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/* Copyright (c) 2020 NVIDIA CORPORATION.
* Copyright (c) 2018-2020 Chris Choy (chrischoy@ai.stanford.edu)
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
* IN THE SOFTWARE.
*
* Please cite "4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural
* Networks", CVPR'19 (https://arxiv.org/abs/1904.08755) if you use any part
* of the code.
*/
#include "coordinate.hpp"
#include "types.hpp"
#include <torch/extension.h>
#include <unordered_map>
#include <vector>
namespace minkowski {
using coordinate_type = int32_t;
uint32_t coordinate_test(const torch::Tensor &coordinates) {
// Create TensorArgs. These record the names and positions of each tensor as a
// parameter.
torch::TensorArg arg_coordinates(coordinates, "coordinates", 0);
torch::CheckedFrom c = "coordinate_test";
torch::checkContiguous(c, arg_coordinates);
// must match coordinate_type
torch::checkScalarType(c, arg_coordinates, torch::kInt);
torch::checkBackend(c, arg_coordinates.tensor, torch::Backend::CPU);
torch::checkDim(c, arg_coordinates, 2);
auto const N = (uint32_t)coordinates.size(0);
auto const D = (uint32_t)coordinates.size(1);
using map_type =
std::unordered_map<coordinate<coordinate_type>, default_types::index_type,
detail::coordinate_murmur3<coordinate_type>,
detail::coordinate_equal_to<coordinate_type>>;
map_type map = map_type{N, detail::coordinate_murmur3<coordinate_type>{D},
detail::coordinate_equal_to<coordinate_type>{D}};
coordinate_type const * ptr = coordinates.data_ptr<coordinate_type>();
for (default_types::index_type i = 0; i < N; i++) {
map[coordinate<coordinate_type>{ptr + D * i}] = i;
}
return map.size();
}
} // namespace minkowski
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("coordinate_test", &minkowski::coordinate_test,
"Minkowski Engine coordinate test");
}
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