''
 
 ---

diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml
@@ -0,0 +1,5 @@
+blank_issues_enabled: false
+contact_links:
+  - name: Ask a question
+    url: https://forum.rasa.com/
+    about: If you have a "How do I?" question please ask in the forum https://forum.rasa.com
diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -2,7 +2,7 @@
 name: Feature request
 about: Suggest an idea on how to improve Rasa
 title: ''
-labels: 'type:enhancement :sparkles:'
+labels: 'area:rasa-oss :ferris_wheel:,type:enhancement :sparkles:'
 assignees: ''
 
 ---

diff --git a/rasa/nlu/classifiers/diet_classifier.py b/rasa/nlu/classifiers/diet_classifier.py
@@ -1191,17 +1191,19 @@ def _combine_sparse_dense_features(
                     )
                 else:
                     _f = f
-                dense_features.append(self._tf_layers[f"sparse_to_dense.{name}"](_f))
+
+                dense_f = self._tf_layers[f"sparse_to_dense.{name}"](_f)
+
+                if dense_dropout:
+                    dense_f = self._tf_layers[f"dense_input_dropout.{name}"](
+                        dense_f, self._training
+                    )
+
+                dense_features.append(dense_f)
             else:
                 dense_features.append(f)
 
-        outputs = tf.concat(dense_features, axis=-1) * mask
-        if dense_dropout:
-            outputs = self._tf_layers[f"dense_input_dropout.{name}"](
-                outputs, self._training
-            )
-
-        return outputs
+        return tf.concat(dense_features, axis=-1) * mask
 
     def _features_as_seq_ids(
         self, features: List[Union[np.ndarray, tf.Tensor, tf.SparseTensor]], name: Text