llama-cpp-python/vendor/llama.cpp/kompute/test/TestWorkgroup.cpp

// SPDX-License-Identifier: Apache-2.0

#include "gtest/gtest.h"

#include "kompute/Kompute.hpp"
#include "kompute/logger/Logger.hpp"

#include "test_workgroup_shader.hpp"

TEST(TestWorkgroup, TestSimpleWorkgroup)
{
    std::shared_ptr<kp::TensorT<float>> tensorA = nullptr;
    std::shared_ptr<kp::TensorT<float>> tensorB = nullptr;
    {
        std::shared_ptr<kp::Sequence> sq = nullptr;

        {
            kp::Manager mgr;

            tensorA = mgr.tensor(std::vector<float>(16 * 8));
            tensorB = mgr.tensor(std::vector<float>(16 * 8));

            std::vector<std::shared_ptr<kp::Tensor>> params = { tensorA,
                                                                tensorB };
            std::vector<uint32_t> spirv(
              kp::TEST_WORKGROUP_SHADER_COMP_SPV.begin(),
              kp::TEST_WORKGROUP_SHADER_COMP_SPV.end());

            kp::Workgroup workgroup = { 16, 8, 1 };

            std::shared_ptr<kp::Algorithm> algorithm =
              mgr.algorithm(params, spirv, workgroup);

            sq = mgr.sequence();
            sq->record<kp::OpTensorSyncDevice>(params);
            sq->record<kp::OpAlgoDispatch>(algorithm);
            sq->record<kp::OpTensorSyncLocal>(params);
            sq->eval();

            std::vector<float> expectedA = {
                0,  0,  0,  0,  0,  0,  0,  0,  1,  1,  1,  1,  1,  1,  1,  1,
                2,  2,  2,  2,  2,  2,  2,  2,  3,  3,  3,  3,  3,  3,  3,  3,
                4,  4,  4,  4,  4,  4,  4,  4,  5,  5,  5,  5,  5,  5,  5,  5,
                6,  6,  6,  6,  6,  6,  6,  6,  7,  7,  7,  7,  7,  7,  7,  7,
                8,  8,  8,  8,  8,  8,  8,  8,  9,  9,  9,  9,  9,  9,  9,  9,
                10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11,
                12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13,
                14, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15
            };

            std::vector<float> expectedB = {
                0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2,
                3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5,
                6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0,
                1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3,
                4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6,
                7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1,
                2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6, 7
            };

            EXPECT_EQ(tensorA->vector(), expectedA);
            EXPECT_EQ(tensorB->vector(), expectedB);
        }
    }
}