tests working

Author: Matt Sokoloff

labelbox/data/serialization/ndjson/classification.py

@@ -120,7 +120,7 @@ def from_common(
                                                ImageData]) -> "NDChecklist":
         return cls(answer=[
             NDFeature(schema_id=answer.feature_schema_id)
-            for answer in checklist.answers
+            for answer in checklist.answer
         ],
                    data_row={'id': data.uid},
                    schema_id=feature_schema_id,

labelbox/data/serialization/ndjson/metric.py

@@ -6,12 +6,14 @@
 from labelbox.data.serialization.ndjson.base import NDJsonBase
 
 
+
+
 class NDScalarMetric(NDJsonBase):
-    metric_name: str
     metric_value: float
+    metric_name: Optional[str]
     feature_name: Optional[str] = None
     subclass_name: Optional[str] = None
-    aggregation: MetricAggregation
+    aggregation: MetricAggregation = MetricAggregation.ARITHMETIC_MEAN.value
 
     def to_common(self) -> ScalarMetric:
         return ScalarMetric(value=self.metric_value,
@@ -24,7 +26,7 @@ def to_common(self) -> ScalarMetric:
     @classmethod
     def from_common(cls, metric: ScalarMetric,
                     data: Union[TextData, ImageData]) -> "NDScalarMetric":
-        return ScalarMetric(uuid=metric.extra.get('uuid'),
+        return cls(uuid=metric.extra.get('uuid'),
                             metric_value=metric.value,
                             metric_name=metric.metric_name,
                             feature_name=metric.feature_name,
@@ -39,8 +41,8 @@ def dict(self, *args, **kwargs):
                 res.pop(field)
 
         # For backwards compatibility.
-        if res['metric_name'] is None:
-            res.pop('metric_name')
+        if res['metricName'] is None:
+            res.pop('metricName')
             res.pop('aggregation')
         return res
 

tests/integration/mal_and_mea/conftest.py

@@ -299,15 +299,25 @@ def predictions(object_predictions, classification_predictions):
 @pytest.fixture
 def model(client, rand_gen, configured_project):
     ontology = configured_project.ontology()
-
     data = {"name": rand_gen(str), "ontology_id": ontology.uid}
-    return client.create_model(data["name"], data["ontology_id"])
-
+    model = client.create_model(data["name"], data["ontology_id"])
+    yield model
+    try:
+        model.delete()
+    except:
+        # Already was deleted by the test
+        pass
 
 @pytest.fixture
 def model_run(rand_gen, model):
     name = rand_gen(str)
-    return model.create_model_run(name)
+    model_run = model.create_model_run(name)
+    yield model_run
+    try:
+        model_run.delete()
+    except:
+        # Already was deleted by the test
+        pass
 
 
 @pytest.fixture