Return consistent types from metrics (#4632)

* Return consistent types from metrics

* Changelog

* Remove unused import

Author: dirkgr

CHANGELOG.md

@@ -20,6 +20,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 
 - Ignore *args when constructing classes with `FromParams`.
+- Ensured some consistency in the types of the values that metrics return
 
 ## [v1.1.0](https://github.com/allenai/allennlp/releases/tag/v1.1.0) - 2020-09-08
 

allennlp/training/metrics/average.py

@@ -49,10 +49,10 @@ def get_metric(self, reset: bool = False):
         The average of all values that were passed to `__call__`.
         """
 
-        average_value = self._total_value / self._count if self._count > 0 else 0
+        average_value = self._total_value / self._count if self._count > 0 else 0.0
         if reset:
             self.reset()
-        return average_value
+        return float(average_value)
 
     @overrides
     def reset(self):

allennlp/training/metrics/perplexity.py

@@ -1,5 +1,5 @@
 from overrides import overrides
-import torch
+import math
 
 from allennlp.training.metrics.average import Average
 from allennlp.training.metrics.metric import Metric
@@ -26,9 +26,7 @@ def get_metric(self, reset: bool = False):
         """
         average_loss = super().get_metric(reset)
         if average_loss == 0:
-            perplexity = 0.0
+            return 0.0
 
         # Exponentiate the loss to compute perplexity
-        perplexity = float(torch.exp(average_loss))
-
-        return perplexity
+        return math.exp(average_loss)