Add __call__ to TokenizerLike (#1418)

Summary:

Add __call__ to TokenizerLike for transformers compatibility

Differential Revision: D64998805

Author: craymichael

captum/_utils/common.py

@@ -90,8 +90,8 @@ def _is_tuple(inputs: Tensor) -> Literal[False]: ...
 
 @typing.overload
 def _is_tuple(
-    inputs: TensorOrTupleOfTensorsGeneric,
-) -> bool: ...  # type: ignore
+    inputs: TensorOrTupleOfTensorsGeneric,  # type: ignore
+) -> bool: ...
 
 
 def _is_tuple(inputs: Union[Tensor, Tuple[Tensor, ...]]) -> bool:

captum/_utils/typing.py

@@ -2,7 +2,18 @@
 
 # pyre-strict
 
-from typing import List, Literal, Optional, overload, Protocol, Tuple, TypeVar, Union
+from collections import UserDict
+from typing import (
+    List,
+    Literal,
+    Optional,
+    overload,
+    Protocol,
+    Tuple,
+    TYPE_CHECKING,
+    TypeVar,
+    Union,
+)
 
 from torch import Tensor
 from torch.nn import Module
@@ -30,6 +41,13 @@
 ]
 
 
+# Necessary for Python >=3.7 and <3.9!
+if TYPE_CHECKING:
+    BatchEncodingType = UserDict[Union[int, str], object]
+else:
+    BatchEncodingType = UserDict
+
+
 class TokenizerLike(Protocol):
     """A protocol for tokenizer-like objects that can be used with Captum
     LLM attribution methods."""
@@ -62,3 +80,9 @@ def convert_tokens_to_ids(self, tokens: List[str]) -> List[int]: ...
     def convert_tokens_to_ids(
         self, tokens: Union[List[str], str]
     ) -> Union[List[int], int]: ...
+
+    def __call__(
+        self,
+        text: Optional[Union[str, List[str], List[List[str]]]] = None,
+        return_offsets_mapping: bool = False,
+    ) -> BatchEncodingType: ...

tests/attr/test_interpretable_input.py

@@ -5,6 +5,7 @@
 from typing import List, Literal, Optional, overload, Union
 
 import torch
+from captum._utils.typing import BatchEncodingType
 from captum.attr._utils.interpretable_input import TextTemplateInput, TextTokenInput
 from parameterized import parameterized
 from tests.helpers import BaseTest
@@ -68,6 +69,13 @@ def convert_tokens_to_ids(
     def decode(self, token_ids: Tensor) -> str:
         raise NotImplementedError
 
+    def __call__(
+        self,
+        text: Optional[Union[str, List[str], List[List[str]]]] = None,
+        return_offsets_mapping: bool = False,
+    ) -> BatchEncodingType:
+        raise NotImplementedError
+
 
 class TestTextTemplateInput(BaseTest):
     @parameterized.expand(

tests/attr/test_llm_attr.py

@@ -19,6 +19,7 @@
 
 import torch
 from captum._utils.models.linear_model import SkLearnLasso
+from captum._utils.typing import BatchEncodingType
 from captum.attr._core.feature_ablation import FeatureAblation
 from captum.attr._core.kernel_shap import KernelShap
 from captum.attr._core.layer.layer_gradient_shap import LayerGradientShap
@@ -96,6 +97,13 @@ def decode(self, token_ids: Tensor) -> str:
         # pyre-fixme[7]: Expected `str` but got `Union[List[str], str]`.
         return tokens if isinstance(tokens, str) else " ".join(tokens)
 
+    def __call__(
+        self,
+        text: Optional[Union[str, List[str], List[List[str]]]] = None,
+        return_offsets_mapping: bool = False,
+    ) -> BatchEncodingType:
+        raise NotImplementedError
+
 
 class Result(NamedTuple):
     logits: Tensor