Add stacklevel to across captum to satisfy flake8

captum/_utils/av.py

@@ -330,7 +330,8 @@ def _manage_loading_layers(
                 "Overwriting activations: load_from_disk is set to False. Removing all "
                 f"activations matching specified parameters {{path: {path}, "
                 f"model_id: {model_id}, layers: {layers}, identifier: {identifier}}} "
-                "before generating new activations."
+                "before generating new activations.",
+                stacklevel=1,
             )
             for layer in layers:
                 files = glob.glob(

captum/_utils/common.py

@@ -73,17 +73,17 @@ def safe_div(
 @typing.overload
 # pyre-fixme[43]: The return type of overloaded function `_is_tuple` (`Literal[]`)
 #  is incompatible with the return type of the implementation (`bool`).
-# pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
+# pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
 # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-def _is_tuple(inputs: Tensor) -> Literal[False]: ...
+def _is_tuple(inputs: Tuple[Tensor, ...]) -> Literal[True]: ...
 
 
 @typing.overload
 # pyre-fixme[43]: The return type of overloaded function `_is_tuple` (`Literal[]`)
 #  is incompatible with the return type of the implementation (`bool`).
-# pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+# pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
 # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-def _is_tuple(inputs: Tuple[Tensor, ...]) -> Literal[True]: ...
+def _is_tuple(inputs: Tensor) -> Literal[False]: ...
 
 
 def _is_tuple(inputs: Union[Tensor, Tuple[Tensor, ...]]) -> bool:
@@ -277,7 +277,7 @@ def _format_additional_forward_args(
 
 
 @overload
-def _format_additional_forward_args(
+def _format_additional_forward_args(  # type: ignore
     # pyre-fixme[2]: Parameter annotation cannot be `Any`.
     additional_forward_args: Any,
     # pyre-fixme[24]: Generic type `tuple` expects at least 1 type parameter.
@@ -780,10 +780,10 @@ def _reduce_list(
     """
     assert len(val_list) > 0, "Cannot reduce empty list!"
     if isinstance(val_list[0], torch.Tensor):
-        # pyre-fixme[16]: `bool` has no attribute `device`.
-        first_device = val_list[0].device
-        # pyre-fixme[16]: `bool` has no attribute `to`.
-        return red_func([elem.to(first_device) for elem in val_list])
+        first_device = cast(Tensor, val_list[0]).device
+        return red_func(
+            [elem.to(first_device) for elem in cast(List[Tensor], val_list)]
+        )
     elif isinstance(val_list[0], bool):
         # pyre-fixme[7]: Expected `TupleOrTensorOrBoolGeneric` but got `bool`.
         return any(val_list)

captum/_utils/gradient.py

@@ -159,33 +159,34 @@ def _neuron_gradients(
 
 @typing.overload
 # pyre-fixme[43]: The implementation of `_forward_layer_eval` does not accept all
-#  possible arguments of overload defined on line `158`.
+#  possible arguments of overload defined on line `170`.
 def _forward_layer_eval(
     # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
     forward_fn: Callable,
     inputs: Union[Tensor, Tuple[Tensor, ...]],
-    layer: Module,
+    layer: List[Module],
     # pyre-fixme[2]: Parameter annotation cannot be `Any`.
     additional_forward_args: Any = None,
     device_ids: Union[None, List[int]] = None,
     attribute_to_layer_input: bool = False,
     grad_enabled: bool = False,
-) -> Tuple[Tensor, ...]: ...
+) -> List[Tuple[Tensor, ...]]: ...
 
 
 @typing.overload
 # pyre-fixme[43]: The implementation of `_forward_layer_eval` does not accept all
-#  possible arguments of overload defined on line `170`.
+#  possible arguments of overload defined on line `158`.
 def _forward_layer_eval(
     # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
     forward_fn: Callable,
     inputs: Union[Tensor, Tuple[Tensor, ...]],
-    layer: List[Module],
+    layer: Module,
+    # pyre-fixme[2]: Parameter annotation cannot be `Any`.
     additional_forward_args: Any = None,
     device_ids: Union[None, List[int]] = None,
     attribute_to_layer_input: bool = False,
     grad_enabled: bool = False,
-) -> List[Tuple[Tensor, ...]]: ...
+) -> Tuple[Tensor, ...]: ...
 
 
 def _forward_layer_eval(
@@ -434,34 +435,34 @@ def _forward_layer_eval_with_neuron_grads(
 
 @typing.overload
 # pyre-fixme[43]: The implementation of `_forward_layer_eval_with_neuron_grads` does
-#  not accept all possible arguments of overload defined on line `392`.
+#  not accept all possible arguments of overload defined on line `405`.
 def _forward_layer_eval_with_neuron_grads(
     # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
     forward_fn: Callable,
     inputs: Union[Tensor, Tuple[Tensor, ...]],
-    layer: Module,
+    layer: List[Module],
     additional_forward_args: Any = None,
     gradient_neuron_selector: None = None,
     grad_enabled: bool = False,
     device_ids: Union[None, List[int]] = None,
     attribute_to_layer_input: bool = False,
-) -> Tuple[Tensor, ...]: ...
+) -> List[Tuple[Tensor, ...]]: ...
 
 
 @typing.overload
 # pyre-fixme[43]: The implementation of `_forward_layer_eval_with_neuron_grads` does
-#  not accept all possible arguments of overload defined on line `405`.
+#  not accept all possible arguments of overload defined on line `392`.
 def _forward_layer_eval_with_neuron_grads(
     # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
     forward_fn: Callable,
     inputs: Union[Tensor, Tuple[Tensor, ...]],
-    layer: List[Module],
+    layer: Module,
     additional_forward_args: Any = None,
     gradient_neuron_selector: None = None,
     grad_enabled: bool = False,
     device_ids: Union[None, List[int]] = None,
     attribute_to_layer_input: bool = False,
-) -> List[Tuple[Tensor, ...]]: ...
+) -> Tuple[Tensor, ...]: ...
 
 
 def _forward_layer_eval_with_neuron_grads(