* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
#include "gtest/gtest.h"
#include <array>
#include <memory>
#include "acl/acl.h"
#include "aclnn/acl_meta.h"
#include "opdev/make_op_executor.h"
#include "opdev/op_dfx.h"
#include "op_cache_internal.h"
#include "depends/profiler/profiler_stub.h"
#include "thread_local_context.h"
using namespace op;
using namespace op::internal;
static bool profiling_called = false;
class ProfilingCacheUtProfiler : public ProfilerStub {
public:
int32_t MsprofReportApi(uint32_t agingFlag, const MsprofApi* api)
{
profiling_called = true;
return 0;
}
};
static ProfilingCacheUtProfiler prof;
namespace op {
namespace internal {
void CacheTensorInfo(const FVector<const aclTensor*>& inTensors, const FVector<const aclTensor*>& outTensors);
void CacheDfxInfo(uint32_t blockDim, const ProfilingInfoId& id, const TaskInfo& taskInfo, bool isMemSet);
aclnnStatus DoReportAdditionInfo(void* infoLists, const TaskInfo& taskInfo,
const op::internal::ProfilingInfoId& profilingInfoId);
}
}
class ProfilingCacheUt : public testing::Test {
protected:
static void SetUpTestCase()
{
op::internal::opProfilingSwitch.reportFlag = true;
op::internal::opProfilingSwitch.kernelLaunchFlag = true;
op::internal::opProfilingSwitch.kernelLaunchFlag = true;
ProfilerStub::GetInstance()->Install(&prof);
}
static void TearDownTestCase()
{
op::internal::opProfilingSwitch.reportFlag = false;
op::internal::opProfilingSwitch.kernelLaunchFlag = false;
op::internal::opProfilingSwitch.kernelLaunchFlag = false;
ProfilerStub::GetInstance()->UnInstall();
}
};
TEST_F(ProfilingCacheUt, test_storeage)
{
vector<int64_t> shapeA = {2, 1, 32, 16};
aclDataType dtype1 = aclDataType::ACL_FLOAT16;
int64_t multiStride1 = 2;
auto storageShapeA = shapeA;
void* deviceDataA = nullptr;
vector<int64_t> stridesA = {2, 1, 32, 16};
const aclTensor* tensor = aclCreateTensor(shapeA.data(), shapeA.size(), dtype1, stridesA.data(), 0,
aclFormat::ACL_FORMAT_ND, storageShapeA.data(), storageShapeA.size(),
deviceDataA);
;
int64_t* storageDims = nullptr;
uint64_t storageDimsNum = 0;
EXPECT_EQ(aclGetStorageShape(tensor, &storageDims, &storageDimsNum), OK);
EXPECT_EQ(aclGetStorageShape(nullptr, &storageDims, &storageDimsNum), ACLNN_ERR_PARAM_NULLPTR);
delete[] storageDims;
aclDestroyTensor(tensor);
}
TEST_F(ProfilingCacheUt, test_cache_tensor_has_op_cache)
{
vector<int64_t> shapeA = {2, 1, 32, 16};
aclDataType dtype1 = aclDataType::ACL_FLOAT16;
int64_t multiStride1 = 2;
auto storageShapeA = shapeA;
void* deviceDataA = nullptr;
vector<int64_t> stridesA = {2, 1, 32, 16};
const aclTensor* tensorIn = aclCreateTensor(shapeA.data(), shapeA.size(), dtype1, stridesA.data(), 0,
aclFormat::ACL_FORMAT_ND, storageShapeA.data(), storageShapeA.size(),
deviceDataA);
;
const aclTensor* tensorOut = aclCreateTensor(shapeA.data(), shapeA.size(), dtype1, stridesA.data(), 0,
aclFormat::ACL_FORMAT_ND, storageShapeA.data(), storageShapeA.size(),
deviceDataA);
;
FVector<const aclTensor*> in;
FVector<const aclTensor*> out;
in.push_back(tensorIn);
out.push_back(tensorOut);
op::internal::ProfilingInfoId id;
auto opExecCache = new OpExecCache();
opExecCache->SetCacheBuf(GetCacheBuf());
GetOpCacheContext().SetOpCache(opExecCache);
CacheTensorInfo(in, out);
TaskInfo info;
info.type = MSPROF_GE_TASK_TYPE_AI_CORE;
info.ration = 0;
CacheDfxInfo(32, id, info, false);
aclDestroyTensor(tensorIn);
aclDestroyTensor(tensorOut);
delete opExecCache;
}
TEST_F(ProfilingCacheUt, test_cache_tensor_restore_and_report)
{
vector<int64_t> shapeA = {2, 1, 32, 16};
aclDataType dtype1 = aclDataType::ACL_FLOAT16;
int64_t multiStride1 = 2;
auto storageShapeA = shapeA;
void* deviceDataA = nullptr;
vector<int64_t> stridesA = {2, 1, 32, 16};
const aclTensor* tensorIn = aclCreateTensor(shapeA.data(), shapeA.size(), dtype1, stridesA.data(), 0,
aclFormat::ACL_FORMAT_ND, storageShapeA.data(), storageShapeA.size(),
deviceDataA);
;
const aclTensor* tensorOut = aclCreateTensor(shapeA.data(), shapeA.size(), dtype1, stridesA.data(), 0,
aclFormat::ACL_FORMAT_ND, storageShapeA.data(), storageShapeA.size(),
deviceDataA);
;
FVector<const aclTensor*> in;
FVector<const aclTensor*> out;
in.push_back(tensorIn);
out.push_back(tensorOut);
op::internal::ProfilingInfoId id;
auto opExecCache = new OpExecCache();
opExecCache->SetCacheBuf(GetCacheBuf());
GetOpCacheContext().SetOpCache(opExecCache);
CacheTensorInfo(in, out);
TaskInfo info;
info.type = MSPROF_GE_TASK_TYPE_AI_CORE;
info.ration = 0;
CacheDfxInfo(32, id, info, false);
EXPECT_EQ(DoReportAdditionInfo(opExecCache->GetCacheTensorInfo(0), info, id), OK);
aclDestroyTensor(tensorIn);
aclDestroyTensor(tensorOut);
delete opExecCache;
}