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