Add copyright notice to every C++ source

torchmdnet/extensions/extensions.cpp

@@ -1,4 +1,8 @@
-/* Raul P. Pelaez 2023. Torch extensions to the torchmdnet library.
+/*
+ * Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ * Raul P. Pelaez 2023. Torch extensions to the torchmdnet library.
  * You can expose functions to python here which will be compatible with TorchScript.
  * Add your exports to the TORCH_LIBRARY macro below, see __init__.py to see how to access them from python.
  * The WITH_CUDA macro will be defined when compiling with CUDA support.

torchmdnet/extensions/neighbors/common.cuh

@@ -1,4 +1,7 @@
-/* Raul P. Pelaez 2023. Common utilities for the CUDA neighbor operation.
+/* Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ * Raul P. Pelaez 2023. Common utilities for the CUDA neighbor operation.
  */
 #ifndef NEIGHBORS_COMMON_CUH
 #define NEIGHBORS_COMMON_CUH

torchmdnet/extensions/neighbors/neighbors_cpu.cpp

@@ -1,3 +1,7 @@
+/* Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+*/
 #include <torch/extension.h>
 #include <tuple>
 

torchmdnet/extensions/neighbors/neighbors_cuda.cu

@@ -1,5 +1,8 @@
-/* Raul P. Pelaez 2023
-   Connection between the neighbor CUDA implementations and the torch extension.
+/*
+ * Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ * (See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ * Raul P. Pelaez 2023
  */
 #include "neighbors_cuda_brute.cuh"
 #include "neighbors_cuda_cell.cuh"

torchmdnet/extensions/neighbors/neighbors_cuda_brute.cuh

@@ -1,9 +1,13 @@
-/* Raul P. Pelaez 2023. Brute force neighbor list construction in CUDA.
-
-   A brute force approach that assigns a thread per each possible pair of particles in the system.
-   Based on an implementation by Raimondas Galvelis.
-   Works fantastically for small (less than 10K atoms) systems, but cannot handle more than 32K
-   atoms.
+/* Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ *
+ * Raul P. Pelaez 2023. Brute force neighbor list construction in CUDA.
+ *
+ * A brute force approach that assigns a thread per each possible pair of particles in the system.
+ * Based on an implementation by Raimondas Galvelis.
+ * Works fantastically for small (less than 10K atoms) systems, but cannot handle more than 32K
+ * atoms.
  */
 #ifndef NEIGHBORS_BRUTE_CUH
 #define NEIGHBORS_BRUTE_CUH

torchmdnet/extensions/neighbors/neighbors_cuda_cell.cuh

@@ -1,5 +1,7 @@
-/* Raul P. Pelaez 2023. Batched cell list neighbor list implementation for CUDA.
-
+/* Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ * Raul P. Pelaez 2023. Batched cell list neighbor list implementation for CUDA.
  */
 #ifndef NEIGHBOR_CUDA_CELL_H
 #define NEIGHBOR_CUDA_CELL_H

torchmdnet/extensions/neighbors/neighbors_cuda_shared.cuh

@@ -1,8 +1,11 @@
-/* Raul P. Pelaez 2023. Shared memory neighbor list construction for CUDA.
-   This brute force approach checks all pairs of atoms by collaborativelly loading and processing
-   tiles of atoms into shared memory.
-   This approach is tipically slower than the brute force approach, but can handle an arbitrarily
-   large number of atoms.
+/* Copyright Universitat Pompeu Fabra 2020-2023  https://www.compscience.org
+ * Distributed under the MIT License.
+ *(See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
+ * Raul P. Pelaez 2023. Shared memory neighbor list construction for CUDA.
+ * This brute force approach checks all pairs of atoms by collaborativelly loading and processing
+ * tiles of atoms into shared memory.
+ * This approach is tipically slower than the brute force approach, but can handle an arbitrarily
+ * large number of atoms.
  */
 #ifndef NEIGHBORS_SHARED_CUH
 #define NEIGHBORS_SHARED_CUH