Correct remaining typing.Literal imports (#1412)

Summary: Pull Request resolved: #1412 Change remaining imports of `Literal` to be from `typing` library Reviewed By: vivekmig Differential Revision: D64807610 fbshipit-source-id: e7266e7258a4123777fbb8103bd8d48d9afe4ff6
pytorch · Oct 24, 2024 · 0be76f9 · 0be76f9
1 parent e2c06ed
commit 0be76f9
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Showing 12 changed files with 42 additions and 143 deletions.
diff --git a/captum/_utils/common.py b/captum/_utils/common.py
@@ -5,13 +5,23 @@
 from enum import Enum
 from functools import reduce
 from inspect import signature
-from typing import Any, Callable, cast, Dict, List, overload, Sequence, Tuple, Union
+from typing import (
+    Any,
+    Callable,
+    cast,
+    Dict,
+    List,
+    Literal,
+    overload,
+    Sequence,
+    Tuple,
+    Union,
+)
 
 import numpy as np
 import torch
 from captum._utils.typing import (
     BaselineType,
-    Literal,
     TargetType,
     TensorOrTupleOfTensorsGeneric,
     TupleOrTensorOrBoolGeneric,
@@ -71,23 +81,17 @@ 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[True]` is not a valid type.
-# pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
 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[False]` is not a valid type.
-# pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
 def _is_tuple(inputs: Tensor) -> Literal[False]: ...
 
 
 @typing.overload
-def _is_tuple(inputs: TensorOrTupleOfTensorsGeneric) -> bool: ...
+def _is_tuple(
+    inputs: TensorOrTupleOfTensorsGeneric,
+) -> bool: ...  # type: ignore
 
 
 def _is_tuple(inputs: Union[Tensor, Tuple[Tensor, ...]]) -> bool:
@@ -480,22 +484,14 @@ def _expand_and_update_feature_mask(n_samples: int, kwargs: dict) -> None:
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_format_output` does not accept all
-#  possible arguments of overload defined on line `449`.
 def _format_output(
-    # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     is_inputs_tuple: Literal[True],
     output: Tuple[Tensor, ...],
 ) -> Tuple[Tensor, ...]: ...
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_format_output` does not accept all
-#  possible arguments of overload defined on line `455`.
 def _format_output(
-    # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     is_inputs_tuple: Literal[False],
     output: Tuple[Tensor, ...],
 ) -> Tensor: ...
@@ -526,22 +522,14 @@ def _format_output(
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_format_outputs` does not accept all
-#  possible arguments of overload defined on line `483`.
 def _format_outputs(
-    # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     is_multiple_inputs: Literal[False],
     outputs: List[Tuple[Tensor, ...]],
 ) -> Union[Tensor, Tuple[Tensor, ...]]: ...
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_format_outputs` does not accept all
-#  possible arguments of overload defined on line `489`.
 def _format_outputs(
-    # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     is_multiple_inputs: Literal[True],
     outputs: List[Tuple[Tensor, ...]],
 ) -> List[Union[Tensor, Tuple[Tensor, ...]]]: ...

diff --git a/captum/_utils/gradient.py b/captum/_utils/gradient.py
@@ -5,7 +5,18 @@
 import typing
 import warnings
 from collections import defaultdict
-from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Tuple, Union
+from typing import (
+    Any,
+    Callable,
+    cast,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
 
 import torch
 from captum._utils.common import (
@@ -16,7 +27,6 @@
 )
 from captum._utils.sample_gradient import SampleGradientWrapper
 from captum._utils.typing import (
-    Literal,
     ModuleOrModuleList,
     TargetType,
     TensorOrTupleOfTensorsGeneric,
@@ -226,9 +236,6 @@ def _forward_layer_distributed_eval(
     # pyre-fixme[2]: Parameter annotation cannot be `Any`.
     additional_forward_args: Any = None,
     attribute_to_layer_input: bool = False,
-    # pyre-fixme[9]: forward_hook_with_return 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.
     forward_hook_with_return: Literal[False] = False,
     require_layer_grads: bool = False,
 ) -> Dict[Module, Dict[device, Tuple[Tensor, ...]]]: ...
@@ -246,8 +253,6 @@ def _forward_layer_distributed_eval(
     additional_forward_args: Any = None,
     attribute_to_layer_input: bool = False,
     *,
-    # pyre-fixme[31]: Expression `Literal[True]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     forward_hook_with_return: Literal[True],
     require_layer_grads: bool = False,
 ) -> Tuple[Dict[Module, Dict[device, Tuple[Tensor, ...]]], Tensor]: ...
@@ -675,7 +680,6 @@ def compute_layer_gradients_and_eval(
             target_ind=target_ind,
             additional_forward_args=additional_forward_args,
             attribute_to_layer_input=attribute_to_layer_input,
-            # pyre-fixme[6]: For 7th argument expected `Literal[]` but got `bool`.
             forward_hook_with_return=True,
             require_layer_grads=True,
         )

diff --git a/captum/_utils/progress.py b/captum/_utils/progress.py
@@ -5,9 +5,7 @@
 import sys
 import warnings
 from time import time
-from typing import Any, cast, Iterable, Optional, Sized, TextIO
-
-from captum._utils.typing import Literal
+from typing import Any, cast, Iterable, Literal, Optional, Sized, TextIO
 
 try:
     from tqdm.auto import tqdm
@@ -75,10 +73,7 @@ def __enter__(self) -> "NullProgress":
         return self
 
     # pyre-fixme[2]: Parameter must be annotated.
-    # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     def __exit__(self, exc_type, exc_value, exc_traceback) -> Literal[False]:
-        # pyre-fixme[7]: Expected `Literal[]` but got `bool`.
         return False
 
     # pyre-fixme[3]: Return type must be annotated.
@@ -139,11 +134,8 @@ def __enter__(self) -> "SimpleProgress":
         return self
 
     # pyre-fixme[2]: Parameter must be annotated.
-    # pyre-fixme[31]: Expression `Literal[False]` is not a valid type.
-    # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
     def __exit__(self, exc_type, exc_value, exc_traceback) -> Literal[False]:
         self.close()
-        # pyre-fixme[7]: Expected `Literal[]` but got `bool`.
         return False
 
     # pyre-fixme[3]: Return type must be annotated.

diff --git a/captum/attr/_core/layer/layer_conductance.py b/captum/attr/_core/layer/layer_conductance.py
@@ -2,7 +2,7 @@
 
 # pyre-strict
 import typing
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Literal, Optional, Tuple, Union
 
 import torch
 from captum._utils.common import (
@@ -12,7 +12,7 @@
     _format_output,
 )
 from captum._utils.gradient import compute_layer_gradients_and_eval
-from captum._utils.typing import BaselineType, Literal, TargetType
+from captum._utils.typing import BaselineType, TargetType
 from captum.attr._utils.approximation_methods import approximation_parameters
 from captum.attr._utils.attribution import GradientAttribution, LayerAttribution
 from captum.attr._utils.batching import _batch_attribution
@@ -86,8 +86,6 @@ def attribute(
         method: str = "gausslegendre",
         internal_batch_size: Union[None, int] = None,
         *,
-        # 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[True],
         attribute_to_layer_input: bool = False,
         grad_kwargs: Optional[Dict[str, Any]] = None,
@@ -105,9 +103,6 @@ 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[24]: Non-generic type `typing.Literal` cannot take parameters.
         return_convergence_delta: Literal[False] = False,
         attribute_to_layer_input: bool = False,
         grad_kwargs: Optional[Dict[str, Any]] = None,

diff --git a/captum/attr/_core/layer/layer_deep_lift.py b/captum/attr/_core/layer/layer_deep_lift.py
@@ -2,7 +2,7 @@
 
 # pyre-strict
 import typing
-from typing import Any, Callable, cast, Dict, Optional, Sequence, Tuple, Union
+from typing import Any, Callable, cast, Dict, Literal, Optional, Sequence, Tuple, Union
 
 import torch
 from captum._utils.common import (
@@ -13,12 +13,7 @@
     ExpansionTypes,
 )
 from captum._utils.gradient import compute_layer_gradients_and_eval
-from captum._utils.typing import (
-    BaselineType,
-    Literal,
-    TargetType,
-    TensorOrTupleOfTensorsGeneric,
-)
+from captum._utils.typing import BaselineType, TargetType, TensorOrTupleOfTensorsGeneric
 from captum.attr._core.deep_lift import DeepLift, DeepLiftShap
 from captum.attr._utils.attribution import LayerAttribution
 from captum.attr._utils.common import (
@@ -101,8 +96,6 @@ 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 `117`.
     def attribute(
         self,
         inputs: Union[Tensor, Tuple[Tensor, ...]],
@@ -111,27 +104,20 @@ def attribute(
         # 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[24]: Non-generic type `typing.Literal` cannot take parameters.
         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,
     ) -> 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 `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[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[False] = False,
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
@@ -382,8 +368,6 @@ def chunk_output_fn(out: TensorOrTupleOfTensorsGeneric) -> Sequence:
             inputs,
             additional_forward_args,
             target,
-            # pyre-fixme[31]: Expression `Literal[False])]` is not a valid type.
-            # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take parameters.
             cast(Union[Literal[True], Literal[False]], len(attributions) > 1),
         )
 
@@ -464,8 +448,6 @@ def attribute(
         # 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[24]: Non-generic type `typing.Literal` cannot take parameters.
         return_convergence_delta: Literal[True],
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
@@ -483,9 +465,6 @@ 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[24]: Non-generic type `typing.Literal` cannot take parameters.
         return_convergence_delta: Literal[False] = False,
         attribute_to_layer_input: bool = False,
         custom_attribution_func: Union[None, Callable[..., Tuple[Tensor, ...]]] = None,
@@ -686,10 +665,6 @@ def attribute(
             target=exp_target,
             additional_forward_args=exp_addit_args,
             return_convergence_delta=cast(
-                # pyre-fixme[31]: Expression `Literal[(True, False)]` is not a valid
-                #  type.
-                # pyre-fixme[24]: Non-generic type `typing.Literal` cannot take
-                #  parameters.
                 Literal[True, False],
                 return_convergence_delta,
             ),