f1275f52c1
* Rewrite gpu_id related code. * Remove normalised/unnormalised operatios. * Address difference between `Index' and `Device ID'. * Modify doc for `gpu_id'. * Better LOG for GPUSet. * Check specified n_gpus. * Remove inappropriate `device_idx' term. * Clarify GpuIdType and size_t.
110 lines
3.5 KiB
Plaintext
110 lines
3.5 KiB
Plaintext
// This converts all tests from CPU to GPU.
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#include "test_transform_range.cc"
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#if defined(XGBOOST_USE_NCCL)
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namespace xgboost {
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namespace common {
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// Test here is multi gpu specific
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TEST(Transform, MGPU_Basic) {
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auto devices = GPUSet::AllVisible();
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CHECK_GT(devices.Size(), 1);
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const size_t size {256};
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std::vector<bst_float> h_in(size);
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std::vector<bst_float> h_out(size);
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InitializeRange(h_in.begin(), h_in.end());
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std::vector<bst_float> h_sol(size);
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InitializeRange(h_sol.begin(), h_sol.end());
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const HostDeviceVector<bst_float> in_vec {h_in,
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GPUDistribution::Block(GPUSet::Empty())};
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HostDeviceVector<bst_float> out_vec {h_out,
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GPUDistribution::Block(GPUSet::Empty())};
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out_vec.Fill(0);
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in_vec.Reshard(GPUDistribution::Granular(devices, 8));
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out_vec.Reshard(GPUDistribution::Block(devices));
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// Granularity is different, resharding will throw.
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EXPECT_ANY_THROW(
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Transform<>::Init(TestTransformRange<bst_float>{}, Range{0, size}, devices)
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.Eval(&out_vec, &in_vec));
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Transform<>::Init(TestTransformRange<bst_float>{}, Range{0, size},
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devices, false).Eval(&out_vec, &in_vec);
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std::vector<bst_float> res = out_vec.HostVector();
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ASSERT_TRUE(std::equal(h_sol.begin(), h_sol.end(), res.begin()));
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}
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// Test for multi-classes setting.
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template <typename T>
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struct TestTransformRangeGranular {
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const size_t granularity = 8;
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TestTransformRangeGranular(const size_t granular) : granularity{granular} {}
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void XGBOOST_DEVICE operator()(size_t _idx,
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Span<bst_float> _out, Span<const bst_float> _in) {
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auto in_sub = _in.subspan(_idx * granularity, granularity);
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auto out_sub = _out.subspan(_idx * granularity, granularity);
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for (size_t i = 0; i < granularity; ++i) {
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out_sub[i] = in_sub[i];
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}
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}
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};
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TEST(Transform, MGPU_Granularity) {
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GPUSet devices = GPUSet::All(0, -1);
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const size_t size {8990};
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const size_t granularity = 10;
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GPUDistribution distribution =
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GPUDistribution::Granular(devices, granularity);
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std::vector<bst_float> h_in(size);
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std::vector<bst_float> h_out(size);
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InitializeRange(h_in.begin(), h_in.end());
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std::vector<bst_float> h_sol(size);
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InitializeRange(h_sol.begin(), h_sol.end());
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const HostDeviceVector<bst_float> in_vec {h_in, distribution};
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HostDeviceVector<bst_float> out_vec {h_out, distribution};
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ASSERT_NO_THROW(
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Transform<>::Init(
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TestTransformRangeGranular<bst_float>{granularity},
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Range{0, size / granularity},
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distribution)
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.Eval(&out_vec, &in_vec));
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std::vector<bst_float> res = out_vec.HostVector();
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ASSERT_TRUE(std::equal(h_sol.begin(), h_sol.end(), res.begin()));
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}
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TEST(Transform, MGPU_SpecifiedGpuId) {
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// Use 1 GPU, Numbering of GPU starts from 1
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auto devices = GPUSet::All(1, 1);
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const size_t size {256};
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std::vector<bst_float> h_in(size);
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std::vector<bst_float> h_out(size);
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InitializeRange(h_in.begin(), h_in.end());
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std::vector<bst_float> h_sol(size);
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InitializeRange(h_sol.begin(), h_sol.end());
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const HostDeviceVector<bst_float> in_vec {h_in,
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GPUDistribution::Block(devices)};
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HostDeviceVector<bst_float> out_vec {h_out,
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GPUDistribution::Block(devices)};
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ASSERT_NO_THROW(
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Transform<>::Init(TestTransformRange<bst_float>{}, Range{0, size}, devices)
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.Eval(&out_vec, &in_vec));
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std::vector<bst_float> res = out_vec.HostVector();
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ASSERT_TRUE(std::equal(h_sol.begin(), h_sol.end(), res.begin()));
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}
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} // namespace xgboost
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} // namespace common
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#endif |