internlm/SWE-Fixer-Train-110K huggingface dataset:
Repository: nilearn/nilearn

Issue:
[DOC] plot_event() doc says incorrect column name requirement
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Describe your proposed suggestion in detail.

https://nilearn.github.io/stable/modules/generated/nilearn.plotting.plot_event.html#nilearn-plotting-plot-event

says "The [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html#pandas.DataFrame) must have three columns: event_type with event name" but it actually should be "trial_type" per the example here: https://nilearn.github.io/stable/auto_examples/04_glm_first_level/plot_write_events_file.html#sphx-glr-auto-examples-04-glm-first-level-plot-write-events-file-py and bids documentation (https://bids-specification.readthedocs.io/en/stable/04-modality-specific-files/05-task-events.html)

### List any pages that would be impacted.

_No response_


Discussion:

Resolving patch:
diff --git a/nilearn/plotting/matrix_plotting.py b/nilearn/plotting/matrix_plotting.py
--- a/nilearn/plotting/matrix_plotting.py
+++ b/nilearn/plotting/matrix_plotting.py
@@ -475,7 +475,7 @@ def plot_event(model_event, cmap=None, output_file=None, **fig_kwargs):
     model_event : :class:`pandas.DataFrame` or :obj:`list`\
     of :class:`pandas.DataFrame`
         The :class:`pandas.DataFrame` must have three columns:
-        ``event_type`` with event name, ``onset`` and ``duration``.
+        ``trial_type`` with event name, ``onset`` and ``duration``.
 
         .. note::
 


Test patch:
Repository: nilearn/nilearn

Issue:
[DOC] Sphinx reference target failure with scikit-learn 1.3.1
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Describe your proposed suggestion in detail.

Seeing the same issue as https://github.com/nilearn/nilearn/issues/3800 and that was handled in https://github.com/scikit-learn/scikit-learn/pull/26770

See failure: https://github.com/nilearn/nilearn/actions/runs/6259015400/job/16994196734?pr=3936

### List any pages that would be impacted.

_No response_


Discussion:

Resolving patch:
diff --git a/doc/conf.py b/doc/conf.py
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -407,11 +407,9 @@
 
 # Check intersphinx reference targets exist
 nitpicky = True
-# Temporary solution to nilearn/nilearn#3800
-# See also scikit-learn/scikit-learn#26761
+# Temporary solution to nilearn/nilearn#3997
 nitpick_ignore = [
-    ("py:class", "pipeline.Pipeline"),
-    ("py:class", "utils.metadata_routing.MetadataRequest"),
+    ("py:class", "sklearn.utils.metadata_routing.MetadataRequest"),
 ]
 
 binder_branch = "main" if "dev" in current_version else current_version


Test patch:
Repository: nilearn/nilearn

Issue:
[DOC] Formatting of docstring in regions.Parcellations
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Describe your proposed suggestion in detail.

Right now, the line break in the docstring for `nilearn.regions.Parcellations` is causing sub-optimal formatting.

Here's the rendered docstring
<img width="697" alt="Screenshot 2023-08-07 at 20 20 56" src="https://github.com/nilearn/nilearn/assets/15017191/8ac3cca4-5ccc-4235-a086-c4276527a7b4">

and the accompanying docstring:
https://github.com/nilearn/nilearn/blob/321494420f95c7a5e2172108400194b37a02e628/nilearn/regions/parcellations.py#L135-L136

As you can see, "hierarchical_kmeans" is not formatted in the same styling as the other valid methods.

### List any pages that would be impacted.

https://nilearn.github.io/stable/modules/generated/nilearn.regions.Parcellations.html#nilearn.regions.Parcellations


Discussion:
Thanks @emdupre for pointing that out! We'd need to add a backslash (`\`) at the end of type definitions with a line break to fix that. However, in this case, maybe the list of possible inputs should rather be moved to the description below it instead of next to ``:obj:`str` ``
I was thinking: as this is not mission critical we should probably keep it for someone who wants to do a first contribution, no?
Sure! it already has the good first issue label :) 
Has this issues been merged or is there an existing pull request? If not can I pick it up as a good first issue
@NIkhilgKrish 

it is all yours for the taking if you want it. 😃 

Resolving patch:
diff --git a/nilearn/regions/parcellations.py b/nilearn/regions/parcellations.py
--- a/nilearn/regions/parcellations.py
+++ b/nilearn/regions/parcellations.py
@@ -133,7 +133,7 @@ class Parcellations(_MultiPCA):
 
     Parameters
     ----------
-    method: :obj:`str`, {'kmeans', 'ward', 'complete', 'average', 'rena',
+    method : {'kmeans', 'ward', 'complete', 'average', 'rena', \
         'hierarchical_kmeans'}
         A method to choose between for brain parcellations.
         For a small number of parcels, kmeans is usually advisable.


Test patch:
Repository: nilearn/nilearn

Issue:
Refactor unclear code section
I find this logic confusing, maybe flag to refactor (in another PR)

_Originally posted by @ymzayek in https://github.com/nilearn/nilearn/pull/3810#discussion_r1253258959_


Discussion:

Resolving patch:
diff --git a/nilearn/plotting/find_cuts.py b/nilearn/plotting/find_cuts.py
--- a/nilearn/plotting/find_cuts.py
+++ b/nilearn/plotting/find_cuts.py
@@ -475,16 +475,16 @@ def find_parcellation_cut_coords(
         right_hemi[: int(x)] = 0
 
         # Two connected component in both hemispheres
-        if not np.all(left_hemi == False) or np.all(  # noqa: E712
-            right_hemi == False  # noqa: E712
-        ):
+        left_hemi_has_values = np.any(left_hemi)
+        right_hemi_all_zero = not np.any(right_hemi)
+        if left_hemi_has_values or right_hemi_all_zero:
             if label_hemisphere == "left":
                 cur_img = left_hemi.astype(int)
             elif label_hemisphere == "right":
                 cur_img = right_hemi.astype(int)
 
         # Take the largest connected component
-        labels, label_nb = label(cur_img)
+        labels, _ = label(cur_img)
         label_count = np.bincount(labels.ravel().astype(int))
         label_count[0] = 0
         component = labels == label_count.argmax()


Test patch:
diff --git a/nilearn/plotting/tests/test_find_cuts.py b/nilearn/plotting/tests/test_find_cuts.py
--- a/nilearn/plotting/tests/test_find_cuts.py
+++ b/nilearn/plotting/tests/test_find_cuts.py
@@ -335,6 +335,27 @@ def test_find_parcellation_cut_coords(affine_eye):
         find_parcellation_cut_coords(labels_img=img, label_hemisphere="lft")
 
 
+def test_find_parcellation_cut_coords_hemispheres(affine_mni):
+    # Create a mock labels_img object
+    data = np.zeros((10, 10, 10))
+    data[2:5, 2:5, 2:5] = 1  # left hemisphere
+    labels_img = nibabel.Nifti1Image(data, affine_mni)
+
+    # Test when label_hemisphere is "left"
+    coords, labels = find_parcellation_cut_coords(
+        labels_img, return_label_names=True, label_hemisphere="left"
+    )
+    assert len(coords) == 1
+    assert labels == [1]
+
+    # Test when label_hemisphere is "right"
+    coords, labels = find_parcellation_cut_coords(
+        labels_img, return_label_names=True, label_hemisphere="right"
+    )
+    assert len(coords) == 1
+    assert labels == [1]
+
+
 def test_find_probabilistic_atlas_cut_coords(affine_eye):
     # make data
     arr1 = np.zeros((100, 100, 100))
Repository: nilearn/nilearn

Issue:
Rename file to `_proximal_operators.py`
I think this file name can also start with an underscore, so `_proximal_operators.py`

_Originally posted by @ymzayek in https://github.com/nilearn/nilearn/pull/4086#discussion_r1384857423_
            


Discussion:

Resolving patch:
diff --git a/nilearn/decoding/proximal_operators.py b/nilearn/decoding/_proximal_operators.py
similarity index 100%
rename from nilearn/decoding/proximal_operators.py
rename to nilearn/decoding/_proximal_operators.py
diff --git a/nilearn/decoding/space_net_solvers.py b/nilearn/decoding/space_net_solvers.py
--- a/nilearn/decoding/space_net_solvers.py
+++ b/nilearn/decoding/space_net_solvers.py
@@ -24,13 +24,13 @@
     squared_loss,
     squared_loss_grad,
 )
-from .fista import mfista
-from .proximal_operators import (
+from ._proximal_operators import (
     prox_l1,
     prox_l1_with_intercept,
     prox_tvl1,
     prox_tvl1_with_intercept,
 )
+from .fista import mfista
 
 
 def _squared_loss_and_spatial_grad(X, y, w, mask, grad_weight):


Test patch:
diff --git a/nilearn/_utils/tests/test_common.py b/nilearn/_utils/tests/test_common.py
--- a/nilearn/_utils/tests/test_common.py
+++ b/nilearn/_utils/tests/test_common.py
@@ -34,7 +34,7 @@ def test_number_public_functions():
     If this is intentional, then the number should be updated in the test.
     Otherwise it means that the public API of nilearn has changed by mistake.
     """
-    assert len({_[0] for _ in all_functions()}) == 215
+    assert len({_[0] for _ in all_functions()}) == 211
 
 
 def test_number_public_classes():
diff --git a/nilearn/decoding/tests/test_fista.py b/nilearn/decoding/tests/test_fista.py
--- a/nilearn/decoding/tests/test_fista.py
+++ b/nilearn/decoding/tests/test_fista.py
@@ -8,8 +8,8 @@
     squared_loss,
     squared_loss_grad,
 )
+from nilearn.decoding._proximal_operators import prox_l1
 from nilearn.decoding.fista import _check_lipschitz_continuous, mfista
-from nilearn.decoding.proximal_operators import prox_l1
 
 
 @pytest.mark.parametrize("scaling", list(np.logspace(-3, 3, num=7)))
diff --git a/nilearn/decoding/tests/test_operators.py b/nilearn/decoding/tests/test_operators.py
--- a/nilearn/decoding/tests/test_operators.py
+++ b/nilearn/decoding/tests/test_operators.py
@@ -4,7 +4,7 @@
 import pytest
 from numpy.testing import assert_almost_equal
 
-from nilearn.decoding.proximal_operators import prox_l1, prox_tvl1
+from nilearn.decoding._proximal_operators import prox_l1, prox_tvl1
 
 
 def test_prox_l1_nonexpansiveness(rng, n_features=10):
Repository: nilearn/nilearn

Issue:
[BUG] `nilearn.plotting.plot_sur_stat_map` does not display the provided title
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Operating system

- [X] Linux
- [ ] Mac
- [ ] Windows

### Operating system version

For example one of the following:
- Linux Ubuntu 22.04
- Mac OS Version 12 "monterey"
- Windows 11


### Python version

- [ ] 3.12
- [X] 3.11
- [ ] 3.10
- [ ] 3.9
- [ ] 3.8

### nilearn version

Dev version

### Expected behavior

Image itle should be displayed on the image

### Current behavior & error messages

It is actually missing.

### Steps and code to reproduce bug

This is visible in the documentation
https://nilearn.github.io/stable/auto_examples/01_plotting/plot_3d_map_to_surface_projection.html#sphx-glr-auto-examples-01-plotting-plot-3d-map-to-surface-projection-py


Discussion:
Seems to be the case for all examples with `plot_surf_stat_map` and probably anything that calls `plot_surf` as I also saw it with `plot_surf_roi`. Locally running the notebook displays the title so maybe it has to do with the interplay of sphinx and mpl 

Resolving patch:
diff --git a/nilearn/plotting/surf_plotting.py b/nilearn/plotting/surf_plotting.py
--- a/nilearn/plotting/surf_plotting.py
+++ b/nilearn/plotting/surf_plotting.py
@@ -534,7 +534,7 @@ def _plot_surf_matplotlib(coords, faces, surf_map=None, bg_map=None,
     This function handles surface plotting when the selected
     engine is matplotlib.
     """
-    _default_figsize = [4, 4]
+    _default_figsize = [4, 5]
     limits = [coords.min(), coords.max()]
 
     # Get elevation and azimut from view


Test patch:
Repository: nilearn/nilearn

Issue:
Failure of carpet plot with matplotlib-3.9.0.dev0
See workflow: https://github.com/nilearn/nilearn/actions/runs/7985927180/job/21805307226#step:6:5388

Due to PR: https://github.com/matplotlib/matplotlib/pull/27565

Should be fixable as explained in here: https://stackoverflow.com/questions/77710768/getting-constrained-layout-to-work-with-nested-subplots-in-matplotlib
Failure of carpet plot with matplotlib-3.9.0.dev0
See workflow: https://github.com/nilearn/nilearn/actions/runs/7985927180/job/21805307226#step:6:5388

Due to PR: https://github.com/matplotlib/matplotlib/pull/27565

Should be fixable as explained in here: https://stackoverflow.com/questions/77710768/getting-constrained-layout-to-work-with-nested-subplots-in-matplotlib


Discussion:

Resolving patch:
diff --git a/examples/01_plotting/plot_carpet.py b/examples/01_plotting/plot_carpet.py
--- a/examples/01_plotting/plot_carpet.py
+++ b/examples/01_plotting/plot_carpet.py
@@ -45,6 +45,7 @@
     mask_img,
     t_r=t_r,
     standardize="zscore_sample",
+    title="global patterns over time",
 )
 
 display.show()
@@ -83,8 +84,9 @@
     axes=ax,
     cmap="gray",
     standardize="zscore_sample",
+    title="global patterns over time separated by tissue type",
 )
 
-fig.show()
+plt.show()
 
 # sphinx_gallery_dummy_images=1
diff --git a/nilearn/plotting/img_plotting.py b/nilearn/plotting/img_plotting.py
--- a/nilearn/plotting/img_plotting.py
+++ b/nilearn/plotting/img_plotting.py
@@ -1947,7 +1947,7 @@ def plot_carpet(
         gs = mgs.GridSpecFromSubplotSpec(
             1,
             2 + int(legend),
-            subplot_spec=axes,
+            subplot_spec=axes.get_subplotspec(),
             width_ratios=wratios[: 2 + int(legend)],
             wspace=0.0,
         )


Test patch:
Repository: nilearn/nilearn

Issue:
[BUG] NiftiMapsMaskers reports: cross hair does not match "maximum" of a given map
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Operating system

- [X] Linux
- [ ] Mac
- [ ] Windows

### Operating system version

For example one of the following:
- Linux Ubuntu 22.04



### Python version

- [ ] 3.12
- [X] 3.11
- [ ] 3.10
- [ ] 3.9
- [ ] 3.8

### nilearn version

dev

### Expected behavior

when scorlling through each map I would expect expect the crosshair to show the peak value on each map

### Current behavior & error messages

This is what I got:

![image](https://github.com/nilearn/nilearn/assets/6961185/113f779f-6040-46f8-802b-f34056367963)


Sometimes the map of interest is not even visible:

![image](https://github.com/nilearn/nilearn/assets/6961185/7ed80a53-c0b5-4806-baf2-ce2abee8ecd1)

### Steps and code to reproduce bug

```python
from nilearn import datasets

from nilearn.maskers import (
    NiftiMapsMasker,
)

atlas = datasets.fetch_atlas_msdl()
atlas_filename = atlas["maps"]

data = datasets.fetch_development_fmri(n_subjects=1)

masker = NiftiMapsMasker(
    maps_img=atlas_filename,
    standardize="zscore_sample",
    standardize_confounds="zscore_sample",
    memory="nilearn_cache",
    cmap="grey",
)
masker.fit(data.func[0])

report = masker.generate_report(displayed_maps=[2, 6, 7, 16, 21])
report.save_as_html("nifti_maps_masker.html")
```



Discussion:

Resolving patch:
diff --git a/nilearn/maskers/nifti_maps_masker.py b/nilearn/maskers/nifti_maps_masker.py
--- a/nilearn/maskers/nifti_maps_masker.py
+++ b/nilearn/maskers/nifti_maps_masker.py
@@ -342,21 +342,20 @@ def _reporting(self):
             )
             warnings.warn(msg)
             self._report_content["warning_message"] = msg
-        # Find the cut coordinates
-        cut_coords = [
-            plotting.find_xyz_cut_coords(image.index_img(maps_image, i))
-            for i in maps_to_be_displayed
-        ]
 
-        for idx, component in enumerate(maps_to_be_displayed):
+        for component in maps_to_be_displayed:
+            # Find the cut coordinates
+            cut_coords = plotting.find_xyz_cut_coords(
+                image.index_img(maps_image, component)
+            )
             display = plotting.plot_img(
                 img,
-                cut_coords=cut_coords[idx],
+                cut_coords=cut_coords,
                 black_bg=False,
                 cmap=self.cmap,
             )
             display.add_overlay(
-                image.index_img(maps_image, idx),
+                image.index_img(maps_image, component),
                 cmap=plotting.cm.black_blue,
             )
             embeded_images.append(_embed_img(display))


Test patch:
Repository: nilearn/nilearn

Issue:
[BUG] MultiNiftiMapsMasker reports are empty
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Operating system

- [X] Linux
- [ ] Mac
- [ ] Windows

### Operating system version

For example one of the following:
- Linux Ubuntu 22.04



### Python version

- [ ] 3.12
- [X] 3.11
- [ ] 3.10
- [ ] 3.9
- [ ] 3.8

### nilearn version

dev

### Expected behavior

to have non empty reports

### Current behavior & error messages

This is what I got:

![image](https://github.com/nilearn/nilearn/assets/6961185/3b0cc2fb-3ebf-4268-bc83-452d99573b76)

![image](https://github.com/nilearn/nilearn/assets/6961185/391cde29-9fbc-43de-9f72-6dfc4f99052e)



### Steps and code to reproduce bug

```python
from pathlib import Path
from nilearn import datasets
from nilearn.maskers import (
    MultiNiftiMapsMasker
)

REPORTS_DIR = Path().cwd()

difumo = datasets.fetch_atlas_difumo(
    dimension=64, resolution_mm=2, legacy_format=False
)

data = datasets.fetch_development_fmri(n_subjects=2)

masker = MultiNiftiMapsMasker(
    maps_img=difumo.maps,
    standardize="zscore_sample",
    standardize_confounds="zscore_sample",
    memory="nilearn_cache",
    n_jobs=2,
)

masker.fit()
report = masker.generate_report()
report.save_as_html(REPORTS_DIR / "multi_nifti_maps_masker_atlas.html")

_ = masker.fit_transform(data.func, confounds=data.confounds)
report = masker.generate_report()
report.save_as_html(REPORTS_DIR / "multi_nifti_maps_masker_fitted.html")
```



Discussion:
Oops, indeed.


Resolving patch:
diff --git a/nilearn/reporting/html_report.py b/nilearn/reporting/html_report.py
--- a/nilearn/reporting/html_report.py
+++ b/nilearn/reporting/html_report.py
@@ -13,7 +13,9 @@
 
 ESTIMATOR_TEMPLATES = {
     "NiftiLabelsMasker": "report_body_template_niftilabelsmasker.html",
+    "MultiNiftiLabelsMasker": "report_body_template_niftilabelsmasker.html",
     "NiftiMapsMasker": "report_body_template_niftimapsmasker.html",
+    "MultiNiftiMapsMasker": "report_body_template_niftimapsmasker.html",
     "NiftiSpheresMasker": "report_body_template_niftispheresmasker.html",
     "default": "report_body_template.html",
 }


Test patch:
Repository: nilearn/nilearn

Issue:
[DOC] Add Himanshu to authors
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Describe your proposed suggestion in detail.

Adding myself to authors

### List any pages that would be impacted.

`AUTHORS.rst`


Discussion:

Resolving patch:
diff --git a/maint_tools/citation_cff_maint.py b/maint_tools/citation_cff_maint.py
--- a/maint_tools/citation_cff_maint.py
+++ b/maint_tools/citation_cff_maint.py
@@ -15,11 +15,11 @@
     "Bertrand Thirion",
     "Elizabeth DuPre",
     "Hao-Ting Wang",
+    "Himanshu Aggarwal",
     "Jerome Dockes",
     "Nicolas Gensollen",
     "Rémi Gau",
     "Taylor Salo",
-    "Yasmin Mzayek",
 ]
 
 


Test patch:
Repository: nilearn/nilearn

Issue:
[DOC] Minor discrepancy in comparing means example
### Is there an existing issue for this?

- [X] I have searched the existing issues

### Describe your proposed suggestion in detail.

Using a movie watching dataset as an example but calling it "resting state" in several places

### List any pages that would be impacted.

The "comparing means of images with `math_img`" example: https://nilearn.github.io/stable/auto_examples/06_manipulating_images/plot_compare_mean_image.html


Discussion:
yup that's an easy fix

Resolving patch:
diff --git a/examples/06_manipulating_images/plot_compare_mean_image.py b/examples/06_manipulating_images/plot_compare_mean_image.py
--- a/examples/06_manipulating_images/plot_compare_mean_image.py
+++ b/examples/06_manipulating_images/plot_compare_mean_image.py
@@ -4,7 +4,7 @@
 
 The goal of this example is to illustrate the use of the function
 :func:`nilearn.image.math_img` with a list of images as input.
-We compare the means of 2 resting state 4D images. The mean of the images
+We compare the means of 2 movie watching 4D images. The mean of the images
 could have been computed with nilearn :func:`nilearn.image.mean_img` function.
 """
 
@@ -16,9 +16,9 @@
 
 
 # %%
-# Print basic information on the adhd subjects resting state datasets.
-print(f"Subject 1 resting state dataset at: {dataset.func[0]}")
-print(f"Subject 2 resting state dataset at: {dataset.func[1]}")
+# Print file locations for both subjects.
+print(f"Subject 1 dataset at: {dataset.func[0]}")
+print(f"Subject 2 dataset at: {dataset.func[1]}")
 
 
 # %%
@@ -32,6 +32,6 @@
 )
 
 plotting.plot_stat_map(
-    result_img, title="Comparing means of 2 resting state 4D images."
+    result_img, title="Comparing means of 2 movie watching 4D images."
 )
 plotting.show()


Test patch:
Repository: nilearn/nilearn

Issue:
:rotating_light: NIGHTLY DEPENDENCIES TEST: failure on `refs/heads/main`
The run `8815256231` of the workflow testing Nilearn with the nightly build of its dependencies failed on `refs/heads/main`.

You can view the report here: https://github.com/nilearn/nilearn/actions/runs/8815256231

Pinging @nilearn/core



Discussion:

Resolving patch:
diff --git a/nilearn/_utils/segmentation.py b/nilearn/_utils/segmentation.py
--- a/nilearn/_utils/segmentation.py
+++ b/nilearn/_utils/segmentation.py
@@ -11,10 +11,12 @@
 import warnings
 
 import numpy as np
-from scipy import ndimage as ndi, sparse
+from scipy import __version__, ndimage as ndi, sparse
 from scipy.sparse.linalg import cg
 from sklearn.utils import as_float_array
 
+from nilearn._utils.helpers import compare_version
+
 
 def _make_graph_edges_3d(n_x, n_y, n_z):
     """Return a list of edges for a 3D image.
@@ -355,7 +357,14 @@ def _solve_cg(lap_sparse, B, tol):
     lap_sparse = lap_sparse.tocsc()
     X = []
     for i in range(len(B)):
-        x0 = cg(lap_sparse, -B[i].todense(), tol=tol, atol="legacy")[0]
+        # TODO Python 3.8
+        # consider remove if/else block when dropping support for 3.8
+        # would require pinning scipy to >= 1.12
+        # See https://github.com/nilearn/nilearn/pull/4394
+        if compare_version(__version__, ">=", "1.12"):
+            x0 = cg(lap_sparse, -B[i].todense(), rtol=tol, atol=0)[0]
+        else:
+            x0 = cg(lap_sparse, -B[i].todense(), tol=tol, atol="legacy")[0]
         X.append(x0)
 
     X = np.array(X)


Test patch:
Repository: kornia/kornia

Issue:
Fix simple typo: suports -> supports
There is a small typo in kornia/filters/laplacian.py.
Should read `supports` rather than `suports`.




Discussion:

Resolving patch:
diff --git a/kornia/filters/laplacian.py b/kornia/filters/laplacian.py
--- a/kornia/filters/laplacian.py
+++ b/kornia/filters/laplacian.py
@@ -12,7 +12,7 @@ class Laplacian(nn.Module):
     r"""Creates an operator that returns a tensor using a Laplacian filter.
 
     The operator smooths the given tensor with a laplacian kernel by convolving
-    it to each channel. It suports batched operation.
+    it to each channel. It supports batched operation.
 
     Arguments:
         kernel_size (int): the size of the kernel.


Test patch: