Fix return style formatting

captum/attr/_core/deep_lift.py

@@ -288,7 +288,7 @@ def attribute(  # type: ignore
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                 Attribution score computed based on DeepLift rescale rule with respect
                 to each input feature. Attributions will always be
                 the same size as the provided inputs, with each value
@@ -791,7 +791,7 @@ def attribute(  # type: ignore
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution score computed based on DeepLift rescale rule with
                         respect to each input feature. Attributions will always be
                         the same size as the provided inputs, with each value

captum/attr/_core/feature_ablation.py

@@ -194,8 +194,8 @@ def attribute(
                         Default: None
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The attributions with respect to each input feature.
                         If the forward function returns
                         a scalar value per example, attributions will be

captum/attr/_core/feature_permutation.py

@@ -204,8 +204,8 @@ def attribute(  # type: ignore
                             Default: None
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The attributions with respect to each input feature.
                         If the forward function returns
                         a scalar value per example, attributions will be

captum/attr/_core/gradient_shap.py

@@ -215,7 +215,7 @@ def attribute(
                         Default: False
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution score computed based on GradientSHAP with respect
                         to each input feature. Attributions will always be
                         the same size as the provided inputs, with each value

captum/attr/_core/guided_backprop_deconvnet.py

@@ -186,8 +186,8 @@ def attribute(
                         Default: None
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The guided backprop gradients with respect to each
                         input feature. Attributions will always
                         be the same size as the provided inputs, with each value
@@ -297,8 +297,8 @@ def attribute(
                         Default: None
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The deconvolution attributions with respect to each
                         input feature. Attributions will always
                         be the same size as the provided inputs, with each value

captum/attr/_core/input_x_gradient.py

@@ -84,8 +84,8 @@ def attribute(
                         Default: None
 
         Returns:
-                *tensor* or tuple of *tensors* of **attributions**:
-                - **attributions** (*tensor* or tuple of *tensors*):
+                *tensor* or *tuple* of *tensors* of **attributions**:
+                - **attributions** (*tensor* or *tuple* of *tensors*):
                             The input x gradient with
                             respect to each input feature. Attributions will always be
                             the same size as the provided inputs, with each value

captum/attr/_core/integrated_gradients.py

@@ -233,7 +233,7 @@ def attribute(  # type: ignore
                     Default: False
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                     Integrated gradients with respect to each input feature.
                     attributions will always be the same size as the provided
                     inputs, with each value providing the attribution of the

captum/attr/_core/kernel_shap.py

@@ -220,8 +220,8 @@ def attribute(  # type: ignore
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The attributions with respect to each input feature.
                         If return_input_shape = True, attributions will be
                         the same size as the provided inputs, with each value

captum/attr/_core/layer/grad_cam.py

@@ -151,8 +151,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attributions based on GradCAM method.
                         Attributions will be the same size as the
                         output of the given layer, except for dimension 2,

captum/attr/_core/layer/internal_influence.py

@@ -187,8 +187,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-              - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+              - **attributions** (*tensor* or *tuple* of *tensors*):
                         Internal influence of each neuron in given
                         layer output. Attributions will always be the same size
                         as the output or input of the given layer depending on

captum/attr/_core/layer/layer_activation.py

@@ -87,8 +87,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* or list of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors* or *list*):
+            *tensor* or *tuple* of *tensors* or *list* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors* or *list*):
                         Activation of each neuron in given layer output.
                         Attributions will always be the same size as the
                         output of the given layer.

captum/attr/_core/layer/layer_conductance.py

@@ -235,7 +235,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Conductance of each neuron in given layer input or
                         output. Attributions will always be the same size as
                         the input or output of the given layer, depending on

captum/attr/_core/layer/layer_deep_lift.py

@@ -256,7 +256,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                 Attribution score computed based on DeepLift's rescale rule with
                 respect to layer's inputs or outputs. Attributions will always be the
                 same size as the provided layer's inputs or outputs, depending on
@@ -587,7 +587,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution score computed based on DeepLift's rescale rule
                         with respect to layer's inputs or outputs. Attributions
                         will always be the same size as the provided layer's inputs

captum/attr/_core/layer/layer_feature_ablation.py

@@ -171,8 +171,8 @@ def attribute(
                         Default: 1
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution of each neuron in given layer input or
                         output. Attributions will always be the same size as
                         the input or output of the given layer, depending on

captum/attr/_core/layer/layer_gradient_shap.py

@@ -246,7 +246,7 @@ def attribute(
                         Default: False
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution score computed based on GradientSHAP with
                         respect to layer's input or output. Attributions will always
                         be the same size as the provided layer's inputs or outputs,

captum/attr/_core/layer/layer_gradient_x_activation.py

@@ -134,8 +134,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* or list of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors* or *list*):
+            *tensor* or *tuple* of *tensors* or *list* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors* or *list*):
                         Product of gradient and activation for each
                         neuron in given layer output.
                         Attributions will always be the same size as the

captum/attr/_core/layer/layer_lrp.py

@@ -175,10 +175,10 @@ def attribute(
                     Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions** or 2-element tuple of
-            **attributions**, **delta** or list of **attributions** and **delta**:
+            *tensor* or *tuple* of *tensors* of **attributions** or 2-element tuple of
+            **attributions**, **delta** or *list* of **attributions** and **delta**:
 
-              - **attributions** (*tensor* or tuple of *tensors*):
+              - **attributions** (*tensor* or *tuple* of *tensors*):
                         The propagated relevance values with respect to each
                         input feature. Attributions will always
                         be the same size as the provided inputs, with each value

captum/attr/_core/lime.py

@@ -1013,8 +1013,8 @@ def attribute(  # type: ignore
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The attributions with respect to each input feature.
                         If return_input_shape = True, attributions will be
                         the same size as the provided inputs, with each value

captum/attr/_core/lrp.py

@@ -155,10 +155,10 @@ def attribute(
                     of rules is printed during propagation.
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**
+            *tensor* or *tuple* of *tensors* of **attributions**
             or 2-element tuple of **attributions**, **delta**:
 
-              - **attributions** (*tensor* or tuple of *tensors*):
+              - **attributions** (*tensor* or *tuple* of *tensors*):
                         The propagated relevance values with respect to each
                         input feature. The values are normalized by the output score
                         value (sum(relevance)=1). To obtain values comparable to other

captum/attr/_core/neuron/neuron_conductance.py

@@ -244,8 +244,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Conductance for
                         particular neuron with respect to each input feature.
                         Attributions will always be the same size as the provided

captum/attr/_core/neuron/neuron_deep_lift.py

@@ -207,7 +207,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                 Computes attributions using Deeplift's rescale rule for
                 particular neuron with respect to each input feature.
                 Attributions will always be the same size as the provided
@@ -445,7 +445,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Computes attributions using Deeplift's rescale rule for
                         particular neuron with respect to each input feature.
                         Attributions will always be the same size as the provided

captum/attr/_core/neuron/neuron_feature_ablation.py

@@ -189,8 +189,8 @@ def attribute(
                         Default: 1
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attributions of particular neuron with respect to each input
                         feature. Attributions will always be the same size as the
                         provided inputs, with each value providing the attribution

captum/attr/_core/neuron/neuron_gradient.py

@@ -130,8 +130,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Gradients of particular neuron with respect to each input
                         feature. Attributions will always be the same size as the
                         provided inputs, with each value providing the attribution

captum/attr/_core/neuron/neuron_gradient_shap.py

@@ -209,7 +209,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution score computed based on GradientSHAP with respect
                         to each input feature. Attributions will always be
                         the same size as the provided inputs, with each value

captum/attr/_core/neuron/neuron_guided_backprop_deconvnet.py

@@ -134,8 +134,8 @@ def attribute(
                         Support for multiple tensors will be added later.
                         Default: False
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Deconvolution attribution of
                         particular neuron with respect to each input feature.
                         Attributions will always be the same size as the provided
@@ -303,8 +303,8 @@ def attribute(
                         Support for multiple tensors will be added later.
                         Default: False
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Guided backprop attribution of
                         particular neuron with respect to each input feature.
                         Attributions will always be the same size as the provided

captum/attr/_core/neuron/neuron_integrated_gradients.py

@@ -202,8 +202,8 @@ def attribute(
                         Default: False
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Integrated gradients for particular neuron with
                         respect to each input feature.
                         Attributions will always be the same size as the provided

captum/attr/_core/noise_tunnel.py

@@ -139,7 +139,7 @@ def attribute(
 
         Returns:
             **attributions** or 2-element tuple of **attributions**, **delta**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         Attribution with
                         respect to each input feature. attributions will always be
                         the same size as the provided inputs, with each value

captum/attr/_core/occlusion.py

@@ -187,8 +187,8 @@ def attribute(  # type: ignore
                             Default: False
 
         Returns:
-                *tensor* or tuple of *tensors* of **attributions**:
-                - **attributions** (*tensor* or tuple of *tensors*):
+                *tensor* or *tuple* of *tensors* of **attributions**:
+                - **attributions** (*tensor* or *tuple* of *tensors*):
                             The attributions with respect to each input feature.
                             Attributions will always be
                             the same size as the provided inputs, with each value

captum/attr/_core/saliency.py

@@ -95,8 +95,8 @@ def attribute(
                         Default: None
 
         Returns:
-            *tensor* or tuple of *tensors* of **attributions**:
-            - **attributions** (*tensor* or tuple of *tensors*):
+            *tensor* or *tuple* of *tensors* of **attributions**:
+            - **attributions** (*tensor* or *tuple* of *tensors*):
                         The gradients with respect to each input feature.
                         Attributions will always be
                         the same size as the provided inputs, with each value