[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

.devcontainer/devcontainer.json

@@ -23,4 +23,4 @@
 	// "postCreateCommand": "pip install -r requirements.txt",
 	// Uncomment to connect as a non-root user. See https://aka.ms/vscode-remote/containers/non-root.
 	// "remoteUser": "vscode"
-}
+}

.github/workflows/deploy.yaml

@@ -2,7 +2,7 @@ on:
   push:
     tags:
     - 'v*'
-    
+
 name: Deploy
 
 jobs:

MANIFEST.in

@@ -5,4 +5,4 @@ include pyproject.toml
 
 recursive-exclude test *
 recursive-include cpu *
-recursive-include cuda *
+recursive-include cuda *

conda/torch-points-kernels/README.md

@@ -1,3 +1,3 @@
 ```
 ./build_conda.sh 3.9 1.9.0 cu111  # python, pytorch and cuda version
-```
+```

cpu/include/cloud.h

@@ -104,4 +104,4 @@ inline std::ostream& operator<<(std::ostream& os, const PointCloud<scalar_t>& P)
         os << "[" << p[0] << ", " << p[1] << ", " << p[2] << "];";
     }
     return os;
-}
+}

cpu/include/fps.h

@@ -1,3 +1,3 @@
 #pragma once
 #include <torch/extension.h>
-at::Tensor fps(at::Tensor points, const int nsamples, bool random = true);
+at::Tensor fps(at::Tensor points, const int nsamples, bool random = true);

cpu/include/interpolate.h

@@ -4,4 +4,4 @@
 at::Tensor knn_interpolate(at::Tensor features, at::Tensor idx, at::Tensor weight);
 
 at::Tensor knn_interpolate_grad(at::Tensor grad_out, at::Tensor idx, at::Tensor weight,
-                                const int m);
+                                const int m);

cpu/include/knn.h

@@ -1,3 +1,3 @@
 #pragma once
 #include <torch/extension.h>
-std::pair<at::Tensor, at::Tensor> dense_knn(at::Tensor support, at::Tensor query, int k);
+std::pair<at::Tensor, at::Tensor> dense_knn(at::Tensor support, at::Tensor query, int k);

cpu/src/fps.cpp

@@ -34,4 +34,4 @@ at::Tensor fps(at::Tensor points, const int nsamples, bool random)
         }
     }
     return out;
-}
+}

cpu/src/knn.cpp

@@ -56,4 +56,4 @@ std::pair<at::Tensor, at::Tensor> dense_knn(at::Tensor support, at::Tensor query
     auto out_idx = torch::stack(batch_idx);
     auto out_dist = torch::stack(batch_dist);
     return std::make_pair(out_idx, out_dist);
-}
+}