chore: import upstream snapshot with attribution
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/**
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* Copyright (c) 2020 by Contributors
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* @file array/cpu/array_nonzero.cc
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* @brief Array nonzero CPU implementation
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*/
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#include <dgl/array.h>
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#include <cub/cub.cuh>
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#include "../../runtime/cuda/cuda_common.h"
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#include "./utils.h"
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namespace dgl {
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using runtime::NDArray;
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namespace aten {
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namespace impl {
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template <typename IdType>
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struct IsNonZeroIndex {
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explicit IsNonZeroIndex(const IdType* array) : array_(array) {}
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__device__ bool operator()(const int64_t index) { return array_[index] != 0; }
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const IdType* array_;
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};
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template <DGLDeviceType XPU, typename IdType>
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IdArray NonZero(IdArray array) {
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const auto& ctx = array->ctx;
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auto device = runtime::DeviceAPI::Get(ctx);
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const int64_t len = array->shape[0];
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IdArray ret = NewIdArray(len, ctx, 64);
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cudaStream_t stream = runtime::getCurrentCUDAStream();
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const IdType* const in_data = static_cast<const IdType*>(array->data);
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int64_t* const out_data = static_cast<int64_t*>(ret->data);
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IsNonZeroIndex<IdType> comp(in_data);
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cub::CountingInputIterator<int64_t> counter(0);
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// room for cub to output on GPU
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int64_t* d_num_nonzeros =
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static_cast<int64_t*>(device->AllocWorkspace(ctx, sizeof(int64_t)));
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size_t temp_size = 0;
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CUDA_CALL(cub::DeviceSelect::If(
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nullptr, temp_size, counter, out_data, d_num_nonzeros, len, comp,
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stream));
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void* temp = device->AllocWorkspace(ctx, temp_size);
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CUDA_CALL(cub::DeviceSelect::If(
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temp, temp_size, counter, out_data, d_num_nonzeros, len, comp, stream));
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device->FreeWorkspace(ctx, temp);
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// copy number of selected elements from GPU to CPU
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int64_t num_nonzeros = cuda::GetCUDAScalar(device, ctx, d_num_nonzeros);
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device->FreeWorkspace(ctx, d_num_nonzeros);
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device->StreamSync(ctx, stream);
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// truncate array to size
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return ret.CreateView({num_nonzeros}, ret->dtype, 0);
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}
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template IdArray NonZero<kDGLCUDA, int32_t>(IdArray);
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template IdArray NonZero<kDGLCUDA, int64_t>(IdArray);
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} // namespace impl
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} // namespace aten
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} // namespace dgl
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