mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-04 21:51:28 +00:00
* ad gelu and fast_gelu * added GeLU and fast GeLU * clean up * add gemm+fastgelu example * add gemm+gelu instances * update profiler * clean up * clean up * adding gemm+bias+activation * clean * adding bias * clean * adding gemm multiple d * debugging * add gemm bias add fastgelu * rename, clean * refactoring; add readme * refactor * refactor * refactor * refactor * refactor * refactor * fix * fix * update example * update example * rename * update example * add ckProfiler * clean * clean * clean * clean * add client app example * update readme * delete obselete files * remove old client app * delete old file * cleaning * clean * remove half * fix header path * fix header path * fix header path * fix header path * fix header path * fix header path for all examples * fix header path * fix header path * fix header path * fix header path * fix header path * fix header path * fix header path * fix header path * fix header path * revert client app example * clean build * fix build * temporary disable client test on Jenkins * clean * clean * clean
116 lines
5.4 KiB
C++
116 lines
5.4 KiB
C++
#include <vector>
|
|
#include <iostream>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include "ck/ck.hpp"
|
|
#include "ck/utility/number.hpp"
|
|
#include "ck/tensor_operation/gpu/device/device_softmax.hpp"
|
|
|
|
#include "ck/library/utility/check_err.hpp"
|
|
#include "ck/library/host_tensor/host_tensor.hpp"
|
|
#include "ck/library/host_tensor/device_memory.hpp"
|
|
#include "ck/library/reference_tensor_operation/cpu/reference_softmax.hpp"
|
|
|
|
namespace ck {
|
|
|
|
template <typename Tuple>
|
|
class TestSoftmax : public ::testing::Test
|
|
{
|
|
protected:
|
|
using InDataType = std::tuple_element_t<0, Tuple>;
|
|
using AccDataType = std::tuple_element_t<1, Tuple>;
|
|
using OutDataType = std::tuple_element_t<2, Tuple>;
|
|
static constexpr index_t Rank = std::tuple_element_t<3, Tuple>{}.value;
|
|
static constexpr index_t NumReduceDim = std::tuple_element_t<4, Tuple>{}.value;
|
|
static constexpr index_t BlockSize = std::tuple_element_t<5, Tuple>{}.value;
|
|
static constexpr index_t MThreadClusterSize = std::tuple_element_t<6, Tuple>{}.value;
|
|
static constexpr index_t KThreadClusterSize = std::tuple_element_t<7, Tuple>{}.value;
|
|
static constexpr index_t MThreadSliceSize = std::tuple_element_t<8, Tuple>{}.value;
|
|
static constexpr index_t KThreadSliceSize = std::tuple_element_t<9, Tuple>{}.value;
|
|
static constexpr index_t InSrcVectorDim = std::tuple_element_t<10, Tuple>{}.value;
|
|
static constexpr index_t InSrcVectorSize = std::tuple_element_t<11, Tuple>{}.value;
|
|
static constexpr index_t OutDstVectorSize = std::tuple_element_t<12, Tuple>{}.value;
|
|
|
|
using ReferenceInstance =
|
|
tensor_operation::host::ReferenceSoftmax<InDataType, OutDataType, AccDataType>;
|
|
|
|
using DeviceInstance = tensor_operation::device::DeviceSoftmax<InDataType,
|
|
AccDataType,
|
|
OutDataType,
|
|
Rank,
|
|
NumReduceDim,
|
|
BlockSize,
|
|
MThreadClusterSize,
|
|
KThreadClusterSize,
|
|
MThreadSliceSize,
|
|
KThreadSliceSize,
|
|
InSrcVectorDim,
|
|
InSrcVectorSize,
|
|
OutDstVectorSize>;
|
|
|
|
TestSoftmax() : ref_instance_invoker_(ReferenceInstance{}.MakeInvoker()) {}
|
|
|
|
void RunSingle(std::vector<index_t> in_length, AccDataType alpha, AccDataType beta)
|
|
{
|
|
std::vector<index_t> reduce_dims(NumReduceDim);
|
|
std::iota(reduce_dims.begin(), reduce_dims.end(), Rank - NumReduceDim);
|
|
|
|
Tensor<InDataType> in(in_length);
|
|
Tensor<OutDataType> out(in_length);
|
|
|
|
in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5});
|
|
out.GenerateTensorValue(GeneratorTensor_2<OutDataType>{-5, 5});
|
|
|
|
Tensor<OutDataType> out_ref(out);
|
|
|
|
DeviceMem in_dev(sizeof(InDataType) * in.mDesc.GetElementSpace());
|
|
DeviceMem out_dev(sizeof(OutDataType) * out.mDesc.GetElementSpace());
|
|
in_dev.ToDevice(in.mData.data());
|
|
out_dev.ToDevice(out.mData.data());
|
|
|
|
std::vector<index_t> i_in_lengths(in.mDesc.GetLengths().begin(),
|
|
in.mDesc.GetLengths().end());
|
|
std::vector<index_t> i_in_strides(in.mDesc.GetStrides().begin(),
|
|
in.mDesc.GetStrides().end());
|
|
|
|
auto device_instance = DeviceInstance{};
|
|
auto argument_ptr = device_instance.MakeArgumentPointer(i_in_lengths,
|
|
i_in_strides,
|
|
reduce_dims,
|
|
alpha,
|
|
beta,
|
|
in_dev.GetDeviceBuffer(),
|
|
out_dev.GetDeviceBuffer());
|
|
|
|
if(!device_instance.IsSupportedArgument(argument_ptr.get()))
|
|
{
|
|
FAIL() << "Unsupported argument";
|
|
}
|
|
|
|
auto invoker_ptr = device_instance.MakeInvokerPointer();
|
|
invoker_ptr->Run(argument_ptr.get());
|
|
|
|
ref_instance_invoker_.Run({in, out_ref, alpha, beta, Rank, reduce_dims});
|
|
|
|
out_dev.FromDevice(out.mData.data());
|
|
EXPECT_TRUE(ck::utils::check_err(out.mData, out_ref.mData));
|
|
}
|
|
|
|
void Run()
|
|
{
|
|
for(auto in_length : this->in_lengths_)
|
|
{
|
|
for(auto scale : this->scales_)
|
|
{
|
|
this->RunSingle(in_length, std::get<0>(scale), std::get<1>(scale));
|
|
}
|
|
}
|
|
}
|
|
|
|
std::vector<std::vector<index_t>> in_lengths_ = {{1, 8, 128}, {2, 128, 1024}, {3, 9, 1032}};
|
|
std::vector<std::tuple<AccDataType, AccDataType>> scales_ = {{1, 0}, {2, 2}, {0, 1}};
|
|
|
|
typename ReferenceInstance::Invoker ref_instance_invoker_;
|
|
};
|
|
} // namespace ck
|