forked from huawei/mindspore2022
90 lines
3.2 KiB
C++
90 lines
3.2 KiB
C++
/**
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* Copyright 2019 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 "session/cpu_session.h"
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#include <algorithm>
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#include "ir/meta_tensor.h"
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#include "ir/anf.h"
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#include "kernel/kernel.h"
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#include "common/utils.h"
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#include "session/anf_runtime_algorithm.h"
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#include "device/kernel_runtime.h"
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#include "predict/predict.h"
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#include "kernel/cpu/cpu_kernel_factory.h"
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#include "device/cpu/kernel_select_cpu.h"
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namespace mindspore {
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namespace session {
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GraphId CPUSession::CompileGraph(const AnfNodePtrList &lst, const AnfNodePtrList &outputs) {
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auto graph_id = graph_sum_;
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auto graph = ConstructKernelGraph(lst, outputs);
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MS_EXCEPTION_IF_NULL(graph);
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MS_LOG(INFO) << "Set kernel info";
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SetKernelInfo(graph.get());
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predictmodel::StepConvertGraph(graph);
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MS_LOG(INFO) << "Build kernel";
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BuildKernel(graph.get());
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MS_LOG(INFO) << "Assign kernel address";
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runtime_.AssignKernelAddress(graph.get());
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return graph_id;
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}
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void CPUSession::RunGraph(const GraphId &graph_id, const std::vector<tensor::TensorPtr> &inputs, VectorRef *outputs) {
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auto &kernel_graph = graphs_[graph_id];
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MS_EXCEPTION_IF_NULL(kernel_graph);
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MS_LOG(INFO) << "Bind input output address";
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runtime_.BindInputOutput(kernel_graph.get(), inputs, outputs);
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MS_LOG(INFO) << "Run graph start";
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predictmodel::StepConvertWeight(inputs);
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auto execution_order = kernel_graph->execution_order();
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Reorder(&execution_order);
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kernel_graph->set_execution_order(execution_order);
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bool ret = runtime_.Run(kernel_graph.get());
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if (!ret) {
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MS_LOG(EXCEPTION) << "Run graph failed";
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}
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MS_LOG(INFO) << "Run graph end";
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}
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void CPUSession::SetKernelInfo(const KernelGraph *kernel_graph) {
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MS_EXCEPTION_IF_NULL(kernel_graph);
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auto &kernel_nodes = kernel_graph->execution_order();
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for (const auto &kernel_node : kernel_nodes) {
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MS_EXCEPTION_IF_NULL(kernel_node);
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device::cpu::SetKernelInfo(kernel_node);
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}
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}
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void CPUSession::BuildKernel(const KernelGraph *kernel_graph) {
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MS_EXCEPTION_IF_NULL(kernel_graph);
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auto &kernel_nodes = kernel_graph->execution_order();
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for (const auto &kernel_node : kernel_nodes) {
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MS_EXCEPTION_IF_NULL(kernel_node);
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std::string kernel_name = AnfAlgo::GetCNodeName(kernel_node);
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MS_LOG(INFO) << "Cpu building operator[" << kernel_name << "].";
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std::shared_ptr<kernel::CPUKernel> cpu_kernel =
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kernel::CPUKernelFactory::GetInstance().Create(kernel_name, kernel_node);
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if (cpu_kernel == nullptr) {
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MS_LOG(EXCEPTION) << "Operator[" << kernel_name << "] is not support.";
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}
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cpu_kernel->Init(kernel_node);
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AnfAlgo::SetKernelMod(cpu_kernel, kernel_node.get());
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MS_LOG(INFO) << "Cpu build success operator[" << kernel_name << "].";
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}
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}
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} // namespace session
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} // namespace mindspore
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