add explicit check for dtype to convert to

pytorch_lightning/metrics/converters.py

@@ -77,6 +77,8 @@ def _convert_to_tensor(data: Any) -> Any:
     # is not array of object
     elif isinstance(data, np.ndarray) and np_str_obj_array_pattern.search(data.dtype.str) is None:
         return torch.from_numpy(data)
+    elif isinstance(data, torch.Tensor):
+        return data
 
     raise TypeError("The given type ('%s') cannot be converted to a tensor!" % type(data).__name__)
 
@@ -94,6 +96,8 @@ def _convert_to_numpy(data: Union[torch.Tensor, np.ndarray, numbers.Number]) ->
         return data.cpu().detach().numpy()
     elif isinstance(data, numbers.Number):
         return np.array([data])
+    elif isinstance(data, np.ndarray):
+        return data
 
     raise TypeError("The given type ('%s') cannot be converted to a numpy array!" % type(data).__name__)