bug fix for logging

value
Out[35]: tensor(3211., device='cuda:0')
value.mean() * batch_size  / batch_size
Out[36]: tensor(3210.9998, device='cuda:0')
value.type(torch.float64).mean() * batch_size / batch_size
Out[37]: tensor(3211., device='cuda:0', dtype=torch.float64)

pytorch_lightning/trainer/connectors/logger_connector/result.py

@@ -185,13 +185,13 @@ def __init__(self, metadata: _Metadata, is_tensor: bool) -> None:
         self.meta = metadata
         self.has_reset = False
         if is_tensor:
-            self.add_state("value", torch.tensor(0, dtype=torch.float), dist_reduce_fx=torch.sum)
+            self.add_state("value", torch.tensor(0, dtype=torch.float64), dist_reduce_fx=torch.sum)
             if self.meta.is_mean_reduction:
-                self.add_state("cumulated_batch_size", torch.tensor(0, dtype=torch.float), dist_reduce_fx=torch.sum)
+                self.add_state("cumulated_batch_size", torch.tensor(0, dtype=torch.float64), dist_reduce_fx=torch.sum)
 
     def update(self, value: _IN_METRIC, batch_size: torch.Tensor) -> None:
         if self.is_tensor:
-            value = value.float()
+            value = value.type(torch.float64)
             # performance: no need to accumulate on values only logged on_step
             if self.meta.on_step and not self.meta.on_epoch:
                 self._forward_cache = self.value = self.meta.sync(value)