Address instances of "Overloaded function signature x will never be matched" + minor typing fixes

Summary: Many overloads produced false positives or required changing order due to mypy breaking ties by picking the first matching variant (https://mypy.readthedocs.io/en/stable/more_types.html). This fixes or suppresses these errors. Created T204932142 to address Literal-related issues.

Differential Revision: D64517613

Author: Zach Carmichael

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(

captum/attr/_core/deep_lift.py

@@ -118,36 +118,36 @@ def __init__(
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `120`.
+    #  arguments of overload defined on line `131`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
         baselines: BaselineType = None,
         target: TargetType = None,
-        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `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.
-        return_convergence_delta: Literal[False] = False,
+        return_convergence_delta: Literal[True],
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> TensorOrTupleOfTensorsGeneric: ...
+    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `131`.
+    #  arguments of overload defined on line `120`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
         baselines: BaselineType = None,
         target: TargetType = None,
+        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        *,
-        # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `bool`.
+        # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
         # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-        return_convergence_delta: Literal[True],
+        return_convergence_delta: Literal[False] = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
+    ) -> TensorOrTupleOfTensorsGeneric: ...
 
     @log_usage()
     def attribute(  # type: ignore
@@ -636,7 +636,7 @@ def __init__(self, model: Module, multiply_by_inputs: bool = True) -> None:
     # DeepLiftShap.attribute, so we ignore typing here
     @typing.overload  # type: ignore
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `584`.
+    #  arguments of overload defined on line `597`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
@@ -646,30 +646,31 @@ def attribute(
         target: TargetType = None,
         # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `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.
-        return_convergence_delta: Literal[False] = False,
+        return_convergence_delta: Literal[True],
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> TensorOrTupleOfTensorsGeneric: ...
+    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `597`.
+    #  arguments of overload defined on line `584`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
         baselines: Union[
             TensorOrTupleOfTensorsGeneric, Callable[..., TensorOrTupleOfTensorsGeneric]
         ],
         target: TargetType = None,
+        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        *,
-        # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `bool`.
+        # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
         # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-        return_convergence_delta: Literal[True],
+        return_convergence_delta: Literal[False] = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
+    ) -> TensorOrTupleOfTensorsGeneric: ...
 
     @log_usage()
     def attribute(  # type: ignore

captum/attr/_core/integrated_gradients.py

@@ -81,7 +81,7 @@ def __init__(
     # a tuple with both attributions and deltas.
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `82`.
+    #  arguments of overload defined on line `95`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
@@ -92,29 +92,30 @@ def attribute(
         n_steps: int = 50,
         method: str = "gausslegendre",
         internal_batch_size: Union[None, int] = None,
-        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `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.
-        return_convergence_delta: Literal[False] = False,
-    ) -> TensorOrTupleOfTensorsGeneric: ...
+        return_convergence_delta: Literal[True],
+    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `95`.
+    #  arguments of overload defined on line `82`.
     def attribute(
         self,
         inputs: TensorOrTupleOfTensorsGeneric,
         baselines: BaselineType = None,
         target: TargetType = None,
+        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
         n_steps: int = 50,
         method: str = "gausslegendre",
         internal_batch_size: Union[None, int] = None,
-        *,
-        # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `bool`.
+        # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
         # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-        return_convergence_delta: Literal[True],
-    ) -> Tuple[TensorOrTupleOfTensorsGeneric, Tensor]: ...
+        return_convergence_delta: Literal[False] = False,
+    ) -> TensorOrTupleOfTensorsGeneric: ...
 
     @log_usage()
     def attribute(  # type: ignore

captum/attr/_core/layer/layer_deep_lift.py

@@ -102,40 +102,41 @@ def __init__(
     # Ignoring mypy error for inconsistent signature with DeepLift
     @typing.overload  # type: ignore
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `104`.
+    #  arguments of overload defined on line `117`.
     def attribute(
         self,
         inputs: Union[Tensor, Tuple[Tensor, ...]],
         baselines: BaselineType = None,
         target: TargetType = None,
         # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `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.
-        return_convergence_delta: Literal[False] = False,
+        return_convergence_delta: Literal[True],
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
         grad_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> Union[Tensor, Tuple[Tensor, ...]]: ...
+    ) -> Tuple[Union[Tensor, Tuple[Tensor, ...]], Tensor]: ...
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `117`.
+    #  arguments of overload defined on line `104`.
     def attribute(
         self,
         inputs: Union[Tensor, Tuple[Tensor, ...]],
         baselines: BaselineType = None,
         target: TargetType = None,
+        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        *,
-        # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `bool`.
+        # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
         # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-        return_convergence_delta: Literal[True],
+        return_convergence_delta: Literal[False] = False,
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
         grad_kwargs: Optional[Dict[str, Any]] = None,
-    ) -> Tuple[Union[Tensor, Tuple[Tensor, ...]], Tensor]: ...
+    ) -> Union[Tensor, Tuple[Tensor, ...]]: ...
 
     @log_usage()
     # pyre-fixme[43]: This definition does not have the same decorators as the
@@ -452,7 +453,7 @@ def __init__(
     # Ignoring mypy error for inconsistent signature with DeepLiftShap
     @typing.overload  # type: ignore
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `439`.
+    #  arguments of overload defined on line `453`.
     def attribute(
         self,
         inputs: Union[Tensor, Tuple[Tensor, ...]],
@@ -462,32 +463,33 @@ def attribute(
         target: TargetType = None,
         # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `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.
-        return_convergence_delta: Literal[False] = False,
+        return_convergence_delta: Literal[True],
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> Union[Tensor, Tuple[Tensor, ...]]: ...
+    ) -> Tuple[Union[Tensor, Tuple[Tensor, ...]], Tensor]: ...
 
     @typing.overload
     # pyre-fixme[43]: The implementation of `attribute` does not accept all possible
-    #  arguments of overload defined on line `453`.
+    #  arguments of overload defined on line `439`.
     def attribute(
         self,
         inputs: Union[Tensor, Tuple[Tensor, ...]],
         baselines: Union[
             Tensor, Tuple[Tensor, ...], Callable[..., Union[Tensor, Tuple[Tensor, ...]]]
         ],
         target: TargetType = None,
+        # pyre-fixme[2]: Parameter annotation cannot be `Any`.
         additional_forward_args: Any = None,
-        *,
-        # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
+        # pyre-fixme[9]: return_convergence_delta has type `Literal[]`; used as `bool`.
+        # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
         # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
-        return_convergence_delta: Literal[True],
+        return_convergence_delta: Literal[False] = False,
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
-    ) -> Tuple[Union[Tensor, Tuple[Tensor, ...]], Tensor]: ...
+    ) -> Union[Tensor, Tuple[Tensor, ...]]: ...
 
     @log_usage()
     # pyre-fixme[43]: This definition does not have the same decorators as the