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extern.hpp
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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_map.hpp"
#include "coordinate_map_cpu.hpp"
#include "coordinate_map_key.hpp"
#include "coordinate_map_manager.hpp"
#include "errors.hpp"
#include "types.hpp"
#include "utils.hpp"
#ifndef CPU_ONLY
#include "allocators.cuh"
#include "coordinate_map_gpu.cuh"
#endif
#include <torch/extension.h>
#include <pybind11/numpy.h>
#include <pybind11/operators.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace minkowski {
/*************************************
* Convolution
*************************************/
template <typename coordinate_type>
at::Tensor
ConvolutionForwardCPU(at::Tensor const &in_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
template <typename coordinate_type>
std::pair<at::Tensor, at::Tensor>
ConvolutionBackwardCPU(at::Tensor const &in_feat, //
at::Tensor &grad_out_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offsets, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
#ifndef CPU_ONLY
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
at::Tensor ConvolutionForwardGPU(
at::Tensor const &in_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
std::pair<at::Tensor, at::Tensor> ConvolutionBackwardGPU(
at::Tensor const &in_feat, //
at::Tensor &grad_out_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
#endif
/*************************************
* Convolution Transpose
*************************************/
template <typename coordinate_type>
at::Tensor ConvolutionTransposeForwardCPU(
at::Tensor const &in_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
bool generate_new_coordinates, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
template <typename coordinate_type>
std::pair<at::Tensor, at::Tensor> ConvolutionTransposeBackwardCPU(
at::Tensor const &in_feat, //
at::Tensor const &grad_out_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offsets, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
#ifndef CPU_ONLY
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
at::Tensor ConvolutionTransposeForwardGPU(
at::Tensor const &in_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
bool generate_new_coordinates, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
std::pair<at::Tensor, at::Tensor> ConvolutionTransposeBackwardGPU(
at::Tensor const &in_feat, //
at::Tensor const &grad_out_feat, //
at::Tensor const &kernel, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
#endif
/*************************************
* Local Pooling
*************************************/
template <typename coordinate_type>
std::pair<at::Tensor, at::Tensor>
LocalPoolingForwardCPU(at::Tensor const &in_feat,
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
PoolingMode::Type pooling_mode, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
template <typename coordinate_type>
at::Tensor
LocalPoolingBackwardCPU(at::Tensor const &in_feat, //
at::Tensor const &grad_out_feat, //
at::Tensor const &num_nonzero, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
PoolingMode::Type pooling_mode, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
cpu_manager_type<coordinate_type> *p_map_manager);
#ifndef CPU_ONLY
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
std::pair<at::Tensor, at::Tensor> LocalPoolingForwardGPU(
at::Tensor const &in_feat,
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
PoolingMode::Type pooling_mode, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
at::Tensor LocalPoolingBackwardGPU(
at::Tensor const &in_feat, //
at::Tensor const &grad_out_feat, //
at::Tensor const &num_nonzero, //
default_types::stride_type const &kernel_size, //
default_types::stride_type const &kernel_stride, //
default_types::stride_type const &kernel_dilation, //
RegionType::Type const region_type, //
at::Tensor const &offset, //
PoolingMode::Type pooling_mode, //
CoordinateMapKey *p_in_map_key, //
CoordinateMapKey *p_out_map_key, //
gpu_manager_type<coordinate_type, TemplatedAllocator> *p_map_manager);
#endif
/*************************************
* Quantization
*************************************/
std::vector<py::array> quantize_np(
py::array_t<int32_t, py::array::c_style | py::array::forcecast> coords);
std::vector<at::Tensor> quantize_th(at::Tensor &coords);
/*
vector<py::array> quantize_label_np(
py::array_t<int, py::array::c_style | py::array::forcecast> coords,
py::array_t<int, py::array::c_style | py::array::forcecast> labels,
int invalid_label);
vector<at::Tensor> quantize_label_th(at::Tensor coords, at::Tensor labels,
int invalid_label);
at::Tensor quantization_average_features(at::Tensor in_feat, at::Tensor in_map,
at::Tensor out_map, int out_nrows,
int mode);
*/
#ifndef CPU_ONLY
template <typename th_int_type>
torch::Tensor coo_spmm(torch::Tensor const &rows, torch::Tensor const &cols,
torch::Tensor const &vals, int64_t const dim_i,
int64_t const dim_j, torch::Tensor const &mat2,
int64_t spmm_algorithm_id);
std::pair<size_t, size_t> get_memory_info();
#endif
} // end namespace minkowski
namespace py = pybind11;
template <typename coordinate_type>
void instantiate_cpu_func(py::module &m, const std::string &dtypestr) {
m.def((std::string("ConvolutionForwardCPU") + dtypestr).c_str(),
&minkowski::ConvolutionForwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionBackwardCPU") + dtypestr).c_str(),
&minkowski::ConvolutionBackwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionTransposeForwardCPU") + dtypestr).c_str(),
&minkowski::ConvolutionTransposeForwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionTransposeBackwardCPU") + dtypestr).c_str(),
&minkowski::ConvolutionTransposeBackwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("LocalPoolingForwardCPU") + dtypestr).c_str(),
&minkowski::LocalPoolingForwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("LocalPoolingBackwardCPU") + dtypestr).c_str(),
&minkowski::LocalPoolingBackwardCPU<coordinate_type>,
py::call_guard<py::gil_scoped_release>());
/*
m.def((std::string("MaxPoolingForwardCPU") + dtypestr).c_str(),
&mink::MaxPoolingForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("MaxPoolingBackwardCPU") + dtypestr).c_str(),
&mink::MaxPoolingBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("MaxPoolingForwardGPU") + dtypestr).c_str(),
&mink::MaxPoolingForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("MaxPoolingBackwardGPU") + dtypestr).c_str(),
&mink::MaxPoolingBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("PoolingTransposeForwardCPU") + dtypestr).c_str(),
&mink::PoolingTransposeForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("PoolingTransposeBackwardCPU") + dtypestr).c_str(),
&mink::PoolingTransposeBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("PoolingTransposeForwardGPU") + dtypestr).c_str(),
&mink::PoolingTransposeForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("PoolingTransposeBackwardGPU") + dtypestr).c_str(),
&mink::PoolingTransposeBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("GlobalPoolingForwardCPU") + dtypestr).c_str(),
&mink::GlobalPoolingForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("GlobalPoolingBackwardCPU") + dtypestr).c_str(),
&mink::GlobalPoolingBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("GlobalPoolingForwardGPU") + dtypestr).c_str(),
&mink::GlobalPoolingForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("GlobalPoolingBackwardGPU") + dtypestr).c_str(),
&mink::GlobalPoolingBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("GlobalMaxPoolingForwardCPU") + dtypestr).c_str(),
&mink::GlobalMaxPoolingForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("GlobalMaxPoolingBackwardCPU") + dtypestr).c_str(),
&mink::GlobalMaxPoolingBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("GlobalMaxPoolingForwardGPU") + dtypestr).c_str(),
&mink::GlobalMaxPoolingForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("GlobalMaxPoolingBackwardGPU") + dtypestr).c_str(),
&mink::GlobalMaxPoolingBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("BroadcastForwardCPU") + dtypestr).c_str(),
&mink::BroadcastForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("BroadcastBackwardCPU") + dtypestr).c_str(),
&mink::BroadcastBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("BroadcastForwardGPU") + dtypestr).c_str(),
&mink::BroadcastForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("BroadcastBackwardGPU") + dtypestr).c_str(),
&mink::BroadcastBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("PruningForwardCPU") + dtypestr).c_str(),
&mink::PruningForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("PruningBackwardCPU") + dtypestr).c_str(),
&mink::PruningBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("PruningForwardGPU") + dtypestr).c_str(),
&mink::PruningForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("PruningBackwardGPU") + dtypestr).c_str(),
&mink::PruningBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
m.def((std::string("UnionForwardCPU") + dtypestr).c_str(),
&mink::UnionForwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("UnionBackwardCPU") + dtypestr).c_str(),
&mink::UnionBackwardCPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#ifndef CPU_ONLY
m.def((std::string("UnionForwardGPU") + dtypestr).c_str(),
&mink::UnionForwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("UnionBackwardGPU") + dtypestr).c_str(),
&mink::UnionBackwardGPU<MapType, Dtype>,
py::call_guard<py::gil_scoped_release>());
#endif
*/
}
#ifndef CPU_ONLY
template <typename coordinate_type,
template <typename C> class TemplatedAllocator>
void instantiate_gpu_func(py::module &m, const std::string &dtypestr) {
m.def((std::string("ConvolutionForwardGPU") + dtypestr).c_str(),
&minkowski::ConvolutionForwardGPU<coordinate_type, TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionBackwardGPU") + dtypestr).c_str(),
&minkowski::ConvolutionBackwardGPU<coordinate_type, TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionTransposeForwardGPU") + dtypestr).c_str(),
&minkowski::ConvolutionTransposeForwardGPU<coordinate_type,
TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("ConvolutionTransposeBackwardGPU") + dtypestr).c_str(),
&minkowski::ConvolutionTransposeBackwardGPU<coordinate_type,
TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
m.def((std::string("LocalPoolingForwardGPU") + dtypestr).c_str(),
&minkowski::LocalPoolingForwardGPU<coordinate_type, TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
m.def(
(std::string("LocalPoolingBackwardGPU") + dtypestr).c_str(),
&minkowski::LocalPoolingBackwardGPU<coordinate_type, TemplatedAllocator>,
py::call_guard<py::gil_scoped_release>());
}
void non_templated_cpu_func(py::module &m) {
m.def("quantize_np", &minkowski::quantize_np);
m.def("quantize_th", &minkowski::quantize_th);
}
void non_templated_gpu_func(py::module &m) {
m.def("coo_spmm_int32", &minkowski::coo_spmm<int32_t>,
py::call_guard<py::gil_scoped_release>());
m.def("coo_spmm_int64", &minkowski::coo_spmm<int64_t>,
py::call_guard<py::gil_scoped_release>());
}
#endif
void initialize_non_templated_classes(py::module &m) {
// Enums
py::enum_<minkowski::GPUMemoryAllocatorBackend::Type>(
m, "GPUMemoryAllocatorType")
.value("PYTORCH", minkowski::GPUMemoryAllocatorBackend::Type::PYTORCH)
.value("CUDA", minkowski::GPUMemoryAllocatorBackend::Type::CUDA)
.export_values();
py::enum_<minkowski::CUDAKernelMapMode::Mode>(m, "CUDAKernelMapMode")
.value("MEMORY_EFFICIENT",
minkowski::CUDAKernelMapMode::Mode::MEMORY_EFFICIENT)
.value("SPEED_OPTIMIZED",
minkowski::CUDAKernelMapMode::Mode::SPEED_OPTIMIZED)
.export_values();
py::enum_<minkowski::MinkowskiAlgorithm::Mode>(m, "MinkowskiAlgorithm")
.value("DEFAULT",
minkowski::MinkowskiAlgorithm::Mode::DEFAULT)
.value("MEMORY_EFFICIENT",
minkowski::MinkowskiAlgorithm::Mode::MEMORY_EFFICIENT)
.value("SPEED_OPTIMIZED",
minkowski::MinkowskiAlgorithm::Mode::SPEED_OPTIMIZED)
.export_values();
py::enum_<minkowski::CoordinateMapBackend::Type>(m, "CoordinateMapType")
.value("CPU", minkowski::CoordinateMapBackend::Type::CPU)
.value("CUDA", minkowski::CoordinateMapBackend::Type::CUDA)
.export_values();
py::enum_<minkowski::RegionType::Type>(m, "RegionType")
.value("HYPER_CUBE", minkowski::RegionType::Type::HYPER_CUBE)
.value("HYPER_CROSS", minkowski::RegionType::Type::HYPER_CROSS)
.value("CUSTOM", minkowski::RegionType::Type::CUSTOM)
.export_values();
py::enum_<minkowski::PoolingMode::Type>(m, "PoolingMode")
.value("LOCAL_SUM_POOLING",
minkowski::PoolingMode::Type::LOCAL_SUM_POOLING)
.value("LOCAL_AVG_POOLING",
minkowski::PoolingMode::Type::LOCAL_AVG_POOLING)
.value("LOCAL_MAX_POOLING",
minkowski::PoolingMode::Type::LOCAL_MAX_POOLING)
.export_values();
// Classes
py::class_<minkowski::CoordinateMapKey>(m, "CoordinateMapKey")
.def(py::init<minkowski::default_types::size_type>())
.def(py::init<minkowski::default_types::stride_type, std::string>())
.def("__repr__", &minkowski::CoordinateMapKey::to_string)
.def("is_key_set", &minkowski::CoordinateMapKey::is_key_set)
.def("get_coordinate_size",
&minkowski::CoordinateMapKey::get_coordinate_size)
.def("get_key", &minkowski::CoordinateMapKey::get_key)
.def("set_key", (void (minkowski::CoordinateMapKey::*)(
minkowski::default_types::stride_type, std::string)) &
minkowski::CoordinateMapKey::set_key)
.def("get_tensor_stride", &minkowski::CoordinateMapKey::get_tensor_stride)
.def(py::self == py::self);
}
template <typename manager_type>
void instantiate_manager(py::module &m, const std::string &dtypestr) {
py::class_<manager_type>(
m, (std::string("CoordinateMapManager") + dtypestr).c_str())
.def(py::init<>())
.def(py::init<minkowski::MinkowskiAlgorithm::Mode,
minkowski::default_types::size_type>())
.def("__repr__",
py::overload_cast<>(&manager_type::to_string, py::const_))
.def("print_coordinate_map",
py::overload_cast<minkowski::CoordinateMapKey const *>(
&manager_type::to_string, py::const_))
.def("insert_and_map", &manager_type::insert_and_map)
.def("stride", &manager_type::py_stride)
.def("origin", &manager_type::py_origin)
.def("get_coordinates", &manager_type::get_coordinates)
.def("get_coordinate_map_keys", &manager_type::get_coordinate_map_keys)
.def("size", py::overload_cast<minkowski::CoordinateMapKey const *>(
&manager_type::size, py::const_))
.def("kernel_map", &manager_type::kernel_map)
.def("origin_map", &manager_type::origin_map_th)
.def("origin_map_size", &manager_type::origin_map_size);
}
bool is_cuda_available() {
#ifndef CPU_ONLY
return true;
#else
return false;
#endif
}
int cuda_version() {
#if defined(CUDART_VERSION)
return CUDART_VERSION;
#else
return -1;
#endif
}
std::pair<size_t, size_t> get_gpu_memory_info() {
#ifndef CPU_ONLY
return minkowski::get_memory_info();
#else
return std::make_pair(0, 0);
#endif
}