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graphengine/tests/ut/ge/single_op/single_op_task_unittest.cc

117 lines
4.1 KiB

/**
* Copyright 2019-2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <gtest/gtest.h>
#include <vector>
#include "graph/load/model_manager/model_utils.h"
#include "graph/utils/graph_utils.h"
#include "runtime/rt.h"
#define protected public
#define private public
#include "single_op/single_op_model.h"
#include "single_op/task/tbe_task_builder.h"
#include "single_op/task/op_task.h"
#include "single_op/task/tbe_task_builder.h"
#include "external/register/op_tiling_registry.h"
#undef private
#undef protected
using namespace std;
using namespace testing;
using namespace ge;
using namespace optiling;
class UtestSingleOpTask : public testing::Test {
protected:
void SetUp() {}
void TearDown() {}
};
TEST_F(UtestSingleOpTask, test_build_kernel_task) {
string model_data_str = "123456789";
SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
model.input_offset_list_.push_back(0);
model.input_sizes_.push_back(16);
model.output_offset_list_.push_back(0);
model.output_sizes_.push_back(16);
auto graph = make_shared<ComputeGraph>("graph");
auto op_desc = make_shared<OpDesc>("Add", "Add");
std::vector<char> kernelBin;
TBEKernelPtr tbe_kernel = std::make_shared<ge::OpKernelBin>("name/Add", std::move(kernelBin));
op_desc->SetExtAttr(ge::OP_EXTATTR_NAME_TBE_KERNEL, tbe_kernel);
std::string kernel_name("kernel/Add");
AttrUtils::SetStr(op_desc, op_desc->GetName() + "_kernelname", kernel_name);
vector<int64_t> shape{16, 16};
GeShape ge_shape(shape);
GeTensorDesc desc(ge_shape);
op_desc->AddInputDesc(desc);
op_desc->AddOutputDesc(desc);
auto node = graph->AddNode(op_desc);
std::mutex stream_mu_;
rtStream_t stream_ = nullptr;
StreamResource stream_resource(0);
SingleOp single_op(&stream_resource, &stream_mu_, stream_);
domi::TaskDef task_def;
task_def.set_type(RT_MODEL_TASK_ALL_KERNEL);
domi::KernelDefWithHandle *kernel_with_handle = task_def.mutable_kernel_with_handle();
kernel_with_handle->set_original_kernel_key("");
kernel_with_handle->set_node_info("");
kernel_with_handle->set_block_dim(32);
kernel_with_handle->set_args_size(64);
string args(64, '1');
kernel_with_handle->set_args(args.data(), 64);
domi::KernelContext *context = kernel_with_handle->mutable_context();
context->set_op_index(1);
context->set_kernel_type(2); // ccKernelType::TE
uint16_t args_offset[9] = {0};
context->set_args_offset(args_offset, 9 * sizeof(uint16_t));
model.op_list_[1] = node;
TbeOpTask task_tmp;
TbeOpTask *task = &task_tmp;
ASSERT_EQ(model.BuildKernelTask(task_def, &task), SUCCESS);
vector<GeTensorDesc> input_desc;
vector<DataBuffer> input_buffers;
vector<GeTensorDesc> output_desc;
vector<DataBuffer> output_buffers;
task->node_ = node;
OpTilingFunc op_tiling_func = [](const TeOpParas &, const OpCompileInfo &, OpRunInfo &) -> bool {return true;};
OpTilingRegistryInterf("Add", op_tiling_func);
ge::AttrUtils::SetStr(op_desc, "compile_info_key", "op_compile_info_key");
ge::AttrUtils::SetStr(op_desc, "compile_info_json", "op_compile_info_json");
char c = '0';
char* buffer = &c;
task->tiling_buffer_ = buffer;
task->max_tiling_size_ = 64;
task->tiling_data_ = "tiling_data";
task->arg_size_ = 64;
uint8_t task_args{0};
task->args_.reset(&task_args);
ASSERT_EQ(task->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream_), SUCCESS);
char handle_tmp = '0';
char *handle = &handle_tmp;
task->SetHandle(handle);
ASSERT_EQ(task->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream_), SUCCESS);
}