#include #include #include #ifdef WITH_CUDA #include "cuda/radius_cuda.h" #endif #include "cpu/radius_cpu.h" #ifdef _WIN32 PyMODINIT_FUNC PyInit__radius(void) { return NULL; } #endif torch::Tensor radius(torch::Tensor x, torch::Tensor y, torch::optional ptr_x, torch::optional ptr_y, double r, int64_t max_num_neighbors, int64_t n_threads) { if (x.device().is_cuda()) { #ifdef WITH_CUDA if (!(ptr_x.has_value()) && !(ptr_y.has_value())) { auto batch_x = torch::tensor({0,torch::size(x,0)}).to(torch::kLong).to(torch::kCUDA); auto batch_y = torch::tensor({0,torch::size(y,0)}).to(torch::kLong).to(torch::kCUDA); return radius_cuda(x, y, batch_x, batch_y, r, max_num_neighbors); } else if (!(ptr_x.has_value())) { auto batch_x = torch::tensor({0,torch::size(x,0)}).to(torch::kLong).to(torch::kCUDA); auto batch_y = ptr_y.value(); return radius_cuda(x, y, batch_x, batch_y, r, max_num_neighbors); } else if (!(ptr_y.has_value())) { auto batch_x = ptr_x.value(); auto batch_y = torch::tensor({0,torch::size(y,0)}).to(torch::kLong).to(torch::kCUDA); return radius_cuda(x, y, batch_x, batch_y, r, max_num_neighbors); } auto batch_x = ptr_x.value(); auto batch_y = ptr_y.value(); return radius_cuda(x, y, batch_x, batch_y, r, max_num_neighbors); #else AT_ERROR("Not compiled with CUDA support"); #endif } else { if (!(ptr_x.has_value()) && !(ptr_y.has_value())) { return radius_cpu(x,y,r,max_num_neighbors, n_threads); } if (!(ptr_x.has_value())) { auto batch_x = torch::zeros({torch::size(x,0)}).to(torch::kLong); auto batch_y = ptr_y.value(); return batch_radius_cpu(x, y, batch_x, batch_y, r, max_num_neighbors); } else if (!(ptr_y.has_value())) { auto batch_x = ptr_x.value(); auto batch_y = torch::zeros({torch::size(y,0)}).to(torch::kLong); return batch_radius_cpu(x, y, batch_x, batch_y, r, max_num_neighbors); } auto batch_x = ptr_x.value(); auto batch_y = ptr_y.value(); return batch_radius_cpu(x, y, batch_x, batch_y, r, max_num_neighbors); } } static auto registry = torch::RegisterOperators().op("torch_cluster::radius", &radius);