* 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 <array>
#include <iostream>
#include <memory>
#include <stdlib.h>
#include "gtest/gtest.h"
#include "gtest/gtest_prod.h"
#include "acl/acl.h"
#include "register/op_impl_registry.h"
#include "aclnn/acl_meta.h"
#include "aclnn/aclnn_base.h"
#include "kernel_mgr.h"
#include "memset_ctx_holder.h"
#include "opdev/make_op_executor.h"
#include "opdev/op_def.h"
#include "opdev/op_dfx.h"
#include "opdev/common_types.h"
#include "opdev/op_arg_def.h"
#include "opdev/op_errno.h"
#include "op_ctx_def.h"
#include "thread_local_context.h"
#include "op_kernel.h"
#include "memset_op.h"
#include "depends/platform/platform_stub.h"
#include "kernel_launcher.h"
#include "depends/acl/aclrt_stub.h"
#include "test_comp_op_common.h"
using namespace op;
using namespace op::internal;
using namespace op::internal::test;
extern inline uint32_t SortOpTypeId();
OP_TYPE_REGISTER(Axpy);
OP_TYPE_REGISTER(MemSet);
OP_TYPE_REGISTER(MemSetV2);
OP_TYPE_REGISTER(AddN);
class KernelLaunchUT : public testing::Test {
protected:
static void SetUpTestCase()
{
setenv("ASCEND_OPP_PATH", OP_API_COMMON_UT_SRC_DIR, 1);
op::internal::GetThreadLocalContext().cacheHasFull_ = true;
AxpyOpTypeId();
SortOpTypeId();
AddNOpTypeId();
}
static void TearDownTestCase() {}
op::internal::OpKernelBin* CreateFakeOpKernelBin(bool hasDevPtrArg)
{
uint32_t opType = op::OpTypeDict::ToOpType("QuantBatchMatmulV3");
const char* p = std::getenv("ASCEND_OPP_PATH");
EXPECT_NE(p, nullptr);
KeyAndDetail key;
key.key = "hahaha";
size_t hashKey = 123;
char jsonPath[1024];
char binPath[1024];
snprintf_s(jsonPath, sizeof(jsonPath), sizeof(jsonPath),
"%s/built-in/op_impl/ai_core/tbe/kernel/ascend910/quant_batch_matmul_v3/"
"QuantBatchMatmulV3_ND_ND_int8_int8_bf16_high_performance.json",
p);
snprintf_s(binPath, sizeof(binPath), sizeof(binPath),
"%s/built-in/op_impl/ai_core/tbe/kernel/ascend910/add/"
"Add_41dadce325b0f810d03359af2a38990b_high_performance.o",
p);
op::internal::OpKernelBin* fakeBin = new op::internal::OpKernelBin(
opType, jsonPath, jsonPath, binPath, key, hashKey, BinType::DYNAMIC_BIN, false, hasDevPtrArg);
return fakeBin;
}
};
TEST_F(KernelLaunchUT, KernelLaunchUTCase1)
{
op::Shape selfShape{33, 15, 1, 48};
op::Shape otherShape{33, 15, 14, 48};
op::Shape outShape{33, 15, 14, 48};
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
auto other = std::make_unique<aclTensor>(otherShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
float alpha = 13.37;
auto out = std::make_unique<aclTensor>(outShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
uint32_t opType = op::OpTypeDict::ToOpType("Axpy");
auto input = OP_INPUT(self.get(), other.get());
auto output = OP_OUTPUT(out.get());
auto attr = OP_ATTR(alpha);
auto ws = OP_WORKSPACE(out.get());
int dummyStream = 0;
void* stream = &dummyStream;
auto ctx = op::MakeOpArgContext(input, output, attr, ws);
auto rc = op::internal::gKernelMgr.Run(opType, stream, ctx);
EXPECT_EQ(rc, ACL_SUCCESS);
}
TEST_F(KernelLaunchUT, KernelLaunchUTCase2)
{
op::Shape selfShape{33, 15, 64};
op::Shape outShape{33, 15, 64};
op::Shape idxShape{33, 15, 64};
op::Shape wsShape{32};
int64_t dim = 0;
bool descending = true;
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, nullptr);
auto out = std::make_unique<aclTensor>(outShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, nullptr);
auto idx = std::make_unique<aclTensor>(idxShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
uint32_t opType = op::OpTypeDict::ToOpType("Sort");
auto input = OP_INPUT(self.get());
auto output = OP_OUTPUT(out.get(), idx.get(), static_cast<aclTensor*>(nullptr),
static_cast<aclTensorList*>(nullptr));
auto attr = OP_ATTR(dim, descending);
auto ws1 = std::make_unique<aclTensor>(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, nullptr);
auto ws2 = std::make_unique<aclTensor>(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, nullptr);
auto ws3 = std::make_unique<aclTensor>(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, nullptr);
const aclTensor* wsArr[] = {ws1.get(), ws2.get(), ws3.get()};
aclTensorList* wsList = aclCreateTensorList(wsArr, 3);
auto wsArg = OP_WORKSPACE(wsList);
int dummyStream = 0;
void* stream = &dummyStream;
auto ctx = op::MakeOpArgContext(input, output, attr, wsArg);
auto rc = op::internal::gKernelMgr.Run(opType, stream, ctx);
EXPECT_EQ(rc, ACL_SUCCESS);
delete wsList;
}
TEST_F(KernelLaunchUT, KernelLaunchUTCase3)
{
op::Shape selfShape{33, 15, 64};
op::Shape outShape{33, 15, 64};
op::Shape idxShape{33, 15, 64};
int alpha = 1337;
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto other = std::make_unique<aclTensor>(outShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto out = std::make_unique<aclTensor>(idxShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
const aclTensor* inputTensor[2] = {self.get(), other.get()};
aclTensorList* inputList = aclCreateTensorList(inputTensor, 2);
uint32_t opType = op::OpTypeDict::ToOpType("AddN");
auto input = OP_INPUT(inputList);
auto output = OP_OUTPUT(out.get());
auto attr = OP_ATTR(alpha);
auto ws = OP_WORKSPACE(out.get());
int dummyStream = 0;
void* stream = &dummyStream;
auto ctx = op::MakeOpArgContext(input, output, attr, ws);
auto rc = op::internal::gKernelMgr.Run(opType, stream, ctx);
delete inputList;
EXPECT_EQ(rc, ACL_SUCCESS);
}
TEST_F(KernelLaunchUT, KernelLaunchUTCase4)
{
op::Shape selfShape{33, 15, 64};
op::Shape outShape{33, 15, 64};
op::Shape idxShape{33, 15, 64};
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto other = std::make_unique<aclTensor>(outShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto out = std::make_unique<aclTensor>(idxShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
const aclTensor* inputTensor[2] = {self.get(), other.get()};
aclTensorList* inputList = aclCreateTensorList(inputTensor, 2);
auto input = OP_INPUT(inputList);
auto output = OP_OUTPUT(out.get());
auto ctx = op::MakeOpArgContext(input, output);
size_t tn_list = op::internal::GetAclTensorCount(*(ctx->GetOpArg(op::OpArgDef::OP_INPUT_ARG)));
size_t tn = op::internal::GetAclTensorCount(*(ctx->GetOpArg(op::OpArgDef::OP_OUTPUT_ARG)));
delete inputList;
EXPECT_EQ(tn, 1u);
EXPECT_EQ(tn_list, 2u);
}
TEST_F(KernelLaunchUT, MemSetTiling1)
{
op::internal::MemSetKernelContextHolder ctx;
op::internal::MemSetTensorInfo tensor{0, ge::DT_FLOAT, 0.0f, 0, 100, 256, op::OpArgType::OPARG_FLOAT};
std::vector<op::internal::MemSetTensorInfo> tensorInfo{tensor};
ctx.UpdateComputeNodeInfo(tensorInfo);
EXPECT_EQ(ctx.inputNum_, 2ul);
}
extern "C" int InitHugeMemThreadLocal(void* arg, bool sync);
extern "C" void UnInitHugeMemThreadLocal(void* arg, bool sync);
extern "C" void ReleaseHugeMem(void* arg, bool sync);
static void MemSetV2OutputTensorNoDevPtr(op::internal::OpKernelBin* kernelBin)
{
OP_LOGI("not support dev ptr");
InitHugeMemThreadLocal(nullptr, false);
PlatformInfoStub::GetInstance()->SetSoCVersion("Ascend950", "Ascend950DT_9591");
op::Shape selfShape{33, 15, 64};
op::Shape wsShape{32};
int addr[6] = {0};
aclTensor tensor1(selfShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, &addr[0]);
tensor1.SetFromWorkspace(false);
aclTensor* tensorPtr1 = &tensor1;
aclTensor tensor2(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[1]);
tensor2.SetFromWorkspace(false);
aclTensor* tensorPtr2 = &tensor2;
aclTensor tensor3(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[2]);
tensor3.SetFromWorkspace(false);
aclTensor* tensorPtr3 = &tensor3;
aclTensor tensor4(wsShape, op::DataType::DT_UINT32, op::Format::FORMAT_ND, &addr[3]);
tensor4.SetFromWorkspace(false);
aclTensor* tensorPtr4 = &tensor4;
aclTensor tensor5(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, &addr[4]);
tensor5.SetFromWorkspace(false);
aclTensor* tensorPtr5 = &tensor5;
aclTensor tensor6(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, &addr[5]);
tensor6.SetFromWorkspace(false);
aclTensor* tensorPtr6 = &tensor6;
const aclTensor* tensorArr1[3] = {tensorPtr2, tensorPtr3, nullptr};
aclTensorList* tensorList1 = aclCreateTensorList(tensorArr1, 3);
const aclTensor* tensorsArr2[2] = {tensorPtr5, tensorPtr6};
aclTensorList* workspaceTensorList = aclCreateTensorList(tensorsArr2, 2);
auto input = OP_INPUT(tensorPtr1, tensorList1);
auto output = OP_OUTPUT(tensorPtr1, tensorList1);
auto workspace = OP_WORKSPACE(tensorPtr4, workspaceTensorList);
auto outshape = OP_OUTSHAPE(tensorPtr4, 0);
auto ctx = op::MakeOpArgContext(input, output, workspace, outshape);
kernelBin->memSetValue_ = {
{3, op::DataType::DT_FLOAT, 1.1f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{4, op::DataType::DT_INT32, 0.0f, 1, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{5, op::DataType::DT_INT32, 0.0f, 2, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{6, op::DataType::DT_UINT32, 0.0f, 3, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{7, op::DataType::DT_FLOAT16, 2.2f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{8, op::DataType::DT_FLOAT16, 3.3f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{9, op::DataType::DT_UINT32, 0.0f, 4, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr}};
auto unique_executor = CREATE_EXECUTOR();
aclOpExecutor* executor = unique_executor.get();
op::internal::GetThreadLocalContext().executor_ = executor;
aclrtStream stream = 0;
auto ret = kernelBin->MemsetOutputTensor(stream, ctx);
EXPECT_EQ(ret, ACLNN_SUCCESS);
EXPECT_EQ(kernelBin->memSetValueCtx_.size(), 7);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].argIdx_, 3);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].tensor_, tensorPtr1);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].argIdx_, 4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].tensor_, tensorPtr2);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].argIdx_, 5);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].tensor_, tensorPtr3);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].argIdx_, 6);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].tensor_, tensorPtr4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[4].argIdx_, 7);
EXPECT_EQ((kernelBin->memSetValueCtx_)[4].tensor_, tensorPtr5);
EXPECT_EQ((kernelBin->memSetValueCtx_)[4].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[5].argIdx_, 8);
EXPECT_EQ((kernelBin->memSetValueCtx_)[5].tensor_, tensorPtr6);
EXPECT_EQ((kernelBin->memSetValueCtx_)[5].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[6].argIdx_, 9);
EXPECT_EQ((kernelBin->memSetValueCtx_)[6].tensor_, tensorPtr4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[6].tensorList_, nullptr);
MemsetV2ArgContext memsetV2ArgCtx;
ret = memsetV2ArgCtx.Init(kernelBin->memSetValueCtx_);
EXPECT_EQ(ret, ACLNN_SUCCESS);
op::OpArgContext* memsetV2OpArgCtx = memsetV2ArgCtx.GetMemsetV2OpArgContext();
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_INPUT_ARG), true);
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_OUTPUT_ARG), true);
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_WORKSPACE_ARG), true);
EXPECT_EQ(memsetV2ArgCtx.memsetTensors_->Size(), 7);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[0], tensorPtr1);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[1], tensorPtr2);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[2], tensorPtr3);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[3], tensorPtr4);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[4], tensorPtr5);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[5], tensorPtr6);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[6], tensorPtr4);
EXPECT_EQ(memsetV2ArgCtx.intAttrArray_->Size(), 4);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[0], 1);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[1], 2);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[2], 3);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[3], 4);
EXPECT_EQ(memsetV2ArgCtx.floatAttrArray_->Size(), 3);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[0], 1.1);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[1], 2.2);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[2], 3.3);
unique_executor.ReleaseTo(&executor);
delete executor;
delete tensorList1;
delete workspaceTensorList;
DestroyOpArgContext(ctx);
ReleaseHugeMem(nullptr, false);
UnInitHugeMemThreadLocal(nullptr, false);
}
static void MemSetV2OutputTensorWithDevPtr(op::internal::OpKernelBin* kernelBin)
{
OP_LOGI("support dev ptr");
PlatformInfoStub::GetInstance()->SetSoCVersion("Ascend950", "Ascend950DT_9591");
op::Shape selfShape{33, 15, 64};
op::Shape wsShape{32};
int addr[6] = {0};
aclTensor tensor1(selfShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, &addr[0]);
tensor1.SetFromWorkspace(false);
aclTensor* tensorPtr1 = &tensor1;
aclTensor tensor2(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[1]);
tensor2.SetFromWorkspace(false);
aclTensor* tensorPtr2 = &tensor2;
aclTensor tensor3(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[2]);
tensor3.SetFromWorkspace(false);
aclTensor* tensorPtr3 = &tensor3;
aclTensor tensor4(selfShape, op::DataType::DT_UINT32, op::Format::FORMAT_ND, &addr[3]);
tensor4.SetFromWorkspace(false);
aclTensor* tensorPtr4 = &tensor4;
aclTensor tensor5(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, &addr[4]);
tensor5.SetFromWorkspace(false);
aclTensor* tensorPtr5 = &tensor5;
aclTensor tensor6(wsShape, op::DataType::DT_FLOAT16, op::Format::FORMAT_ND, &addr[5]);
tensor6.SetFromWorkspace(false);
aclTensor* tensorPtr6 = &tensor6;
const aclTensor* tensorArr1[3] = {tensorPtr2, tensorPtr3, nullptr};
aclTensorList* tensorList1 = aclCreateTensorList(tensorArr1, 3);
auto input = OP_INPUT(tensorPtr1, tensorList1);
auto output = OP_OUTPUT(tensorPtr1, tensorList1, nullptr);
auto outshape = OP_OUTSHAPE(tensorPtr4, 0);
auto ctx = op::MakeOpArgContext(input, output, outshape);
const aclTensor* tensorsArr2[2] = {tensorPtr5, tensorPtr6};
aclTensorList* workspaceTensorList = aclCreateTensorList(tensorsArr2, 2);
EXPECT_EQ(ctx->ContainsOpArgType(OP_WORKSPACE_ARG), false);
ctx->AppendOpWorkspaceArg(workspaceTensorList);
EXPECT_EQ(ctx->ContainsOpArgType(OP_WORKSPACE_ARG), true);
kernelBin->memSetValue_ = {
{2, op::DataType::DT_FLOAT, 6.6f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{3, op::DataType::DT_INT32, 0.0f, 6, 100, 256, op::OpArgType::OPARG_ACLTENSOR_LIST, nullptr, nullptr, nullptr},
{4, op::DataType::DT_FLOAT16, 8.8f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR_LIST, nullptr, nullptr,
nullptr},
{5, op::DataType::DT_UINT32, 0.0f, 8, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr}};
auto unique_executor = CREATE_EXECUTOR();
aclOpExecutor* executor = unique_executor.get();
op::internal::GetThreadLocalContext().executor_ = executor;
aclrtStream stream = 0;
auto ret = kernelBin->MemsetOutputTensor(stream, ctx);
EXPECT_EQ(ret, ACLNN_SUCCESS);
EXPECT_EQ(kernelBin->memSetValueCtx_.size(), 4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].argIdx_, 2);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].tensor_, tensorPtr1);
EXPECT_EQ((kernelBin->memSetValueCtx_)[0].tensorList_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].argIdx_, 3);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].tensor_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[1].tensorList_, tensorList1);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].argIdx_, 4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].tensor_, nullptr);
EXPECT_EQ((kernelBin->memSetValueCtx_)[2].tensorList_, workspaceTensorList);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].argIdx_, 5);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].tensor_, tensorPtr4);
EXPECT_EQ((kernelBin->memSetValueCtx_)[3].tensorList_, nullptr);
MemsetV2ArgContext memsetV2ArgCtx;
ret = memsetV2ArgCtx.Init(kernelBin->memSetValueCtx_);
EXPECT_EQ(ret, ACLNN_SUCCESS);
op::OpArgContext* memsetV2OpArgCtx = memsetV2ArgCtx.GetMemsetV2OpArgContext();
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_INPUT_ARG), true);
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_OUTPUT_ARG), true);
EXPECT_EQ(memsetV2OpArgCtx->ContainsOpArgType(op::OP_WORKSPACE_ARG), true);
EXPECT_EQ(memsetV2ArgCtx.memsetTensors_->Size(), 6);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[0], tensorPtr1);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[1], tensorPtr2);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[2], tensorPtr3);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[3], tensorPtr5);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[4], tensorPtr6);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[5], tensorPtr4);
EXPECT_EQ(memsetV2ArgCtx.intAttrArray_->Size(), 3);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[0], 6);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[1], 6);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[2], 8);
EXPECT_EQ(memsetV2ArgCtx.floatAttrArray_->Size(), 3);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[0], 6.6);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[1], 8.8);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[2], 8.8);
unique_executor.ReleaseTo(&executor);
delete executor;
delete tensorList1;
delete workspaceTensorList;
DestroyOpArgContext(ctx);
}
static void MemSetV2OutputTensorWithDevPtr2(op::internal::OpKernelBin* kernelBin)
{
OP_LOGI("support dev ptr 2");
PlatformInfoStub::GetInstance()->SetSoCVersion("Ascend950", "Ascend950DT_9591");
op::Shape selfShape{33, 15, 64};
op::Shape wsShape{31, 32};
int addr[6] = {0};
aclTensor tensor1(selfShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, &addr[0]);
tensor1.SetFromWorkspace(false);
aclTensor* tensorPtr1 = &tensor1;
aclTensor tensor2(wsShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[1]);
tensor2.SetFromWorkspace(false);
aclTensor* tensorPtr2 = &tensor2;
aclTensor tensor3(wsShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, &addr[2]);
tensor3.SetFromWorkspace(false);
aclTensor* tensorPtr3 = &tensor3;
const aclTensor* tensorArr1[3] = {tensorPtr2, tensorPtr3, nullptr};
aclTensorList* tensorList1 = aclCreateTensorList(tensorArr1, 3);
kernelBin->memSetValueCtx_ = {
{2, op::DataType::DT_FLOAT, 6.6f, 0, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, tensorPtr1, nullptr},
{3, op::DataType::DT_FLOAT, 8.8f, 6, 100, 256, op::OpArgType::OPARG_ACLTENSOR, nullptr, nullptr, nullptr},
{4, op::DataType::DT_INT32, 0.0f, 6, 100, 256, op::OpArgType::OPARG_ACLTENSOR_LIST, nullptr, nullptr,
tensorList1},
{5, op::DataType::DT_INT32, 0.0f, 8, 100, 256, op::OpArgType::OPARG_ACLTENSOR_LIST, nullptr, nullptr, nullptr}};
auto unique_executor = CREATE_EXECUTOR();
aclOpExecutor* executor = unique_executor.get();
op::internal::GetThreadLocalContext().executor_ = executor;
MemsetV2ArgContext memsetV2ArgCtx;
auto ret = memsetV2ArgCtx.Init(kernelBin->memSetValueCtx_);
EXPECT_EQ(ret, ACLNN_SUCCESS);
op::OpArgContext* memsetV2OpArgCtx = memsetV2ArgCtx.GetMemsetV2OpArgContext();
EXPECT_EQ(memsetV2ArgCtx.memsetTensors_->Size(), 3);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[0], tensorPtr1);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[1], tensorPtr2);
EXPECT_EQ((*memsetV2ArgCtx.memsetTensors_)[2], tensorPtr3);
EXPECT_EQ(memsetV2ArgCtx.intAttrArray_->Size(), 2);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[0], 6);
EXPECT_EQ((*memsetV2ArgCtx.intAttrArray_)[1], 6);
EXPECT_EQ(memsetV2ArgCtx.floatAttrArray_->Size(), 1);
EXPECT_FLOAT_EQ((*memsetV2ArgCtx.floatAttrArray_)[0], 6.6);
unique_executor.ReleaseTo(&executor);
delete executor;
delete tensorList1;
}
TEST_F(KernelLaunchUT, MemSetV2LaunchTest)
{
auto* kernelBinWithDevPtr = CreateFakeOpKernelBin(true);
aclnnStatus ret = kernelBinWithDevPtr->JsonLoad();
auto* kernelBinNoDevPtr = CreateFakeOpKernelBin(false);
ret = kernelBinNoDevPtr->JsonLoad();
const uint64_t threadCount = 0;
vector<std::thread> threadVec;
for (uint64_t i = 0; i < threadCount; i++) {
threadVec.emplace_back(std::thread(MemSetV2OutputTensorWithDevPtr, kernelBinWithDevPtr));
threadVec.emplace_back(std::thread(MemSetV2OutputTensorWithDevPtr2, kernelBinWithDevPtr));
threadVec.emplace_back(std::thread(MemSetV2OutputTensorNoDevPtr, kernelBinNoDevPtr));
}
for (uint64_t i = 0; i < threadCount * 3; i++) {
threadVec[i].join();
}
for (auto& [key, value] : kernelBinWithDevPtr->tilingParseCtxHolder_) {
if (value.get()) {
value.get()->ReleaseTilingParse();
}
}
for (auto& [key, value] : kernelBinNoDevPtr->tilingParseCtxHolder_) {
if (value.get()) {
value.get()->ReleaseTilingParse();
}
}
delete kernelBinWithDevPtr;
delete kernelBinNoDevPtr;
}
TEST_F(KernelLaunchUT, KernelLaunchUT_Outshape)
{
op::Shape selfShape{33, 15, 64};
op::Shape outShape{33, 15, 64};
op::Shape idxShape{33, 15, 64};
op::Shape outShapeShape{4, 9};
op::Shape wsShape{64};
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto other = std::make_unique<aclTensor>(outShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto out = std::make_unique<aclTensor>(idxShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto ws = std::make_unique<aclTensor>(outShapeShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto outshape = std::make_unique<aclTensor>(outShapeShape, op::DataType::DT_INT32, op::Format::FORMAT_ND, nullptr);
auto input_arg = OP_INPUT(self.get(), other.get());
auto output_arg = OP_OUTPUT(out.get());
auto ws_arg = OP_WORKSPACE(ws.get());
auto outshape_arg = OP_OUTSHAPE({outshape.get(), 0});
auto attr_arg = OP_ATTR(123);
uint32_t opType = op::OpTypeDict::ToOpType("Axpy");
int dummyStream = 0;
void* stream = &dummyStream;
auto ctx = op::MakeOpArgContext(input_arg, output_arg, attr_arg, ws_arg, outshape_arg);
auto rc = op::internal::gKernelMgr.Run(opType, stream, ctx);
EXPECT_EQ(rc, ACL_SUCCESS);
}
TEST_F(KernelLaunchUT, GetAclTensorCountTerst1)
{
aclTensor* nullTensor = nullptr;
aclTensorList* nullTensorList = nullptr;
auto input_arg = OP_INPUT(nullTensor, nullTensorList);
auto ctx = op::MakeOpArgContext(input_arg);
size_t num = GetAclTensorCount(*(ctx->GetOpArg(op::OpArgDef::OP_INPUT_ARG)));
EXPECT_EQ(num, 0u);
}
TEST_F(KernelLaunchUT, SetMemSetFlagFromJsonTest)
{
const char* p = std::getenv("ASCEND_OPP_PATH");
EXPECT_NE(p, nullptr);
op::internal::KeyAndDetail key;
key.key = "hahaha";
size_t hashKey = 123;
constexpr size_t binNum = 4;
op::internal::OpKernelBin* bins[binNum];
for (size_t i = 1; i <= binNum; i++) {
char jsonPath[1024];
char binPath[1024];
snprintf_s(jsonPath, sizeof(jsonPath), sizeof(jsonPath),
"%s/built-in/op_impl/ai_core/tbe/kernel/ascend910/dummy/dummy_%zu.json", p, i);
snprintf_s(binPath, sizeof(binPath), sizeof(binPath),
"%s/built-in/op_impl/ai_core/tbe/kernel/ascend910/dummy/dummy_%zu.o", p, i);
op::internal::OpKernelBin* bin = new op::internal::OpKernelBin(
9999, jsonPath, jsonPath, binPath, key, hashKey, op::internal::BinType::DYNAMIC_BIN, false, false);
aclnnStatus rc = bin->JsonLoad();
EXPECT_EQ(rc, ACLNN_SUCCESS);
bins[i - 1] = bin;
}
EXPECT_EQ(bins[0]->memSetValue_.size(), 1);
EXPECT_EQ(bins[0]->memSetValue_[0].argIdx_, 3);
EXPECT_EQ(bins[0]->memSetValue_[0].dtype_, op::DataType::DT_FLOAT16);
EXPECT_EQ(bins[0]->memSetValue_[0].valueFloat_, 65504.0f);
EXPECT_EQ(bins[1]->memSetValue_.size(), 2);
EXPECT_EQ(bins[1]->memSetValue_[0].argIdx_, 3);
EXPECT_EQ(bins[1]->memSetValue_[0].dtype_, op::DataType::DT_FLOAT);
EXPECT_EQ(bins[1]->memSetValue_[0].valueFloat_, 65504.0f);
EXPECT_EQ(bins[1]->memSetValue_[1].argIdx_, 4);
EXPECT_EQ(bins[1]->memSetValue_[1].dtype_, op::DataType::DT_INT32);
EXPECT_EQ(bins[1]->memSetValue_[1].valueInt_, 655);
EXPECT_EQ(bins[2]->memSetValue_.size(), 2);
EXPECT_EQ(bins[2]->memSetValue_[0].argIdx_, 3);
EXPECT_EQ(bins[2]->memSetValue_[0].dtype_, op::DataType::DT_INT32);
EXPECT_EQ(bins[2]->memSetValue_[0].valueInt_, 655);
EXPECT_EQ(bins[2]->memSetValue_[1].argIdx_, 4);
EXPECT_EQ(bins[2]->memSetValue_[1].dtype_, op::DataType::DT_FLOAT);
EXPECT_EQ(bins[2]->memSetValue_[1].valueInt_, 0);
EXPECT_EQ(bins[3]->memSetValue_.size(), 2);
EXPECT_EQ(bins[3]->memSetValue_[0].argIdx_, 3);
EXPECT_EQ(bins[3]->memSetValue_[0].dtype_, op::DataType::DT_UINT32);
EXPECT_EQ(bins[3]->memSetValue_[0].valueInt_, 655);
EXPECT_EQ(bins[3]->memSetValue_[1].argIdx_, 4);
EXPECT_EQ(bins[3]->memSetValue_[1].dtype_, op::DataType::DT_FLOAT);
EXPECT_EQ(bins[3]->memSetValue_[1].valueFloat_, 65504.0f);
for (size_t i = 0; i < binNum; i++) {
delete bins[i];
}
}
TEST_F(KernelLaunchUT, RtsArgTest)
{
op::Shape selfShape{100};
op::Shape outShape{100};
aclOpExecutor exe;
int64_t inputData[100];
auto self = exe.AllocIntArray(inputData, 100);
auto out = exe.AllocTensor(outShape, op::DataType::DT_INT32);
auto inputTensor = exe.ConvertToTensor(self, op::DataType::DT_INT32);
auto input_arg = OP_INPUT(inputTensor);
auto output_arg = OP_OUTPUT(out);
op::internal::ExpandableRtsArgBuffer buffer;
buffer.Init(TEST_LAUNCH_ARG_INIT_CAP, TEST_TILING_HOST_DATA_INIT_CAP);
op::internal::TilingData* tilingData = buffer.GetTilingDataPtr();
tilingData->data_size_ = 60;
auto ctx = op::MakeOpArgContext(input_arg, output_arg);
op::internal::LaunchArgInfo argInfo(false, false, ctx);
op::internal::RtsArg arg(true, argInfo, &buffer);
arg.FillArgs();
op::internal::KernelLaunchConfig launchCfg;
launchCfg.funcHandle = (void*)0x12345678;
launchCfg.numBlocks = 32;
launchCfg.schemMode = 1;
launchCfg.dynUBufSize = 0;
launchCfg.blockDimOffset = 0;
launchCfg.engineType = op::internal::LaunchKernelEngineType::NO_VECTOR_CORE;
aclnnStatus rc = arg.LaunchKernel(nullptr, launchCfg);
EXPECT_EQ(rc, ACLNN_SUCCESS);
launchCfg.numBlocks = 32;
launchCfg.schemMode = 1;
launchCfg.dynUBufSize = 0;
launchCfg.blockDimOffset = 0;
launchCfg.engineType = op::internal::LaunchKernelEngineType::VECTOR_CORE_ENGINE_AIC;
rc = arg.LaunchKernel(nullptr, launchCfg);
EXPECT_EQ(rc, ACLNN_SUCCESS);
launchCfg.numBlocks = 7;
launchCfg.schemMode = 1;
launchCfg.dynUBufSize = 0;
launchCfg.blockDimOffset = 8;
launchCfg.engineType = op::internal::LaunchKernelEngineType::VECTOR_CORE_ENGINE_AIV;
rc = arg.LaunchKernel(nullptr, launchCfg);
EXPECT_EQ(rc, ACLNN_SUCCESS);
}
TEST_F(KernelLaunchUT, TestWithHandleTensorPtrList)
{
op::Shape selfShape{100};
op::Shape outShape{100};
aclOpExecutor exe;
int64_t inputData[100];
auto self = exe.AllocIntArray(inputData, 100);
auto out = exe.AllocTensor(outShape, op::DataType::DT_INT32);
auto inputTensor = exe.ConvertToTensor(self, op::DataType::DT_INT32);
auto inputTensor2 = exe.ConvertToTensor(self, op::DataType::DT_INT32);
const aclTensor* inputArr[] = {inputTensor, inputTensor2};
aclTensorList* inputTensors = aclCreateTensorList(inputArr, 2);
auto input_arg = OP_INPUT(inputTensors);
auto output_arg = OP_OUTPUT(out);
auto ctx = op::MakeOpArgContext(input_arg, output_arg);
op::internal::ExpandableRtsArgBuffer buffer;
buffer.Init(TEST_LAUNCH_ARG_INIT_CAP, TEST_TILING_HOST_DATA_INIT_CAP);
op::internal::TilingData* tilingData = buffer.GetTilingDataPtr();
tilingData->data_size_ = 60;
op::internal::LaunchArgInfo argInfo(false, true, ctx);
op::internal::RtsArg arg(true, argInfo, &buffer);
arg.FillArgs();
op::internal::KernelLaunchConfig launchCfg;
launchCfg.funcHandle = (void*)0x12345678;
launchCfg.numBlocks = 32;
launchCfg.schemMode = 1;
launchCfg.dynUBufSize = 0;
launchCfg.blockDimOffset = 0;
launchCfg.engineType = op::internal::LaunchKernelEngineType::VECTOR_CORE_ENGINE_AIC;
aclnnStatus rc = arg.LaunchKernel(nullptr, launchCfg);
delete inputTensors;
op::DestroyOpArgContext(ctx);
}
TEST_F(KernelLaunchUT, Launch1982Test)
{
setenv("ENABLE_1982", "1", 1);
PlatformInfoStub::GetInstance()->SetSoCVersion("Ascend910_93", "Ascend910_9391");
op::Shape selfShape{100};
op::Shape outShape{100};
aclOpExecutor exe;
int64_t inputData[100];
auto self = exe.AllocIntArray(inputData, 100);
auto out = exe.AllocTensor(outShape, op::DataType::DT_INT32);
auto inputTensor = exe.ConvertToTensor(self, op::DataType::DT_INT32);
auto input_arg = OP_INPUT(inputTensor);
auto output_arg = OP_OUTPUT(out);
auto ctx = op::MakeOpArgContext(input_arg, output_arg);
op::internal::ExpandableRtsArgBuffer buffer;
buffer.Init(TEST_LAUNCH_ARG_INIT_CAP, TEST_TILING_HOST_DATA_INIT_CAP);
op::internal::TilingData* tilingData = buffer.GetTilingDataPtr();
tilingData->data_size_ = 60;
op::internal::LaunchArgInfo argInfo(false, false, ctx);
op::internal::RtsArg arg(true, argInfo, &buffer);
arg.FillArgs();
op::internal::KernelLaunchConfig launchCfg;
launchCfg.funcHandle = (void*)0x12345678;
launchCfg.numBlocks = 32;
launchCfg.schemMode = 1;
launchCfg.dynUBufSize = 1;
launchCfg.blockDimOffset = 0;
launchCfg.engineType = op::internal::LaunchKernelEngineType::NO_VECTOR_CORE;
aclnnStatus rc = arg.LaunchKernel(nullptr, launchCfg);
op::DestroyOpArgContext(ctx);
PlatformInfoStub::GetInstance()->Reset();
unsetenv("ENABLE_1982");
}
class CaptureActiveStub : public AclrtStub {
public:
aclError aclmdlRICaptureGetInfo(aclrtStream stream, aclmdlRICaptureStatus* status, aclmdlRI* captureMdl) override
{
*status = ACL_MODEL_RI_CAPTURE_STATUS_ACTIVE;
return ACL_SUCCESS;
}
};
class CaptureGetInfoFailStub : public AclrtStub {
public:
aclError aclmdlRICaptureGetInfo(aclrtStream stream, aclmdlRICaptureStatus* status, aclmdlRI* captureMdl) override
{
return ACL_ERROR_FAILURE;
}
};
static void TestLaunchWithCaptureStub(AclrtStub* captureStub)
{
if (captureStub != nullptr) {
AclrtStub::GetInstance()->Install(captureStub);
}
op::Shape selfShape{33, 15, 1, 48};
op::Shape otherShape{33, 15, 14, 48};
op::Shape outShape{33, 15, 14, 48};
auto self = std::make_unique<aclTensor>(selfShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
auto other = std::make_unique<aclTensor>(otherShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
float alpha = 13.37;
auto out = std::make_unique<aclTensor>(outShape, op::DataType::DT_FLOAT, op::Format::FORMAT_ND, nullptr);
uint32_t opType = op::OpTypeDict::ToOpType("Axpy");
auto uniqueExecutor = CREATE_EXECUTOR();
aclOpExecutor* executor = uniqueExecutor.get();
thread_local uint64_t kernelLaunchIdDefinedInL0Dfx = op::internal::GenKernelLauncherId("Axpy");
op::internal::ProfilingInfoId profilingInfoId(0, kernelLaunchIdDefinedInL0Dfx, 0);
auto ctx = op::MakeOpArgContext(OP_INPUT(self.get(), other.get()), OP_OUTPUT(out.get()), OP_ATTR(alpha),
OP_WORKSPACE(out.get()));
auto launcher = new op::AiCoreKernelLauncher{opType, op::AI_CORE, profilingInfoId, executor, ctx};
auto rc = launcher->Launch();
EXPECT_EQ(rc, ACL_SUCCESS);
delete launcher;
if (captureStub != nullptr) {
AclrtStub::GetInstance()->UnInstall();
}
}
TEST_F(KernelLaunchUT, KernelLaunch_CaptureActive_SkipOverflow)
{
CaptureActiveStub captureStub;
TestLaunchWithCaptureStub(&captureStub);
}
TEST_F(KernelLaunchUT, KernelLaunch_CaptureNone_NormalOverflow) { TestLaunchWithCaptureStub(nullptr); }
TEST_F(KernelLaunchUT, KernelLaunch_CaptureGetInfoFail_NormalOverflow)
{
CaptureGetInfoFailStub failStub;
TestLaunchWithCaptureStub(&failStub);
}