Fix

mmcv/runner/fp16_utils.py

@@ -22,10 +22,10 @@
     pass
 
 
-def cast_tensor_type(inputs: Union[torch.Tensor, nn.Module, str, np.ndarray,
-                                   abc.Mapping, abc.Iterable],
-                     src_type: torch.dtype,
-                     dst_type: torch.dtype) -> torch.Tensor:
+def cast_tensor_type(
+    inputs: Union[torch.Tensor, nn.Module, str, np.ndarray, abc.Mapping,
+                  abc.Iterable], src_type: torch.dtype, dst_type: torch.dtype
+) -> Union[torch.Tensor, nn.Module, str, abc.Mapping, abc.Iterable]:
     """Recursively convert Tensor in inputs from src_type to dst_type.
 
     Note:
@@ -56,13 +56,13 @@ def cast_tensor_type(inputs: Union[torch.Tensor, nn.Module, str, np.ndarray,
     elif isinstance(inputs, np.ndarray):
         return inputs
     elif isinstance(inputs, abc.Mapping):
-        return type(inputs)({  # type: ignore
+        return type(inputs)({  # type:ignore
             k: cast_tensor_type(v, src_type, dst_type)
             for k, v in inputs.items()
         })
     elif isinstance(inputs, abc.Iterable):
-        return type(inputs)(  # type: ignore
-            cast_tensor_type(item, src_type, dst_type) for item in inputs)
+        return type(inputs)(cast_tensor_type(item, src_type, dst_type)
+                            for item in inputs)  # type:ignore
     else:
         return inputs
 
@@ -360,7 +360,7 @@ class LossScaler:
     """
 
     def __init__(self,
-                 init_scale: float = 2**32,
+                 init_scale: float = 2.**32,
                  mode: str = 'dynamic',
                  scale_factor: float = 2.,
                  scale_window: int = 1000):