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// SPDX-License-Identifier: Apache-2.0
#include "gtest/gtest.h"
#include "kompute/Kompute.hpp"
#include "kompute/logger/Logger.hpp"
#include "shaders/Utils.hpp"
TEST(TestMultipleAlgoExecutions, TestEndToEndFunctionality)
{
kp::Manager mgr;
// Default tensor constructor simplifies creation of float values
auto tensorInA = mgr.tensor({ 2., 2., 2. });
auto tensorInB = mgr.tensor({ 1., 2., 3. });
// Explicit type constructor supports int, in32, double, float and int
auto tensorOutA = mgr.tensorT<uint32_t>({ 0, 0, 0 });
auto tensorOutB = mgr.tensorT<uint32_t>({ 0, 0, 0 });
std::string shader = (R"(
#version 450
layout (local_size_x = 1) in;
// The input tensors bind index is relative to index in parameter passed
layout(set = 0, binding = 0) buffer buf_in_a { float in_a[]; };
layout(set = 0, binding = 1) buffer buf_in_b { float in_b[]; };
layout(set = 0, binding = 2) buffer buf_out_a { uint out_a[]; };
layout(set = 0, binding = 3) buffer buf_out_b { uint out_b[]; };
// Kompute supports push constants updated on dispatch
layout(push_constant) uniform PushConstants {
float val;
} push_const;
// Kompute also supports spec constants on initalization
layout(constant_id = 0) const float const_one = 0;
void main() {
uint index = gl_GlobalInvocationID.x;
out_a[index] += uint( in_a[index] * in_b[index] );
out_b[index] += uint( const_one * push_const.val );
}
)");
std::vector<std::shared_ptr<kp::Tensor>> params = {
tensorInA, tensorInB, tensorOutA, tensorOutB
};
kp::Workgroup workgroup({ 3, 1, 1 });
std::vector<float> specConsts({ 2 });
std::vector<float> pushConstsA({ 2.0 });
std::vector<float> pushConstsB({ 3.0 });
auto algorithm = mgr.algorithm(
params, compileSource(shader), workgroup, specConsts, pushConstsA);
// 3. Run operation with string shader synchronously
mgr.sequence()
->record<kp::OpTensorSyncDevice>(params)
->record<kp::OpAlgoDispatch>(algorithm)
->eval()
->record<kp::OpAlgoDispatch>(algorithm, pushConstsB)
->eval();
auto sq = mgr.sequence();
sq->evalAsync<kp::OpTensorSyncLocal>(params);
sq->evalAwait();
EXPECT_EQ(tensorOutA->vector(), std::vector<uint32_t>({ 4, 8, 12 }));
EXPECT_EQ(tensorOutB->vector(), std::vector<uint32_t>({ 10, 10, 10 }));
}
TEST(TestMultipleAlgoExecutions, SingleSequenceRecord)
{
kp::Manager mgr;
std::shared_ptr<kp::TensorT<float>> tensorA = mgr.tensor({ 0, 0, 0 });
std::string shader(R"(
#version 450
layout (local_size_x = 1) in;
layout(set = 0, binding = 0) buffer a { float pa[]; };
void main() {
uint index = gl_GlobalInvocationID.x;
pa[index] = pa[index] + 1;
})");
std::vector<uint32_t> spirv = compileSource(shader);
{
// A sharedMemoryBarrier is required as the shader is not thread-safe:w
std::shared_ptr<kp::OpMemoryBarrier> shaderBarrier{
new kp::OpMemoryBarrier({ tensorA },
vk::AccessFlagBits::eTransferRead,
vk::AccessFlagBits::eShaderWrite,
vk::PipelineStageFlagBits::eComputeShader,
vk::PipelineStageFlagBits::eComputeShader)
};
mgr.sequence()
->record<kp::OpTensorSyncDevice>({ tensorA })
->record<kp::OpAlgoDispatch>(mgr.algorithm({ tensorA }, spirv))
->record(shaderBarrier)
->record<kp::OpAlgoDispatch>(mgr.algorithm({ tensorA }, spirv))
->record(shaderBarrier)
->record<kp::OpAlgoDispatch>(mgr.algorithm({ tensorA }, spirv))
->record<kp::OpTensorSyncLocal>({ tensorA })
->eval();
}
EXPECT_EQ(tensorA->vector(), std::vector<float>({ 3, 3, 3 }));
}
TEST(TestMultipleAlgoExecutions, MultipleCmdBufRecords)
{
kp::Manager mgr;
std::shared_ptr<kp::TensorT<float>> tensorA = mgr.tensor({ 0, 0, 0 });
std::string shader(R"(
#version 450
layout (local_size_x = 1) in;
layout(set = 0, binding = 0) buffer a { float pa[]; };
void main() {
uint index = gl_GlobalInvocationID.x;
pa[index] = pa[index] + 1;
})");
std::vector<uint32_t> spirv = compileSource(shader);
std::shared_ptr<kp::Algorithm> algorithm =
mgr.algorithm({ tensorA }, spirv);
std::shared_ptr<kp::Sequence> sq = mgr.sequence();
mgr.sequence()->record<kp::OpTensorSyncDevice>({ tensorA })->eval();
mgr.sequence()->record<kp::OpAlgoDispatch>(algorithm)->eval();
mgr.sequence()->record<kp::OpAlgoDispatch>(algorithm)->eval();
mgr.sequence()->record<kp::OpAlgoDispatch>(algorithm)->eval();
mgr.sequence()->record<kp::OpTensorSyncLocal>({ tensorA })->eval();
EXPECT_EQ(tensorA->vector(), std::vector<float>({ 3, 3, 3 }));
}
TEST(TestMultipleAlgoExecutions, MultipleSequences)
{
kp::Manager mgr;
std::shared_ptr<kp::TensorT<float>> tensorA = mgr.tensor({ 0, 0, 0 });
std::string shader(R"(
#version 450
layout (local_size_x = 1) in;
layout(set = 0, binding = 0) buffer a { float pa[]; };
void main() {
uint index = gl_GlobalInvocationID.x;
pa[index] = pa[index] + 1;
})");
std::vector<uint32_t> spirv = compileSource(shader);
std::shared_ptr<kp::Algorithm> algorithm =
mgr.algorithm({ tensorA }, spirv);
std::shared_ptr<kp::Sequence> sq = mgr.sequence();
sq->record<kp::OpTensorSyncDevice>({ tensorA })->eval();
sq->record<kp::OpAlgoDispatch>(algorithm)->eval();
sq->record<kp::OpAlgoDispatch>(algorithm)->eval();
sq->record<kp::OpAlgoDispatch>(algorithm)->eval();
sq->record<kp::OpTensorSyncLocal>({ tensorA })->eval();
EXPECT_EQ(tensorA->vector(), std::vector<float>({ 3, 3, 3 }));
}
TEST(TestMultipleAlgoExecutions, SingleRecordMultipleEval)
{
kp::Manager mgr;
std::shared_ptr<kp::TensorT<float>> tensorA = mgr.tensor({ 0, 0, 0 });
std::string shader(R"(
#version 450
layout (local_size_x = 1) in;
layout(set = 0, binding = 0) buffer a { float pa[]; };
void main() {
uint index = gl_GlobalInvocationID.x;
pa[index] = pa[index] + 1;
})");
std::vector<uint32_t> spirv = compileSource(shader);
std::shared_ptr<kp::Algorithm> algorithm =
mgr.algorithm({ tensorA }, spirv);
std::shared_ptr<kp::Sequence> sq = mgr.sequence();
sq->record<kp::OpTensorSyncDevice>({ tensorA })->eval();
sq->record<kp::OpAlgoDispatch>(algorithm)->eval()->eval()->eval();
sq->record<kp::OpTensorSyncLocal>({ tensorA })->eval();
EXPECT_EQ(tensorA->vector(), std::vector<float>({ 3, 3, 3 }));
}
TEST(TestMultipleAlgoExecutions, TestAlgorithmUtilFunctions)
{
kp::Manager mgr;
// Default tensor constructor simplifies creation of float values
auto tensorInA = mgr.tensor({ 2., 2., 2. });
auto tensorInB = mgr.tensor({ 1., 2., 3. });
// Explicit type constructor supports int, in32, double, float and int
auto tensorOutA = mgr.tensorT<uint32_t>({ 0, 0, 0 });
auto tensorOutB = mgr.tensorT<uint32_t>({ 0, 0, 0 });
std::string shader = (R"(
#version 450
layout (local_size_x = 1) in;
// The input tensors bind index is relative to index in parameter passed
layout(set = 0, binding = 0) buffer buf_in_a { float in_a[]; };
layout(set = 0, binding = 1) buffer buf_in_b { float in_b[]; };
layout(set = 0, binding = 2) buffer buf_out_a { uint out_a[]; };
layout(set = 0, binding = 3) buffer buf_out_b { uint out_b[]; };
// Kompute supports push constants updated on dispatch
layout(push_constant) uniform PushConstants {
float val;
} push_const;
// Kompute also supports spec constants on initalization
layout(constant_id = 0) const float const_one = 0;
void main() {
uint index = gl_GlobalInvocationID.x;
out_a[index] += uint( in_a[index] * in_b[index] );
out_b[index] += uint( const_one * push_const.val );
}
)");
std::vector<std::shared_ptr<kp::Tensor>> params = {
tensorInA, tensorInB, tensorOutA, tensorOutB
};
kp::Workgroup workgroup({ 3, 1, 1 });
std::vector<float> specConsts({ 2 });
std::vector<float> pushConsts({ 2.0 });
auto algorithm = mgr.algorithm(
params, compileSource(shader), workgroup, specConsts, pushConsts);
EXPECT_EQ(algorithm->getWorkgroup(), workgroup);
EXPECT_EQ(algorithm->getPushConstants<float>(), pushConsts);
EXPECT_EQ(algorithm->getSpecializationConstants<float>(), specConsts);
}