122 lines
3.7 KiB
Plaintext
122 lines
3.7 KiB
Plaintext
/**
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* Copyright 2021-2024, XGBoost Contributors
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*/
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#include <gtest/gtest.h>
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#include <thrust/equal.h> // for equal
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#include <thrust/iterator/constant_iterator.h> // for make_constant_iterator
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#include <thrust/sequence.h> // for sequence
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#include "../../../src/common/cuda_context.cuh"
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#include "../../../src/common/linalg_op.cuh"
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#include "../helpers.h"
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#include "xgboost/context.h"
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#include "xgboost/linalg.h"
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namespace xgboost::linalg {
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namespace {
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void TestElementWiseKernel() {
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auto device = DeviceOrd::CUDA(0);
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Tensor<float, 3> l{{2, 3, 4}, device};
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{
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/**
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* Non-contiguous
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*/
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// GPU view
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auto t = l.View(device).Slice(linalg::All(), 1, linalg::All());
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ASSERT_FALSE(t.CContiguous());
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ElementWiseTransformDevice(t, [] __device__(size_t i, float) { return i; });
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// CPU view
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t = l.View(DeviceOrd::CPU()).Slice(linalg::All(), 1, linalg::All());
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std::size_t k = 0;
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for (size_t i = 0; i < l.Shape(0); ++i) {
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for (size_t j = 0; j < l.Shape(2); ++j) {
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ASSERT_EQ(k++, t(i, j));
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}
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}
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t = l.View(device).Slice(linalg::All(), 1, linalg::All());
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cuda_impl::ElementWiseKernel(
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t, [=] XGBOOST_DEVICE(std::size_t i, std::size_t j) mutable { t(i, j) = i + j; });
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t = l.Slice(linalg::All(), 1, linalg::All());
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for (size_t i = 0; i < l.Shape(0); ++i) {
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for (size_t j = 0; j < l.Shape(2); ++j) {
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ASSERT_EQ(i + j, t(i, j));
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}
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}
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}
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{
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/**
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* Contiguous
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*/
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auto t = l.View(device);
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ElementWiseTransformDevice(t, [] XGBOOST_DEVICE(size_t i, float) { return i; });
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ASSERT_TRUE(t.CContiguous());
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// CPU view
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t = l.View(DeviceOrd::CPU());
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size_t ind = 0;
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for (size_t i = 0; i < l.Shape(0); ++i) {
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for (size_t j = 0; j < l.Shape(1); ++j) {
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for (size_t k = 0; k < l.Shape(2); ++k) {
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ASSERT_EQ(ind++, t(i, j, k));
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}
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}
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}
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}
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}
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void TestSlice() {
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auto ctx = MakeCUDACtx(1);
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thrust::device_vector<double> data(2 * 3 * 4);
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auto t = MakeTensorView(&ctx, dh::ToSpan(data), 2, 3, 4);
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dh::LaunchN(1, [=] __device__(size_t) {
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auto s = t.Slice(linalg::All(), linalg::Range(0, 3), linalg::Range(0, 4));
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auto all = t.Slice(linalg::All(), linalg::All(), linalg::All());
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static_assert(decltype(s)::kDimension == 3);
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for (size_t i = 0; i < s.Shape(0); ++i) {
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for (size_t j = 0; j < s.Shape(1); ++j) {
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for (size_t k = 0; k < s.Shape(2); ++k) {
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SPAN_CHECK(s(i, j, k) == all(i, j, k));
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}
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}
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}
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});
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}
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void TestWriteAccess(CUDAContext const* cuctx, linalg::TensorView<double, 3> t) {
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thrust::for_each(cuctx->CTP(), linalg::tbegin(t), linalg::tend(t),
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[=] XGBOOST_DEVICE(double& v) { v = 0; });
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auto eq = thrust::equal(cuctx->CTP(), linalg::tcbegin(t), linalg::tcend(t),
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thrust::make_constant_iterator<double>(0.0), thrust::equal_to<>{});
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ASSERT_TRUE(eq);
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}
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} // anonymous namespace
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TEST(Linalg, GPUElementWise) { TestElementWiseKernel(); }
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TEST(Linalg, GPUTensorView) { TestSlice(); }
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TEST(Linalg, GPUIter) {
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auto ctx = MakeCUDACtx(1);
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auto cuctx = ctx.CUDACtx();
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dh::device_vector<double> data(2 * 3 * 4);
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thrust::sequence(cuctx->CTP(), data.begin(), data.end(), 1.0);
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auto t = MakeTensorView(&ctx, dh::ToSpan(data), 2, 3, 4);
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static_assert(!std::is_const_v<decltype(t)::element_type>);
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static_assert(!std::is_const_v<decltype(t)::value_type>);
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auto n = std::distance(linalg::tcbegin(t), linalg::tcend(t));
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ASSERT_EQ(n, t.Size());
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ASSERT_FALSE(t.Empty());
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bool eq = thrust::equal(cuctx->CTP(), data.cbegin(), data.cend(), linalg::tcbegin(t));
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ASSERT_TRUE(eq);
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TestWriteAccess(cuctx, t);
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}
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} // namespace xgboost::linalg
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