Merge 9277db0 into 622d6e5

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.4.4-dev0
+current_version = 0.4.5-dev0
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<build>\d+))?

docs/conf.py

@@ -101,7 +101,7 @@
 # built documents.
 #
 # The short X.Y version.
-version = "0.4.4-dev0"
+version = "0.4.5-dev0"
 # The full version, including alpha/beta/rc tags.
 release = ""  # Is set by calling `setup.py docs`
 

setup.cfg

@@ -4,7 +4,7 @@
 
 [metadata]
 name = whylogs
-version = 0.4.4-dev0
+version = 0.4.5-dev0
 description = Profile and monitor your ML data pipeline end-to-end
 author = WhyLabs.ai
 author-email = support@whylabs.ai

src/whylogs/_version.py

@@ -1,3 +1,3 @@
 """WhyLabs version number."""
 
-__version__ = "0.4.4-dev0"
+__version__ = "0.4.5-dev0"

src/whylogs/core/metrics/model_metrics.py

@@ -96,20 +96,21 @@ def merge(self, other):
         """
         if other is None:
             return self
-        if other.confusion_matrix is None and other.regression_metrics is None:
-            # TODO: return a copy instead
-            return self
-        if self.confusion_matrix is None and self.regression_metrics is None:
-            return other
 
-        if self.model_type is None or other.model_type is None:
-            model_type = ModelType.UNKNOWN
-        elif other.model_type != self.model_type:
-            model_type = ModelType.UNKNOWN
+        model_type = ModelType.UNKNOWN
+
+        if (self.model_type not in (ModelType.REGRESSION, ModelType.CLASSIFICATION)):
+            if other.model_type in (ModelType.REGRESSION, ModelType.CLASSIFICATION):
+                model_type = other.model_type
+
+        elif other.model_type not in (ModelType.REGRESSION, ModelType.CLASSIFICATION):
+            if self.model_type in (ModelType.REGRESSION, ModelType.CLASSIFICATION):
+                model_type = self.model_type
         else:
             model_type = self.model_type
 
         return ModelMetrics(
             confusion_matrix=self.confusion_matrix.merge(other.confusion_matrix) if self.confusion_matrix else None,
-            regression_metrics=self.regression_metrics.merge(other.regression_metrics)if self.regression_metrics else None,
+            regression_metrics=self.regression_metrics.merge(
+                other.regression_metrics)if self.regression_metrics else None,
             model_type=model_type)

src/whylogs/core/metrics/regression_metrics.py

@@ -74,6 +74,8 @@ def merge(self, other):
         Returns:
               RegressionMetrics: merged regression metrics
         """
+        if other is None:
+            return self
 
         if self.count == 0:
             return other

tests/unit/core/metrics/test_model_metrics.py

@@ -26,7 +26,7 @@ def tests_model_metrics():
                                                              jdx].floats.count == expected_1[idx][jdx]
 
 
-def tests_model_metrics_to_protobuf():
+def tests_model_metrics_to_protobuf_classification():
     mod_met = ModelMetrics(model_type=ModelType.CLASSIFICATION)
 
     targets_1 = ["cat", "dog", "pig"]
@@ -39,12 +39,45 @@ def tests_model_metrics_to_protobuf():
 
     message = mod_met.to_protobuf()
 
-    ModelMetrics.from_protobuf(message)
+    model_metrics = ModelMetrics.from_protobuf(message)
+    assert model_metrics.model_type == ModelType.CLASSIFICATION
+    assert model_metrics.confusion_matrix.labels == ["cat", "dog", "pig"]
+
+
+def tests_no_metrics_to_protobuf_classification():
+    mod_met = ModelMetrics(model_type=ModelType.CLASSIFICATION)
+
+    assert mod_met.model_type == ModelType.CLASSIFICATION
+    message = mod_met.to_protobuf()
+
+    model_metrics = ModelMetrics.from_protobuf(message)
+    assert model_metrics.model_type == ModelType.CLASSIFICATION
+
+def tests_no_metrics_to_protobuf_regression():
+
+    mod_met = ModelMetrics(model_type=ModelType.REGRESSION)
+    assert mod_met.model_type == ModelType.REGRESSION
+    message = mod_met.to_protobuf()
+
+
+    model_metrics = ModelMetrics.from_protobuf(message)
+    assert model_metrics.model_type == ModelType.REGRESSION
+
+def tests_model_metrics_to_protobuf_regression():
+    regression_model = ModelMetrics(model_type=ModelType.REGRESSION)
+
+    targets_1 = [0.1, 0.3, 0.4]
+    predictions_1 = [0.5, 0.5, 0.5]
+    regression_model.compute_regression_metrics(predictions_1, targets_1)
+    regression_message = regression_model.to_protobuf()
+    model_metrics_from_message = ModelMetrics.from_protobuf(regression_message)
+    assert model_metrics_from_message.model_type == ModelType.REGRESSION
+
 
 
 def test_merge_none():
     metrics = ModelMetrics()
-    metrics.merge(None)
+    assert metrics.merge(None) == metrics
 
 
 def test_merge_metrics_with_none_confusion_matrix():
@@ -54,11 +87,28 @@ def test_merge_metrics_with_none_confusion_matrix():
     new_metrics = metrics.merge(other)
 
 
+def test_merge_metrics_model():
+    metrics = ModelMetrics()
+    other = ModelMetrics(model_type=ModelType.REGRESSION)
+    other.regression_metrics = None
+    new_metrics = metrics.merge(other)
+    assert new_metrics.model_type==ModelType.REGRESSION
+    assert new_metrics.confusion_matrix is None
+
+    # keep initial model type during merge
+    metrics = ModelMetrics(model_type=ModelType.REGRESSION)
+    other = ModelMetrics(model_type=ModelType.CLASSIFICATION)
+    other.regression_metrics = None
+    new_metrics = metrics.merge(other)
+    assert new_metrics.model_type==ModelType.REGRESSION
+    assert new_metrics.confusion_matrix is None
+
 def test_merge_metrics_with_none_regression_matrix():
     metrics = ModelMetrics()
-    other = ModelMetrics()
+    other = ModelMetrics(model_type=ModelType.REGRESSION)
     other.regression_metrics = None
-    new_metrics= metrics.merge(other)
+    new_metrics = metrics.merge(other)
+    assert new_metrics.model_type==ModelType.REGRESSION
 
 def test_merge_metrics_with_none_confusion_matrix():
     metrics = ModelMetrics()
@@ -67,10 +117,11 @@ def test_merge_metrics_with_none_confusion_matrix():
     other.regression_metrics = None
 
     new_metrics = metrics.merge(other)
+    assert new_metrics.model_type == ModelType.UNKNOWN
+
 
 def test_model_metrics_init():
     reg_met = RegressionMetrics()
-    conf_ma= ConfusionMatrix()
+    conf_ma = ConfusionMatrix()
     with pytest.raises(NotImplementedError):
         metrics = ModelMetrics(confusion_matrix=conf_ma, regression_metrics=reg_met)
-