mirror of
https://github.com/nomic-ai/kompute.git
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393 lines
12 KiB
C++
393 lines
12 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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#include "gtest/gtest.h"
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#include "kompute/Kompute.hpp"
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#include "kompute/logger/Logger.hpp"
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#include "shaders/Utils.hpp"
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TEST(TestPushConstants, TestConstantsAlgoDispatchOverride)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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float x;
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float y;
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float z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { float pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<float>> tensor =
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mgr.tensor({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo = mgr.algorithm(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { 0.0, 0.0, 0.0 });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(algo,
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std::vector<float>{ 0.1, 0.2, 0.3 });
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sq->eval<kp::OpAlgoDispatch>(algo,
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std::vector<float>{ 0.3, 0.2, 0.1 });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(tensor->vector(), std::vector<float>({ 0.4, 0.4, 0.4 }));
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}
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}
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}
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TEST(TestPushConstants, TestConstantsAlgoDispatchNoOverride)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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float x;
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float y;
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float z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { float pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<float>> tensor =
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mgr.tensor({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo = mgr.algorithm(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { 0.1, 0.2, 0.3 });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(algo);
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sq->eval<kp::OpAlgoDispatch>(algo,
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std::vector<float>{ 0.3, 0.2, 0.1 });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(tensor->vector(), std::vector<float>({ 0.4, 0.4, 0.4 }));
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}
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}
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}
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TEST(TestPushConstants, TestConstantsWrongSize)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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float x;
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float y;
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float z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { float pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<float>> tensor =
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mgr.tensor({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo = mgr.algorithm(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { 0.0 });
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sq = mgr.sequence()->record<kp::OpTensorSyncDevice>({ tensor });
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EXPECT_THROW(sq->record<kp::OpAlgoDispatch>(
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algo, std::vector<float>{ 0.1, 0.2, 0.3 }),
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std::runtime_error);
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}
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}
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}
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// TODO: Ensure different types are considered for push constants
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// TEST(TestPushConstants, TestConstantsWrongType)
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// {
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// {
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// std::string shader(R"(
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// #version 450
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// layout(push_constant) uniform PushConstants {
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// float x;
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// float y;
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// float z;
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// } pcs;
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// layout (local_size_x = 1) in;
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// layout(set = 0, binding = 0) buffer a { float pa[]; };
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// void main() {
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// pa[0] += pcs.x;
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// pa[1] += pcs.y;
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// pa[2] += pcs.z;
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// })");
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//
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// std::vector<uint32_t> spirv = compileSource(shader);
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//
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// std::shared_ptr<kp::Sequence> sq = nullptr;
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//
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// {
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// kp::Manager mgr;
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//
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// std::shared_ptr<kp::TensorT<float>> tensor =
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// mgr.tensor({ 0, 0, 0 });
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//
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// std::shared_ptr<kp::Algorithm> algo = mgr.algorithm(
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// { tensor }, spirv, kp::Workgroup({ 1 }), {}, { 0.0 });
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//
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// sq = mgr.sequence()->record<kp::OpTensorSyncDevice>({ tensor });
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//
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// EXPECT_THROW(sq->record<kp::OpAlgoDispatch>(
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// algo, std::vector<uint32_t>{ 1, 2, 3 }),
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// std::runtime_error);
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// }
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// }
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// }
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TEST(TestPushConstants, TestConstantsMixedTypes)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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float x;
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uint y;
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int z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { float pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y - 2147483000;
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pa[2] += pcs.z;
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})");
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struct TestConsts
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{
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float x;
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uint32_t y;
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int32_t z;
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};
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<float>> tensor =
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mgr.tensorT<float>({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo =
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mgr.algorithm<float, TestConsts>(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { { 0, 0, 0 } });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(
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algo, std::vector<TestConsts>{ { 15.32, 2147483650, 10 } });
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sq->eval<kp::OpAlgoDispatch>(
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algo, std::vector<TestConsts>{ { 30.32, 2147483650, -3 } });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(tensor->vector(), std::vector<float>({ 45.64, 1300, 7 }));
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}
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}
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}
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TEST(TestPushConstants, TestConstantsInt)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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int x;
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int y;
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int z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { int pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<int32_t>> tensor =
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mgr.tensorT<int32_t>({ -1, -1, -1 });
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std::shared_ptr<kp::Algorithm> algo =
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mgr.algorithm<int32_t, int32_t>(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { { 0, 0, 0 } });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(
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algo, std::vector<int32_t>{ { -1, -1, -1 } });
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sq->eval<kp::OpAlgoDispatch>(
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algo, std::vector<int32_t>{ { -1, -1, -1 } });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(tensor->vector(), std::vector<int32_t>({ -3, -3, -3 }));
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}
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}
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}
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TEST(TestPushConstants, TestConstantsUnsignedInt)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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uint x;
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uint y;
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uint z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { uint pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<uint32_t>> tensor =
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mgr.tensorT<uint32_t>({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo =
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mgr.algorithm<uint32_t, uint32_t>(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { { 0, 0, 0 } });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(
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algo,
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std::vector<uint32_t>{ { 2147483650, 2147483650, 2147483650 } });
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sq->eval<kp::OpAlgoDispatch>(algo,
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std::vector<uint32_t>{ { 5, 5, 5 } });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(
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tensor->vector(),
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std::vector<uint32_t>({ 2147483655, 2147483655, 2147483655 }));
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}
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}
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}
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TEST(TestPushConstants, TestConstantsDouble)
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{
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{
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std::string shader(R"(
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#version 450
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layout(push_constant) uniform PushConstants {
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double x;
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double y;
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double z;
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} pcs;
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layout (local_size_x = 1) in;
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layout(set = 0, binding = 0) buffer a { double pa[]; };
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void main() {
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pa[0] += pcs.x;
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pa[1] += pcs.y;
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pa[2] += pcs.z;
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})");
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std::vector<uint32_t> spirv = compileSource(shader);
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std::shared_ptr<kp::Sequence> sq = nullptr;
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{
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kp::Manager mgr;
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std::shared_ptr<kp::TensorT<double>> tensor =
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mgr.tensorT<double>({ 0, 0, 0 });
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std::shared_ptr<kp::Algorithm> algo = mgr.algorithm<double, double>(
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{ tensor }, spirv, kp::Workgroup({ 1 }), {}, { { 0, 0, 0 } });
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sq = mgr.sequence()->eval<kp::OpTensorSyncDevice>({ tensor });
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// We need to run this in sequence to avoid race condition
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// We can't use atomicAdd as swiftshader doesn't support it for
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// float
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sq->eval<kp::OpAlgoDispatch>(
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algo,
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std::vector<double>{ { 1.1111222233334444,
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2.1111222233334444,
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3.1111222233334444 } });
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sq->eval<kp::OpAlgoDispatch>(
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algo,
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std::vector<double>{ { 1.1111222233334444,
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2.1111222233334444,
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3.1111222233334444 } });
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sq->eval<kp::OpTensorSyncLocal>({ tensor });
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EXPECT_EQ(tensor->vector(),
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std::vector<double>({ 2.2222444466668888,
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4.2222444466668888,
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6.2222444466668888 }));
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}
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}
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}
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