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255 lines
8.8 KiB
C++
255 lines
8.8 KiB
C++
// Copyright Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#include <cmath>
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#include <memory>
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#include "CustomMatchers.hpp"
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#include "CustomSections.hpp"
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#include "TestContext.hpp"
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#include "TestKernels.hpp"
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#include <common/SourceMatcher.hpp>
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#include <common/TestValues.hpp>
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#include <rocRoller/AssemblyKernel.hpp>
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#include <rocRoller/CodeGen/ArgumentLoader.hpp>
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#include <rocRoller/CodeGen/CopyGenerator.hpp>
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#include <rocRoller/CodeGen/Instruction.hpp>
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#include <rocRoller/CodeGen/MemoryInstructions.hpp>
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#include <rocRoller/Expression.hpp>
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#include <rocRoller/ExpressionTransformations.hpp>
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#include <catch2/catch_test_macros.hpp>
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#include <catch2/matchers/catch_matchers.hpp>
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#include <catch2/matchers/catch_matchers_floating_point.hpp>
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#include <catch2/matchers/catch_matchers_string.hpp>
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using namespace rocRoller;
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namespace ExpressionTest
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{
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struct BinaryExpressionKernel : public AssemblyTestKernel
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{
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using ExpressionFunc = std::function<Expression::ExpressionPtr(Expression::ExpressionPtr,
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Expression::ExpressionPtr)>;
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BinaryExpressionKernel(ContextPtr context,
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ExpressionFunc func,
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DataType resultType,
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DataType aType,
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DataType bType)
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: AssemblyTestKernel(context)
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, m_func(func)
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, m_resultType(resultType)
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, m_aType(aType)
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, m_bType(bType)
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{
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}
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void generate() override
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{
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auto k = m_context->kernel();
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k->addArgument(
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{"result", {m_resultType, PointerType::PointerGlobal}, DataDirection::WriteOnly});
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k->addArgument({"a", m_aType});
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k->addArgument({"b", m_bType});
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m_context->schedule(k->preamble());
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m_context->schedule(k->prolog());
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auto kb = [&]() -> Generator<Instruction> {
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Register::ValuePtr s_result, s_a, s_b;
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co_yield m_context->argLoader()->getValue("result", s_result);
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co_yield m_context->argLoader()->getValue("a", s_a);
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co_yield m_context->argLoader()->getValue("b", s_b);
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auto v_result
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= Register::Value::Placeholder(m_context,
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Register::Type::Vector,
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{m_resultType, PointerType::PointerGlobal},
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1);
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auto v_a = s_a->placeholder(Register::Type::Vector, {});
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auto v_b = s_b->placeholder(Register::Type::Vector, {});
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auto a = v_a->expression();
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auto b = v_b->expression();
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auto expr = m_func(a, b);
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co_yield v_a->allocate();
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co_yield v_b->allocate();
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co_yield v_result->allocate();
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co_yield m_context->copier()->copy(v_result, s_result, "Move pointer");
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co_yield m_context->copier()->copy(v_a, s_a, "Move pointer");
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co_yield m_context->copier()->copy(v_b, s_b, "Move pointer");
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Register::ValuePtr v_c;
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co_yield Expression::generate(v_c, expr, m_context);
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co_yield m_context->mem()->storeGlobal(
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v_result, v_c, 0, DataTypeInfo::Get(m_resultType).elementBytes);
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};
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m_context->schedule(kb());
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m_context->schedule(k->postamble());
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m_context->schedule(k->amdgpu_metadata());
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}
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protected:
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ExpressionFunc m_func;
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DataType m_resultType, m_aType, m_bType;
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};
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void potentiallyMutate(int32_t& x)
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{
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// Just force the compiler to consider that we might have changed the value of x.
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}
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TEST_CASE("Run binary expression kernel 1", "[expression][gpu]")
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{
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auto context = TestContext::ForTestDevice();
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auto expr
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= [](Expression::ExpressionPtr a, Expression::ExpressionPtr b) { return -b * (a + b); };
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BinaryExpressionKernel kernel(
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context.get(), expr, DataType::Double, DataType::Double, DataType::Double);
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auto d_result = make_shared_device<double>();
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for(auto a : TestValues::doubleValues)
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{
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for(auto b : TestValues::doubleValues)
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{
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double r = -b * (a + b);
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CAPTURE(a, b, r);
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kernel({}, d_result.get(), a, b);
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double result;
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CHECK_THAT(d_result, HasDeviceScalar(Catch::Matchers::WithinULP(r, 2)));
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CHECK_THAT(d_result, HasDeviceScalarEqualTo(r));
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}
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}
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}
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TEST_CASE("Assemble binary expression kernel 1", "[expression][codegen]")
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{
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SUPPORTED_ARCH_SECTION(arch)
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{
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auto context = TestContext::ForTarget(arch);
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auto expr = [](Expression::ExpressionPtr a, Expression::ExpressionPtr b) {
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return -b * (a + b);
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};
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BinaryExpressionKernel kernel(
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context.get(), expr, DataType::Double, DataType::Double, DataType::Double);
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CHECK(kernel.getAssembledKernel().size() > 0);
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}
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}
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TEST_CASE("Run binary expression kernel 2", "[expression][gpu]")
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{
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auto context = TestContext::ForTestDevice();
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auto expr = [](Expression::ExpressionPtr a, Expression::ExpressionPtr b) {
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return Expression::fuseTernary((a + b) << b);
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};
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BinaryExpressionKernel kernel(
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context.get(), expr, DataType::Int32, DataType::Int32, DataType::UInt32);
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auto d_result = make_shared_device<int>();
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for(auto a : TestValues::int32Values)
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{
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for(auto b : {5, 2, 3, 1, 12, 4})
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{
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int r = (a + b) << b;
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CAPTURE(a, b, r);
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kernel({}, d_result.get(), a, b);
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CHECK_THAT(d_result, HasDeviceScalarEqualTo(r));
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}
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}
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}
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TEST_CASE("Assemble binary expression kernel 2", "[expression][codegen]")
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{
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SUPPORTED_ARCH_SECTION(arch)
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{
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auto context = TestContext::ForTarget(arch);
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auto expr = [](Expression::ExpressionPtr a, Expression::ExpressionPtr b) {
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return Expression::fuseTernary((a + b) << b);
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};
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BinaryExpressionKernel kernel(
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context.get(), expr, DataType::Int32, DataType::Int32, DataType::UInt32);
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CHECK(kernel.getAssembledKernel().size() > 0);
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using namespace Catch::Matchers;
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CHECK_THAT(context.output(),
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ContainsSubstring("v_lshlrev_b32", Catch::CaseSensitive::No));
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}
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}
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TEST_CASE("Run ConvertPropagation kernel binary",
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"[expression][expression-transformation][gpu]")
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{
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using InputType = int64_t;
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using ResultType = int32_t;
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constexpr auto inputType = TypeInfo<InputType>::Var.dataType;
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constexpr auto resultType = TypeInfo<ResultType>::Var.dataType;
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using CPUExpressionFunc = std::function<ResultType(InputType, InputType)>;
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auto [gpu_expr, cpu_expr] = GENERATE(
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as<std::pair<BinaryExpressionKernel::ExpressionFunc, CPUExpressionFunc>>{},
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std::make_pair([](auto a, auto b) { return Expression::convert(resultType, a + b); },
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[](auto a, auto b) { return static_cast<ResultType>(a + b); }),
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std::make_pair(
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[](auto a, auto b) { return Expression::convert(resultType, a + a * b); },
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[](auto a, auto b) { return static_cast<ResultType>(a + a * b); }),
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std::make_pair(
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[](auto a, auto b) {
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return Expression::convert(resultType,
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a + Expression::convert(resultType, a * b));
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},
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[](auto a, auto b) {
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return static_cast<ResultType>(a + static_cast<ResultType>(a * b));
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}),
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std::make_pair(
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[](auto a, auto b) { return Expression::convert(resultType, a - a * b); },
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[](auto a, auto b) { return static_cast<ResultType>(a - a * b); }));
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BinaryExpressionKernel kernel(
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TestContext::ForTestDevice().get(), gpu_expr, resultType, inputType, inputType);
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auto result = make_shared_device<int32_t>();
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for(auto a : TestValues::int64Values)
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{
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for(auto b : TestValues::int64Values)
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{
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CAPTURE(a, b);
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int32_t r = cpu_expr(a, b);
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kernel({}, result.get(), a, b);
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CHECK_THAT(result, HasDeviceScalarEqualTo(r));
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}
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}
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}
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}
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