[Fix] Avoid infinite GPU waiting in dist training (open-mmlab#6501)

* [open-mmlab#6495] fix infinite GPU waiting in dist training

* print log_vars keys in assertion msg

* linting issue

mmdet/models/detectors/base.py

@@ -381,6 +381,16 @@ def _parse_losses(self, losses):
         loss = sum(_value for _key, _value in log_vars.items()
                    if 'loss' in _key)
 
+        # If the loss_vars has different length, GPUs will wait infinitely
+        if dist.is_available() and dist.is_initialized():
+            log_var_length = torch.tensor(len(log_vars), device=loss.device)
+            dist.all_reduce(log_var_length)
+            message = (f'rank {dist.get_rank()}' +
+                       f' len(log_vars): {len(log_vars)}' + ' keys: ' +
+                       ','.join(log_vars.keys()))
+            assert log_var_length == len(log_vars) * dist.get_world_size(), \
+                'loss log variables are different across GPUs!\n' + message
+
         log_vars['loss'] = loss
         for loss_name, loss_value in log_vars.items():
             # reduce loss when distributed training