Adding isort (#310)

Summary:
This applies isort to alphabetize import ordering. We also add an isort check to CircleCI to ensure that import ordering is maintained in future PRs. This required adding an isort config that is compatible with black, which was found here: https://github.com/psf/black

This also adds a type: ignore for an issue caused by merging Insights type fixes with type hints for common.
Pull Request resolved: #310

Reviewed By: orionr

Differential Revision: D20206324

Pulled By: vivekmig

fbshipit-source-id: 48cce82d60a9a6f7384211e7aae2ffb4c0c85772

Author: vivekmig

.circleci/config.yml

@@ -38,6 +38,13 @@ commands:
           name: "Lint with black"
           command: black --check --diff .
 
+  isort:
+    description: "Check import order with isort"
+    steps:
+      - run:
+          name: "Check import order with isort"
+          command: isort --check-only
+
   mypy_check:
     description: "Static type checking with mypy"
     steps:
@@ -132,6 +139,7 @@ jobs:
           args: "-n -f"
       - lint_flake8
       - lint_black
+      - isort
       - mypy_check
       - unit_tests
       - sphinx
@@ -145,6 +153,7 @@ jobs:
           args: "-f"
       - lint_flake8
       - lint_black
+      - isort
       - mypy_check
       - unit_tests
       - sphinx
@@ -176,6 +185,7 @@ jobs:
           args: "-n"
       - lint_flake8
       - lint_black
+      - isort
       - mypy_check
       - unit_tests
       - sphinx
@@ -200,6 +210,7 @@ jobs:
           args: "-n -f -d"
       - lint_flake8
       - lint_black
+      - isort
       - unit_tests
       - sphinx
       - configure_github_bot

.isort.cfg

@@ -0,0 +1,7 @@
+[settings]
+multi_line_output=3
+include_trailing_comma=True
+force_grid_wrap=0
+use_parentheses=True
+line_length=88
+known_third_party=pytext,torchvision,bs4

CONTRIBUTING.md

@@ -35,7 +35,7 @@ pip using `pip install isort`, and run locally by calling
 ```bash
 isort
 ```
-from the repository root. No additional configuration should be needed.
+from the repository root. Configuration for isort is located in .isort.cfg.
 
 We feel strongly that having a consistent code style is extremely important, so
 CircleCI will fail on your PR if it does not adhere to the black or flake8 formatting style or isort import ordering.

captum/attr/__init__.py

@@ -1,51 +1,52 @@
 #!/usr/bin/env python3
 
-from ._core.integrated_gradients import IntegratedGradients  # noqa
 from ._core.deep_lift import DeepLift, DeepLiftShap  # noqa
-from ._core.input_x_gradient import InputXGradient  # noqa
-from ._core.saliency import Saliency  # noqa
-from ._core.noise_tunnel import NoiseTunnel  # noqa
-from ._core.gradient_shap import GradientShap  # noqa
-from ._core.guided_backprop_deconvnet import GuidedBackprop, Deconvolution  # noqa
-from ._core.guided_grad_cam import GuidedGradCam  # noqa
 from ._core.feature_ablation import FeatureAblation  # noqa
 from ._core.feature_permutation import FeaturePermutation  # noqa
-from ._core.occlusion import Occlusion  # noqa
-from ._core.shapley_value import ShapleyValueSampling, ShapleyValues  # noqa
-from ._core.layer.layer_conductance import LayerConductance  # noqa
-from ._core.layer.layer_gradient_x_activation import LayerGradientXActivation  # noqa
-from ._core.layer.layer_activation import LayerActivation  # noqa
-from ._core.layer.internal_influence import InternalInfluence  # noqa
+from ._core.gradient_shap import GradientShap  # noqa
+from ._core.guided_backprop_deconvnet import Deconvolution  # noqa
+from ._core.guided_backprop_deconvnet import GuidedBackprop
+from ._core.guided_grad_cam import GuidedGradCam  # noqa
+from ._core.input_x_gradient import InputXGradient  # noqa
+from ._core.integrated_gradients import IntegratedGradients  # noqa
 from ._core.layer.grad_cam import LayerGradCam  # noqa
-from ._core.layer.layer_deep_lift import LayerDeepLift, LayerDeepLiftShap  # noqa
+from ._core.layer.internal_influence import InternalInfluence  # noqa
+from ._core.layer.layer_activation import LayerActivation  # noqa
+from ._core.layer.layer_conductance import LayerConductance  # noqa
+from ._core.layer.layer_deep_lift import LayerDeepLift  # noqa
+from ._core.layer.layer_deep_lift import LayerDeepLiftShap
 from ._core.layer.layer_gradient_shap import LayerGradientShap  # noqa
+from ._core.layer.layer_gradient_x_activation import LayerGradientXActivation  # noqa
 from ._core.layer.layer_integrated_gradients import LayerIntegratedGradients  # noqa
-from ._core.neuron.neuron_feature_ablation import NeuronFeatureAblation  # noqa
 from ._core.neuron.neuron_conductance import NeuronConductance  # noqa
+from ._core.neuron.neuron_deep_lift import NeuronDeepLift  # noqa
+from ._core.neuron.neuron_deep_lift import NeuronDeepLiftShap
+from ._core.neuron.neuron_feature_ablation import NeuronFeatureAblation  # noqa
 from ._core.neuron.neuron_gradient import NeuronGradient  # noqa
-from ._core.neuron.neuron_integrated_gradients import NeuronIntegratedGradients  # noqa
-from ._core.neuron.neuron_deep_lift import NeuronDeepLift, NeuronDeepLiftShap  # noqa
 from ._core.neuron.neuron_gradient_shap import NeuronGradientShap  # noqa
-from ._core.neuron.neuron_guided_backprop_deconvnet import (
+from ._core.neuron.neuron_guided_backprop_deconvnet import (  # noqa
     NeuronDeconvolution,
     NeuronGuidedBackprop,
-)  # noqa
-
+)
+from ._core.neuron.neuron_integrated_gradients import NeuronIntegratedGradients  # noqa
+from ._core.noise_tunnel import NoiseTunnel  # noqa
+from ._core.occlusion import Occlusion  # noqa
+from ._core.saliency import Saliency  # noqa
+from ._core.shapley_value import ShapleyValues, ShapleyValueSampling  # noqa
+from ._models.base import InterpretableEmbeddingBase  # noqa
 from ._models.base import (
-    InterpretableEmbeddingBase,
     TokenReferenceBase,
     configure_interpretable_embedding_layer,
     remove_interpretable_embedding_layer,
-)  # noqa
+)
+from ._utils import visualization  # noqa
 from ._utils.attribution import Attribution  # noqa
 from ._utils.attribution import GradientAttribution  # noqa
-from ._utils.attribution import PerturbationAttribution  # noqa
 from ._utils.attribution import LayerAttribution  # noqa
 from ._utils.attribution import NeuronAttribution  # noqa
-from ._utils import visualization  # noqa
-from ._utils.summarizer import Summarizer, CommonSummarizer
-from ._utils.stat import Mean, StdDev, MSE, Var, Min, Max, Sum, Count
-
+from ._utils.attribution import PerturbationAttribution  # noqa
+from ._utils.stat import MSE, Count, Max, Mean, Min, StdDev, Sum, Var
+from ._utils.summarizer import CommonSummarizer, Summarizer
 
 __all__ = [
     "Attribution",

captum/attr/_core/deep_lift.py

@@ -1,41 +1,40 @@
 #!/usr/bin/env python3
 import typing
-from typing import Tuple, Union, Any, List, Callable, cast
-
 import warnings
+from typing import Any, Callable, List, Tuple, Union, cast
+
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 from torch import Tensor
 from torch.nn import Module
 from torch.utils.hooks import RemovableHandle
 
-import numpy as np
-
+from .._utils.attribution import GradientAttribution
 from .._utils.common import (
-    _is_tuple,
-    _format_input,
+    ExpansionTypes,
+    _call_custom_attribution_func,
+    _compute_conv_delta_and_format_attrs,
+    _expand_additional_forward_args,
+    _expand_target,
+    _format_additional_forward_args,
+    _format_attributions,
     _format_baseline,
     _format_callable_baseline,
-    _format_attributions,
+    _format_input,
     _format_tensor_into_tuples,
-    _format_additional_forward_args,
+    _is_tuple,
     _run_forward,
-    _validate_input,
-    _expand_target,
-    _expand_additional_forward_args,
     _tensorize_baseline,
-    _call_custom_attribution_func,
-    _compute_conv_delta_and_format_attrs,
-    ExpansionTypes,
+    _validate_input,
 )
-from .._utils.attribution import GradientAttribution
 from .._utils.gradient import apply_gradient_requirements, undo_gradient_requirements
 from .._utils.typing import (
-    TensorOrTupleOfTensorsGeneric,
+    BaselineType,
     Literal,
     TargetType,
-    BaselineType,
+    TensorOrTupleOfTensorsGeneric,
 )
 
 

captum/attr/_core/feature_ablation.py

@@ -1,24 +1,23 @@
 #!/usr/bin/env python3
 
-import torch
+from typing import Any, Callable, Tuple, Union, cast
 
+import torch
 from torch import Tensor, dtype
 
-from typing import Any, Callable, Tuple, Union, cast
-
+from .._utils.attribution import PerturbationAttribution
 from .._utils.common import (
+    _expand_additional_forward_args,
+    _expand_target,
     _find_output_mode_and_verify,
+    _format_additional_forward_args,
     _format_attributions,
     _format_input,
     _format_input_baseline,
     _is_tuple,
     _run_forward,
-    _expand_additional_forward_args,
-    _expand_target,
-    _format_additional_forward_args,
 )
-from .._utils.attribution import PerturbationAttribution
-from .._utils.typing import TensorOrTupleOfTensorsGeneric, TargetType, BaselineType
+from .._utils.typing import BaselineType, TargetType, TensorOrTupleOfTensorsGeneric
 
 
 class FeatureAblation(PerturbationAttribution):

captum/attr/_core/feature_permutation.py

@@ -4,8 +4,8 @@
 import torch
 from torch import Tensor
 
-from .feature_ablation import FeatureAblation
 from .._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric
+from .feature_ablation import FeatureAblation
 
 
 def _permute_feature(x: Tensor, feature_mask: Tensor) -> Tensor:

captum/attr/_core/gradient_shap.py

@@ -1,26 +1,25 @@
 #!/usr/bin/env python3
-import torch
+import typing
+from typing import Any, Callable, Tuple, Union
 
 import numpy as np
+import torch
 
 from .._utils.attribution import GradientAttribution
 from .._utils.common import (
-    _is_tuple,
-    _format_input_baseline,
-    _format_callable_baseline,
     _compute_conv_delta_and_format_attrs,
+    _format_callable_baseline,
+    _format_input_baseline,
+    _is_tuple,
 )
-
-from .noise_tunnel import NoiseTunnel
-from typing import Any, Callable, Tuple, Union
 from .._utils.typing import (
-    Tensor,
-    TensorOrTupleOfTensorsGeneric,
+    BaselineType,
     Literal,
     TargetType,
-    BaselineType,
+    Tensor,
+    TensorOrTupleOfTensorsGeneric,
 )
-import typing
+from .noise_tunnel import NoiseTunnel
 
 
 class GradientShap(GradientAttribution):

captum/attr/_core/guided_backprop_deconvnet.py

@@ -1,15 +1,15 @@
 #!/usr/bin/env python3
 import warnings
+from typing import Any, List, Tuple, Union
+
 import torch
 import torch.nn.functional as F
-from typing import Any, List, Union, Tuple
-
 from torch import Tensor
 from torch.nn import Module
 from torch.utils.hooks import RemovableHandle
 
 from .._utils.attribution import GradientAttribution
-from .._utils.common import _format_input, _format_attributions, _is_tuple
+from .._utils.common import _format_attributions, _format_input, _is_tuple
 from .._utils.gradient import apply_gradient_requirements, undo_gradient_requirements
 from .._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric
 

captum/attr/_core/guided_grad_cam.py

@@ -1,17 +1,16 @@
 #!/usr/bin/env python3
-import torch
 import warnings
+from typing import Any, List, Union
 
-from .._utils.attribution import GradientAttribution, LayerAttribution
-from .._utils.common import _format_input, _format_attributions, _is_tuple
-
-from .layer.grad_cam import LayerGradCam
-from .guided_backprop_deconvnet import GuidedBackprop
-
-from torch.nn import Module
+import torch
 from torch import Tensor
-from typing import Any, List, Union
+from torch.nn import Module
+
+from .._utils.attribution import GradientAttribution, LayerAttribution
+from .._utils.common import _format_attributions, _format_input, _is_tuple
 from .._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric
+from .guided_backprop_deconvnet import GuidedBackprop
+from .layer.grad_cam import LayerGradCam
 
 
 class GuidedGradCam(GradientAttribution):