Merge branch 'master' into patch-1

Author: jjuncho

.conda/meta.yaml

@@ -14,19 +14,28 @@ build:
 requirements:
   host:
     - python>=3.9
+    - setuptools
   run:
     - numpy<2.0
     - pytorch>=1.10
     - matplotlib-base
+    - tqdm
+    - packaging
 
 test:
   imports:
     - captum
 
 about:
   home: https://captum.ai
-  license: BSD
+  license: BSD-3
   license_file: LICENSE
   summary: Model interpretability for PyTorch
+  description: |
+    Captum is a model interpretability and understanding library for PyTorch.
+    Captum means comprehension in Latin and contains general purpose implementations
+    of integrated gradients, saliency maps, smoothgrad, vargrad and others for
+    PyTorch models. It has quick integration for models built with domain-specific
+    libraries such as torchvision, torchtext, and others.
   doc_url: https://captum.ai
   dev_url: https://github.com/pytorch/captum

README.md

@@ -25,8 +25,6 @@ of integrated gradients, saliency maps, smoothgrad, vargrad and others for
 PyTorch models. It has quick integration for models built with domain-specific
 libraries such as torchvision, torchtext, and others.
 
-*Captum is currently in beta and under active development!*
-
 
 #### About Captum
 
@@ -92,6 +90,7 @@ pip install -e .
 To customize the installation, you can also run the following variants of the
 above:
 * `pip install -e .[insights]`: Also installs all packages necessary for running Captum Insights.
+**NOTE**: Captum Insights is being deprecated. See further details [below](#captum-insights).
 * `pip install -e .[dev]`: Also installs all tools necessary for development
   (testing, linting, docs building; see [Contributing](#contributing) below).
 * `pip install -e .[tutorials]`: Also installs all packages necessary for running the tutorial notebooks.
@@ -388,6 +387,10 @@ Captum on different types of models can be found in our tutorials.
 
 ## Captum Insights
 
+**NOTE**: *Support for Captum Insights is being deprecated in an upcoming release.
+While the code will still be available, there will no longer be active
+development or support for it.*
+
 Captum provides a web interface called Insights for easy visualization and
 access to a number of our interpretability algorithms.
 

captum/__init__.py

@@ -9,6 +9,6 @@
 import captum.robust as robust
 
 
-__version__ = "0.7.0"
+__version__ = "0.8.0"
 
 __all__ = ["attr", "concept", "influence", "log", "metrics", "robust"]

captum/_utils/common.py

@@ -232,12 +232,12 @@ def _format_tensor_into_tuples(inputs: None) -> None: ...
 
 @overload
 def _format_tensor_into_tuples(
-    inputs: Union[Tensor, Tuple[Tensor, ...]]
+    inputs: Union[Tensor, Tuple[Tensor, ...]],
 ) -> Tuple[Tensor, ...]: ...
 
 
 def _format_tensor_into_tuples(
-    inputs: Union[None, Tensor, Tuple[Tensor, ...]]
+    inputs: Union[None, Tensor, Tuple[Tensor, ...]],
 ) -> Union[None, Tuple[Tensor, ...]]:
     if inputs is None:
         return None
@@ -261,7 +261,7 @@ def _format_inputs(inputs: Any, unpack_inputs: bool = True) -> Any:
 
 
 def _format_float_or_tensor_into_tuples(
-    inputs: Union[float, Tensor, Tuple[Union[float, Tensor], ...]]
+    inputs: Union[float, Tensor, Tuple[Union[float, Tensor], ...]],
 ) -> Tuple[Union[float, Tensor], ...]:
     if not isinstance(inputs, tuple):
         assert isinstance(
@@ -276,7 +276,7 @@ def _format_float_or_tensor_into_tuples(
 @overload
 def _format_additional_forward_args(
     # pyre-fixme[24]: Generic type `tuple` expects at least 1 type parameter.
-    additional_forward_args: Union[Tensor, Tuple]
+    additional_forward_args: Union[Tensor, Tuple],
     # pyre-fixme[24]: Generic type `tuple` expects at least 1 type parameter.
 ) -> Tuple: ...
 

captum/_utils/typing.py

@@ -24,6 +24,7 @@
 TupleOrTensorOrBoolGeneric = TypeVar(
     "TupleOrTensorOrBoolGeneric", Tuple[Tensor, ...], Tensor, bool
 )
+PassThroughOutputType = TypeVar("PassThroughOutputType")
 ModuleOrModuleList = TypeVar("ModuleOrModuleList", Module, List[Module])
 TargetType = Union[None, int, Tuple[int, ...], Tensor, List[Tuple[int, ...]], List[int]]
 BaselineTupleType = Union[None, Tuple[Union[Tensor, int, float], ...]]

captum/attr/_core/dataloader_attr.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python3
 
 # pyre-strict
+
 from collections import defaultdict
 from copy import copy
 from typing import Callable, cast, Dict, Iterable, List, Optional, Tuple, Union
@@ -30,7 +31,6 @@ class InputRole:
 
 
 # default reducer wehn reduce is None. Simply concat the outputs by the batch dimension
-# pyre-fixme[2]: Parameter must be annotated.
 def _concat_tensors(accum: Optional[Tensor], cur_output: Tensor, _) -> Tensor:
     return cur_output if accum is None else torch.cat([accum, cur_output])
 
@@ -87,9 +87,7 @@ def _perturb_inputs(
         else:
             baseline = baselines[attr_inp_count]
 
-            # pyre-fixme[58]: `*` is not supported for operand types `object` and
-            #  `Tensor`.
-            perturbed_inp = inp * pert_mask + baseline * (1 - pert_mask)
+            perturbed_inp = cast(Tensor, inp) * pert_mask + baseline * (1 - pert_mask)
             perturbed_inputs.append(perturbed_inp)
 
         attr_inp_count += 1