forked from huawei/mindspore2022
786 lines
30 KiB
C++
786 lines
30 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 "runtime/device/kernel_runtime.h"
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#include <vector>
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#include <utility>
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#include <numeric>
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#include <functional>
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#include "common/utils.h"
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#include "common/trans.h"
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#include "utils/utils.h"
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#include "utils/context/ms_context.h"
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#include "frontend/operator/ops.h"
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#include "pipeline/jit/parse/python_adapter.h"
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#include "backend/session/kernel_graph.h"
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#include "backend/session/anf_runtime_algorithm.h"
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#include "backend/kernel_compiler/common_utils.h"
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#include "backend/kernel_compiler/oplib/oplib.h"
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#include "ir/value.h"
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using mindspore::kernel::Address;
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using mindspore::kernel::AddressPtr;
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namespace mindspore {
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namespace device {
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KernelRuntime::~KernelRuntime() {
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#ifdef ENABLE_DUMP_E2E
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dump_conf_ptr_ = nullptr;
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#endif
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}
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bool KernelRuntime::Run(session::KernelGraph *graph) {
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bool ret = false;
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auto context_ptr = MsContext::GetInstance();
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MS_EXCEPTION_IF_NULL(context_ptr);
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#if defined(_WIN32) || defined(_WIN64)
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auto start_time = std::chrono::steady_clock::now();
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#else
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struct timeval start_time, end_time;
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(void)gettimeofday(&start_time, nullptr);
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#endif
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bool is_task_sink = context_ptr->enable_task_sink();
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if (is_task_sink) {
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ret = RunTask(graph);
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} else {
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ret = LaunchKernel(graph);
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}
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#if defined(_WIN32) || defined(_WIN64)
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auto end_time = std::chrono::steady_clock::now();
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std::chrono::duration<double, std::ratio<1, 1000000>> cost = end_time - start_time;
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MS_LOG(INFO) << "Call MS Run Success in " << cost.count() << " us";
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#else
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(void)gettimeofday(&end_time, nullptr);
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const uint64_t kUSecondInSecond = 1000000;
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uint64_t cost = kUSecondInSecond * static_cast<uint64_t>(end_time.tv_sec - start_time.tv_sec);
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cost += static_cast<uint64_t>(end_time.tv_usec - start_time.tv_usec);
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MS_LOG(INFO) << "Call MS Run Success in " << cost << " us";
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#endif
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return ret;
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}
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// for D to impl
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bool KernelRuntime::DumpData(mindspore::session::KernelGraph *graph) {
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if (graph != nullptr) {
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return true;
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}
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return false;
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}
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// for D to impl
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bool KernelRuntime::LoadData(mindspore::session::KernelGraph *graph, Debugger *debugger) {
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if (graph != nullptr) {
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return true;
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}
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return false;
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}
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// for D to impl
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bool KernelRuntime::GenTask(const session::KernelGraph *graph) {
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if (graph != nullptr) {
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return true;
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}
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return false;
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}
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bool KernelRuntime::LoadTask(const session::KernelGraph *graph) {
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if (graph != nullptr) {
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return true;
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}
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return false;
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}
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// for D to impl
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bool KernelRuntime::RunTask(const session::KernelGraph *graph) {
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if (graph != nullptr) {
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return true;
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}
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return false;
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}
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bool KernelRuntime::NodeOutputDeviceAddressExist(const AnfNodePtr &kernel, size_t index) {
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MS_EXCEPTION_IF_NULL(kernel);
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if (AnfAlgo::OutputAddrExist(kernel, index)) {
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return true;
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}
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return false;
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}
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size_t KernelRuntime::CountNodeDeviceMemorySize(const mindspore::AnfNodePtr &node, size_t output_index) {
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MS_EXCEPTION_IF_NULL(node);
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if (output_index >= AnfAlgo::GetOutputTensorNum(node)) {
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MS_EXCEPTION(ArgumentError) << "output index [" << output_index << "] large than the output size ["
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<< AnfAlgo::GetOutputTensorNum(node) << "] of node!";
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}
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TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(node, output_index);
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if (output_type_id == kTypeUnknown) {
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output_type_id = AnfAlgo::GetOutputInferDataType(node, output_index);
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}
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size_t type_size = GetTypeByte(TypeIdToType(output_type_id));
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std::vector<size_t> shape = AnfAlgo::GetOutputDeviceShape(node, output_index);
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auto format = AnfAlgo::GetOutputFormat(node, output_index);
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if (shape.empty() && format != kOpFormat_DEFAULT) {
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shape = trans::PaddingShapeTo4d(shape, AnfAlgo::GetOutputReshapeType(node, output_index));
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shape = trans::TransShapeToDevice(shape, format);
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}
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// scalar's output shape is a empty vector
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size_t tensor_size = std::accumulate(shape.begin(), shape.end(), type_size, std::multiplies<size_t>());
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return tensor_size;
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}
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void KernelRuntime::AssignMemory(session::KernelGraph *graph) {
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auto context_ptr = MsContext::GetInstance();
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MS_EXCEPTION_IF_NULL(context_ptr);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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mem_manager_->ResetDynamicMemory();
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AssignStaticMemory(graph);
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AssignDynamicMemory(graph);
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UpdateRefNodeOutputMem(graph);
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}
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void KernelRuntime::RunOpAssignMemory(const std::vector<tensor::TensorPtr> &input_tensors,
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session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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RunOpAssignInputMemory(input_tensors, graph);
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AssignStaticMemoryValueNode(graph);
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for (const auto &cnode : graph->execution_order()) {
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RunOpAssignOutputMemory(cnode);
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RunOpAssignWorkSpaceMemory(cnode);
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}
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UpdateRefNodeOutputMem(graph);
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}
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void KernelRuntime::RunOpClearMemory(const session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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// clear input parameter memory resource
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for (const auto &input_node : graph->inputs()) {
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MS_EXCEPTION_IF_NULL(input_node);
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AnfAlgo::SetOutputAddr(nullptr, 0, input_node.get());
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}
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// clear input value node memory resource
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for (const auto &value_node : graph->graph_value_nodes()) {
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MS_EXCEPTION_IF_NULL(value_node);
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AnfAlgo::SetOutputAddr(nullptr, 0, value_node.get());
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}
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for (const auto &cnode : graph->execution_order()) {
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MS_EXCEPTION_IF_NULL(cnode);
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// clear output memory resource
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for (size_t index = 0; index < AnfAlgo::GetOutputTensorNum(cnode); ++index) {
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AnfAlgo::SetOutputAddr(nullptr, index, cnode.get());
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}
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// clear workspace memory resource
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auto kernel_mod = AnfAlgo::GetKernelMod(cnode);
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MS_EXCEPTION_IF_NULL(kernel_mod);
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auto workspace_lists = kernel_mod->GetWorkspaceSizeList();
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for (size_t index = 0; index < workspace_lists.size(); ++index) {
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AnfAlgo::SetWorkspaceAddr(nullptr, index, cnode.get());
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}
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}
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}
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void KernelRuntime::AssignStaticMemory(session::KernelGraph *graph) {
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AssignStaticMemoryInput(graph);
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AssignStaticMemoryValueNode(graph);
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AssignStaticMemoryOutput(graph);
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}
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void KernelRuntime::RunOpAssignInputMemory(const std::vector<tensor::TensorPtr> &input_tensors,
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const session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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if (input_tensors.size() != graph->inputs().size()) {
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MS_LOG(EXCEPTION) << "Input tensors size " << input_tensors.size()
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<< " should be equal to graph input parameter size " << graph->inputs().size();
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}
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for (size_t input_index = 0; input_index < graph->inputs().size(); ++input_index) {
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auto item = graph->inputs()[input_index];
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MS_EXCEPTION_IF_NULL(item);
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if (!item->isa<Parameter>()) {
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continue;
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}
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auto output_size = AnfAlgo::GetOutputTensorNum(item);
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for (size_t index = 0; index < output_size; index++) {
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MS_EXCEPTION_IF_NULL(input_tensors[input_index]);
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auto output_address =
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std::dynamic_pointer_cast<device::DeviceAddress>(input_tensors[input_index]->device_address());
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if (output_address != nullptr) {
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AnfAlgo::SetOutputAddr(output_address, index, item.get());
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continue;
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}
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TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
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if (output_type_id == kTypeUnknown) {
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output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
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}
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auto tensor_size = CountNodeDeviceMemorySize(item, index);
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auto device_address =
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CreateDeviceAddress(nullptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
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MS_EXCEPTION_IF_NULL(device_address);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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auto ret = mem_manager_->MallocMemFromMemPool(device_address, tensor_size);
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if (!ret) {
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MS_LOG(EXCEPTION) << "Malloc device memory failed.";
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}
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AnfAlgo::SetOutputAddr(device_address, index, item.get());
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}
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}
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}
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void KernelRuntime::RunOpAssignOutputMemory(const AnfNodePtr &kernel) {
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MS_EXCEPTION_IF_NULL(kernel);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
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MS_EXCEPTION_IF_NULL(kernel_mod);
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auto output_sizes = kernel_mod->GetOutputSizeList();
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if (output_sizes.empty()) {
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return;
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}
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for (size_t i = 0; i < output_sizes.size(); ++i) {
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if (AnfAlgo::OutputAddrExist(kernel, i)) {
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continue;
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}
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if (AnfAlgo::GetCNodeName(kernel) == kApplyMomentumOpName) {
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auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i);
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AnfAlgo::SetOutputAddr(device_address, i, kernel.get());
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continue;
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}
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std::string output_format = AnfAlgo::GetOutputFormat(kernel, i);
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auto output_type = AnfAlgo::GetOutputDeviceDataType(kernel, i);
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auto device_address = CreateDeviceAddress(nullptr, output_sizes[i], output_format, output_type);
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device_address->set_host_shape(trans::GetRuntimePaddingShape(kernel, i));
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MS_EXCEPTION_IF_NULL(device_address);
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auto ret = mem_manager_->MallocMemFromMemPool(device_address, output_sizes[i]);
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if (!ret) {
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MS_LOG(EXCEPTION) << "Malloc device memory failed.";
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}
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AnfAlgo::SetOutputAddr(device_address, i, kernel.get());
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}
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}
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void KernelRuntime::RunOpAssignWorkSpaceMemory(const AnfNodePtr &kernel) {
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MS_EXCEPTION_IF_NULL(kernel);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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if (kernel->isa<CNode>()) {
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auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
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MS_EXCEPTION_IF_NULL(kernel_mod);
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auto workspace_lists = kernel_mod->GetWorkspaceSizeList();
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for (size_t i = 0; i < workspace_lists.size(); ++i) {
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auto device_address = CreateDeviceAddress(nullptr, workspace_lists[i], "", kTypeUnknown);
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MS_EXCEPTION_IF_NULL(device_address);
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auto ret = mem_manager_->MallocMemFromMemPool(device_address, workspace_lists[i]);
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if (!ret) {
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MS_LOG(EXCEPTION) << "Malloc device memory failed.";
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}
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AnfAlgo::SetWorkspaceAddr(device_address, i, kernel.get());
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}
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}
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}
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void KernelRuntime::AssignStaticMemoryInput(const session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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auto graph_inputs = graph->inputs();
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auto graph_valid_input = graph->valid_inputs();
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graph_inputs.insert(graph_inputs.end(), graph->child_graph_result().begin(), graph->child_graph_result().end());
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std::vector<AnfNodePtr> need_alloc_nodes;
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for (size_t i = 0; i < graph_inputs.size(); ++i) {
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auto item = graph_inputs[i];
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MS_EXCEPTION_IF_NULL(item);
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if (i < graph_valid_input.size() && !graph_valid_input[i]) {
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continue;
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}
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if (AnfAlgo::CheckPrimitiveType(item, prim::kPrimMakeTuple)) {
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auto outs = AnfAlgo::GetAllOutput(item);
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for (auto &out : outs) {
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MS_EXCEPTION_IF_NULL(out);
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if (!out->isa<Parameter>()) {
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continue;
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}
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if (NodeOutputDeviceAddressExist(out, 0)) {
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continue;
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}
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need_alloc_nodes.push_back(out);
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}
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}
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if (!item->isa<Parameter>()) {
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continue;
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}
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if (NodeOutputDeviceAddressExist(item, 0)) {
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continue;
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}
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need_alloc_nodes.push_back(item);
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}
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for (auto &item : need_alloc_nodes) {
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auto output_size = AnfAlgo::GetOutputTensorNum(item);
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for (size_t index = 0; index < output_size; index++) {
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TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
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// if graph output is a weight and doesn't link to any cnode, it's data type will be unknown
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if (output_type_id == kTypeUnknown) {
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MS_LOG(WARNING) << "It is not suggested to use a lonely weight parameter as the output of graph";
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output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
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}
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auto tensor_size = CountNodeDeviceMemorySize(item, index);
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auto address = CreateDeviceAddress(nullptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
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if (mem_manager_->MallocMem(address, kStaticMem, tensor_size) == nullptr) {
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MS_LOG(EXCEPTION) << "Cannot alloc address when flag is: " << kStaticMem << ", tensor size is: " << tensor_size;
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}
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AnfAlgo::SetOutputAddr(address, index, item.get());
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}
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}
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}
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void KernelRuntime::AssignStaticMemoryOutput(session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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auto nodes = AnfAlgo::GetAllOutput(graph->output(), {prim::kPrimTupleGetItem});
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std::vector<session::KernelWithIndex> non_communication_op;
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// Assign Communicate Op Memory firstly.
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for (const auto &node : nodes) {
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auto item_with_index = AnfAlgo::VisitKernelWithReturnType(node, 0, true);
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MS_EXCEPTION_IF_NULL(item_with_index.first);
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if (!item_with_index.first->isa<CNode>() || !AnfAlgo::IsRealKernel(item_with_index.first)) {
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continue;
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}
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if (AnfAlgo::IsCommunicationOp(item_with_index.first)) {
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AssignCommunicationNodeMem(kStaticMem, item_with_index.first);
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} else {
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non_communication_op.emplace_back(item_with_index);
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}
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}
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for (const auto &item_with_index : non_communication_op) {
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AssignNodeOutputMem(kStaticMem, item_with_index.first, SizeToInt(item_with_index.second));
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}
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}
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void KernelRuntime::UpdateRefNodeOutputMem(const session::KernelGraph *graph) {
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MS_EXCEPTION_IF_NULL(graph);
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auto &kernels = graph->execution_order();
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for (auto &kernel : kernels) {
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MS_EXCEPTION_IF_NULL(kernel);
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auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
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MS_EXCEPTION_IF_NULL(kernel_mod);
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auto output_sizes = kernel_mod->GetOutputSizeList();
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if (output_sizes.empty()) {
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MS_LOG(INFO) << "This kernel has no output size.";
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continue;
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}
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for (size_t i = 0; i < output_sizes.size(); ++i) {
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session::AnfWithOutIndex out_pair(kernel, i);
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if (graph->IsInRefOutputMap(out_pair)) {
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auto origin_pair = graph->GetRefCorrespondOutput(out_pair);
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MS_EXCEPTION_IF_NULL(origin_pair.first);
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auto origin_node_output_addr = AnfAlgo::GetMutableOutputAddr(origin_pair.first, origin_pair.second);
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MS_EXCEPTION_IF_NULL(origin_node_output_addr);
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auto cur_node_output_addr = AnfAlgo::GetMutableOutputAddr(kernel, i);
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if (origin_node_output_addr.get() != cur_node_output_addr.get()) {
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MS_LOG(INFO) << "REF address is not same, ref node output need address update";
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MS_LOG(INFO) << "REF origin op is " << origin_pair.first->DebugString() << ", output index is "
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<< origin_pair.second << ", cur op is " << kernel->DebugString() << ", out index is " << i;
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AnfAlgo::SetOutputAddr(origin_node_output_addr, i, kernel.get());
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}
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}
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}
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}
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}
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void KernelRuntime::AssignCommunicationNodeMem(MemType type, const AnfNodePtr &node) {
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AssignCommunicationNodeInputMem(type, node);
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AssignCommunicationNodeOutputMem(type, node);
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}
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void KernelRuntime::AssignCommunicationNodeOutputMem(MemType type, const AnfNodePtr &node) {
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MS_EXCEPTION_IF_NULL(node);
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MS_EXCEPTION_IF_NULL(mem_manager_);
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auto kernel_mod = AnfAlgo::GetKernelMod(node);
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MS_EXCEPTION_IF_NULL(kernel_mod);
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auto output_sizes = kernel_mod->GetOutputSizeList();
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if (output_sizes.empty()) {
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MS_LOG(INFO) << "This kernel[" << node->DebugString() << "] has no output size.";
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return;
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}
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auto context_ptr = MsContext::GetInstance();
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MS_EXCEPTION_IF_NULL(context_ptr);
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size_t total_size = 0;
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size_t output_index = 0;
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std::vector<size_t> align_size_list;
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for (uint64_t mem_size : output_sizes) {
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if (AnfAlgo::OutputAddrExist(node, output_index++)) {
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MS_LOG(INFO) << "communication op addr exist";
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continue;
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}
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if (context_ptr->enable_hccl()) {
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mem_size = mem_manager_->GetCommonAlignSize(mem_size);
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}
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total_size += mem_size;
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align_size_list.emplace_back(mem_size);
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}
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if (type == kReuseDynamicMem) {
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// reuse communication op's all outputs' memory
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type = kReuseDynamicCommMem;
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}
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uint8_t *output_ptr = nullptr;
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for (size_t j = 0; j < align_size_list.size(); ++j) {
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std::string output_format = AnfAlgo::GetOutputFormat(node, j);
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auto output_type = AnfAlgo::GetOutputDeviceDataType(node, j);
|
|
auto address = CreateDeviceAddress(nullptr, output_sizes[j], output_format, output_type);
|
|
MS_EXCEPTION_IF_NULL(address);
|
|
if (output_ptr == nullptr) {
|
|
output_ptr = mem_manager_->MallocMem(address, type, total_size, std::pair<AnfNodePtr, size_t>(node, 0));
|
|
MS_EXCEPTION_IF_NULL(output_ptr);
|
|
} else {
|
|
address->set_ptr(output_ptr);
|
|
}
|
|
AnfAlgo::SetOutputAddr(address, j, node.get());
|
|
output_ptr += align_size_list[j];
|
|
}
|
|
}
|
|
|
|
DeviceAddressPtr KernelRuntime::PreAssignCNodeMemory(const AnfNodePtr &anf_node, size_t index) {
|
|
MS_EXCEPTION_IF_NULL(anf_node);
|
|
auto kernel_mod = AnfAlgo::GetKernelMod(anf_node);
|
|
auto output_sizes = kernel_mod->GetOutputSizeList();
|
|
if (output_sizes.size() <= index) {
|
|
MS_LOG(EXCEPTION) << "Previous node output size < node index";
|
|
}
|
|
std::string output_format = AnfAlgo::GetOutputFormat(anf_node, index);
|
|
auto output_type = AnfAlgo::GetOutputDeviceDataType(anf_node, index);
|
|
auto address = CreateDeviceAddress(nullptr, output_sizes[index], output_format, output_type);
|
|
AnfAlgo::SetOutputAddr(address, index, anf_node.get());
|
|
return address;
|
|
}
|
|
|
|
void KernelRuntime::AssignCommunicationNodeInputMem(MemType type, const AnfNodePtr &node) {
|
|
auto context_ptr = MsContext::GetInstance();
|
|
MS_EXCEPTION_IF_NULL(context_ptr);
|
|
MS_EXCEPTION_IF_NULL(node);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
size_t total_size = 0;
|
|
std::vector<std::pair<DeviceAddressPtr, size_t>> addr_size;
|
|
for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(node); ++i) {
|
|
auto input_node_with_index = AnfAlgo::GetPrevNodeOutput(node, i);
|
|
auto input_node = input_node_with_index.first;
|
|
DeviceAddressPtr address = nullptr;
|
|
if (input_node->isa<CNode>()) {
|
|
address = PreAssignCNodeMemory(input_node, input_node_with_index.second);
|
|
} else {
|
|
MS_LOG(EXCEPTION) << "Communication node inputs only support CNode";
|
|
}
|
|
MS_EXCEPTION_IF_NULL(address);
|
|
auto mem_size = mem_manager_->GetCommonAlignSize(address->size());
|
|
total_size += mem_size;
|
|
addr_size.emplace_back(address, mem_size);
|
|
}
|
|
if (addr_size.empty()) {
|
|
return;
|
|
}
|
|
uint8_t *input_ptr =
|
|
mem_manager_->MallocMem(addr_size[0].first, type, total_size, std::pair<AnfNodePtr, size_t>(node, 0));
|
|
for (const auto &iter : addr_size) {
|
|
MS_EXCEPTION_IF_NULL(iter.first);
|
|
iter.first->set_ptr(input_ptr);
|
|
input_ptr += iter.second;
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::AssignNodeOutputMem(MemType type, const AnfNodePtr &node, int index) {
|
|
MS_EXCEPTION_IF_NULL(node);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
if (AnfAlgo::IsGetNext(NOT_NULL(node)) && type == kReuseDynamicMem) {
|
|
MS_LOG(INFO) << "GetNext disable mem_reuse";
|
|
type = kDynamicMem;
|
|
}
|
|
auto kernel_mod = AnfAlgo::GetKernelMod(node);
|
|
MS_EXCEPTION_IF_NULL(kernel_mod);
|
|
auto output_sizes = kernel_mod->GetOutputSizeList();
|
|
if (output_sizes.empty()) {
|
|
MS_LOG(INFO) << "This kernel[" << node->DebugString() << "] has no output size.";
|
|
return;
|
|
}
|
|
for (size_t i = 0; i < output_sizes.size(); ++i) {
|
|
if ((kGetAllOuts != index) && (SizeToInt(i) != index)) {
|
|
continue;
|
|
}
|
|
if (NodeOutputDeviceAddressExist(node, i)) {
|
|
MS_LOG(INFO) << "Already malloc index:" << i;
|
|
continue;
|
|
}
|
|
std::string output_format = AnfAlgo::GetOutputFormat(node, i);
|
|
auto output_type = AnfAlgo::GetOutputDeviceDataType(node, i);
|
|
auto device_address = CreateDeviceAddress(nullptr, output_sizes[i], output_format, output_type);
|
|
MS_EXCEPTION_IF_NULL(device_address);
|
|
uint8_t *ptr =
|
|
mem_manager_->MallocMem(device_address, type, output_sizes[i], std::pair<AnfNodePtr, size_t>(node, i));
|
|
MS_EXCEPTION_IF_NULL(ptr);
|
|
device_address->set_host_shape(trans::GetRuntimePaddingShape(node, i));
|
|
AnfAlgo::SetOutputAddr(device_address, i, node.get());
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::AssignValueNodeTensor(const ValueNodePtr &value_node, const ValuePtr &node_value,
|
|
size_t output_idx) {
|
|
MS_EXCEPTION_IF_NULL(value_node);
|
|
MS_EXCEPTION_IF_NULL(node_value);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
auto ms_context = MsContext::GetInstance();
|
|
MS_EXCEPTION_IF_NULL(ms_context);
|
|
auto tensor = node_value->cast<TensorPtr>();
|
|
if (tensor == nullptr) {
|
|
MS_LOG(WARNING) << "Tensor is null";
|
|
return;
|
|
}
|
|
size_t tensor_size = tensor->data().nbytes();
|
|
auto node_size = CountNodeDeviceMemorySize(value_node, output_idx);
|
|
TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(value_node, output_idx);
|
|
if (output_type_id == kTypeUnknown) {
|
|
output_type_id = AnfAlgo::GetOutputInferDataType(value_node, output_idx);
|
|
}
|
|
auto output_format = AnfAlgo::GetOutputFormat(value_node, output_idx);
|
|
DeviceAddressPtr address = nullptr;
|
|
address = CreateDeviceAddress(nullptr, node_size, output_format, output_type_id);
|
|
MS_EXCEPTION_IF_NULL(address);
|
|
if (ms_context->enable_pynative_infer() && !mem_manager_->MallocMemFromMemPool(address, node_size)) {
|
|
MS_LOG(EXCEPTION) << "Cannot alloc address from memory pool when tensor size is: " << node_size;
|
|
} else if (mem_manager_->MallocMem(address, kStaticMem, node_size) == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Cannot alloc address when flag is: " << kStaticMem << ", tensor size is: " << node_size;
|
|
}
|
|
AnfAlgo::SetOutputAddr(address, output_idx, value_node.get());
|
|
if (!address->SyncHostToDevice(trans::GetRuntimePaddingShape(value_node, 0), tensor_size, tensor->data_type(),
|
|
tensor->data_c())) {
|
|
MS_EXCEPTION(NotExistsError) << "ValueNode SyncHostToDevice fail!" << value_node->DebugString() << "node format is"
|
|
<< AnfAlgo::GetOutputFormat(value_node, output_idx) << "node dtype is "
|
|
<< AnfAlgo::GetOutputInferDataType(value_node, output_idx);
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::AssignStaticMemoryValueNode(session::KernelGraph *graph) {
|
|
MS_EXCEPTION_IF_NULL(graph);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
auto ms_context = MsContext::GetInstance();
|
|
MS_EXCEPTION_IF_NULL(ms_context);
|
|
for (auto &value_node : graph->graph_value_nodes()) {
|
|
MS_EXCEPTION_IF_NULL(value_node);
|
|
if (NodeOutputDeviceAddressExist(value_node, 0)) {
|
|
MS_LOG(INFO) << "value_node[" << value_node->DebugString() << "] address already exist";
|
|
continue;
|
|
}
|
|
auto &node_value = value_node->value();
|
|
MS_EXCEPTION_IF_NULL(node_value);
|
|
if (node_value->isa<Tensor>()) {
|
|
AssignValueNodeTensor(value_node, node_value, 0);
|
|
} else if (node_value->isa<StringImm>()) {
|
|
auto value = GetValue<std::string>(node_value);
|
|
size_t tensor_size = value.size();
|
|
DeviceAddressPtr address = nullptr;
|
|
address = CreateDeviceAddress(nullptr, tensor_size, kOpFormat_DEFAULT, kNumberTypeUInt8);
|
|
MS_EXCEPTION_IF_NULL(address);
|
|
if (ms_context->enable_pynative_infer() && !mem_manager_->MallocMemFromMemPool(address, tensor_size)) {
|
|
MS_LOG(EXCEPTION) << "Cannot alloc address from memory pool when tensor size is: " << tensor_size;
|
|
} else if (mem_manager_->MallocMem(address, kStaticMem, tensor_size) == nullptr) {
|
|
MS_LOG(EXCEPTION) << "Cannot alloc address when flag is: " << kStaticMem << ", tensor size is: " << tensor_size;
|
|
}
|
|
AnfAlgo::SetOutputAddr(address, 0, value_node.get());
|
|
std::vector<int> shape = {1, SizeToInt(tensor_size)};
|
|
if (!address->SyncHostToDevice(shape, tensor_size, kNumberTypeUInt8, value.data())) {
|
|
MS_LOG(EXCEPTION) << "kValueNode SyncHostToDevice fail!";
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::AssignDynamicMemory(session::KernelGraph *graph) {
|
|
MS_EXCEPTION_IF_NULL(graph);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
auto context_ptr = MsContext::GetInstance();
|
|
MS_EXCEPTION_IF_NULL(context_ptr);
|
|
bool is_enable_mem_reuse = context_ptr->enable_mem_reuse();
|
|
auto mem_type = kDynamicMem;
|
|
if (is_enable_mem_reuse) {
|
|
mem_manager_->MallocReusedDynamicMem(graph);
|
|
mem_type = kReuseDynamicMem;
|
|
}
|
|
auto &execution_nodes = graph->execution_order();
|
|
std::vector<CNodePtr> compute_nodes;
|
|
// communication nodes first
|
|
for (auto &node : execution_nodes) {
|
|
if (AnfAlgo::IsCommunicationOp(node)) {
|
|
// skip if the memory is already alocated
|
|
AssignCommunicationNodeMem(mem_type, node);
|
|
} else {
|
|
compute_nodes.emplace_back(node);
|
|
}
|
|
}
|
|
|
|
// then compute nodes
|
|
for (auto &node : compute_nodes) {
|
|
AssignNodeOutputMem(mem_type, node, kGetAllOuts);
|
|
AssignWorkSpaceMem(mem_type, node);
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::AssignWorkSpaceMem(MemType type, const AnfNodePtr &node) {
|
|
MS_EXCEPTION_IF_NULL(node);
|
|
MS_EXCEPTION_IF_NULL(mem_manager_);
|
|
auto kernel_mod = AnfAlgo::GetKernelMod(node);
|
|
MS_EXCEPTION_IF_NULL(kernel_mod);
|
|
size_t index = 0;
|
|
for (auto &size : kernel_mod->GetWorkspaceSizeList()) {
|
|
auto ptr = mem_manager_->MallocWorkSpaceMem(node, index, type, size);
|
|
AnfAlgo::SetWorkspaceAddr(CreateDeviceAddress(ptr, size, "", kTypeUnknown), index, node.get());
|
|
index++;
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::GenLaunchArgs(const mindspore::kernel::KernelMod &kernel_mod, const mindspore::AnfNodePtr &kernel,
|
|
AddressPtrList *kernel_inputs, AddressPtrList *const kernel_workspaces,
|
|
AddressPtrList *kernel_outputs) {
|
|
MS_EXCEPTION_IF_NULL(kernel);
|
|
MS_EXCEPTION_IF_NULL(kernel_inputs);
|
|
MS_EXCEPTION_IF_NULL(kernel_workspaces);
|
|
MS_EXCEPTION_IF_NULL(kernel_outputs);
|
|
auto cnode = kernel->cast<CNodePtr>();
|
|
MS_EXCEPTION_IF_NULL(cnode);
|
|
if (AnfAlgo::GetCNodeName(cnode) == kAtomicAddrCleanOpName) {
|
|
return GenAddrCleanLaunchArgs(cnode, kernel_inputs);
|
|
}
|
|
for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(kernel); ++i) {
|
|
auto real_input = AnfAlgo::GetRealInputIndex(kernel, i);
|
|
auto device_address = AnfAlgo::GetPrevNodeOutputAddr(kernel, real_input);
|
|
MS_EXCEPTION_IF_NULL(device_address);
|
|
kernel::AddressPtr input = std::make_shared<kernel::Address>();
|
|
MS_EXCEPTION_IF_NULL(input);
|
|
input->addr = device_address->ptr_;
|
|
MS_EXCEPTION_IF_NULL(input->addr);
|
|
input->size = device_address->size_;
|
|
kernel_inputs->emplace_back(input);
|
|
}
|
|
|
|
for (size_t i = 0; i < kernel_mod.GetOutputSizeList().size(); ++i) {
|
|
auto device_address = AnfAlgo::GetOutputAddr(kernel, i);
|
|
kernel::AddressPtr output = std::make_shared<kernel::Address>();
|
|
MS_EXCEPTION_IF_NULL(output);
|
|
output->addr = device_address->ptr_;
|
|
MS_EXCEPTION_IF_NULL(output->addr);
|
|
output->size = device_address->size_;
|
|
kernel_outputs->emplace_back(output);
|
|
}
|
|
|
|
for (size_t i = 0; i < kernel_mod.GetWorkspaceSizeList().size(); ++i) {
|
|
auto device_address = AnfAlgo::GetWorkspaceAddr(kernel, i);
|
|
kernel::AddressPtr workspace = std::make_shared<kernel::Address>();
|
|
MS_EXCEPTION_IF_NULL(workspace);
|
|
workspace->addr = device_address->ptr_;
|
|
MS_EXCEPTION_IF_NULL(workspace->addr);
|
|
workspace->size = device_address->size_;
|
|
kernel_workspaces->emplace_back(workspace);
|
|
}
|
|
}
|
|
|
|
void KernelRuntime::GenAddrCleanLaunchArgs(const CNodePtr &cnode, AddressPtrList *kernel_inputs) {
|
|
if (cnode->inputs().size() != 2) {
|
|
MS_LOG(EXCEPTION) << "Atomic Addr clean Node Input nodes not equal 2.";
|
|
}
|
|
MS_EXCEPTION_IF_NULL(cnode->inputs()[1]);
|
|
auto pre_node = (cnode->inputs()[1])->cast<CNodePtr>();
|
|
// set clean output address
|
|
if (AnfAlgo::HasNodeAttr(kAttrAtomicOutputIndexs, pre_node)) {
|
|
auto clean_output_indexs = AnfAlgo::GetNodeAttr<std::vector<size_t>>(pre_node, kAttrAtomicOutputIndexs);
|
|
for (auto index : clean_output_indexs) {
|
|
auto device_address = AnfAlgo::GetOutputAddr(pre_node, index);
|
|
kernel::AddressPtr input = std::make_shared<kernel::Address>();
|
|
MS_EXCEPTION_IF_NULL(input);
|
|
input->addr = device_address->ptr_;
|
|
MS_EXCEPTION_IF_NULL(input->addr);
|
|
input->size = device_address->size_;
|
|
kernel_inputs->emplace_back(input);
|
|
}
|
|
MS_LOG(INFO) << "AtomicAddClean clean output size:" << clean_output_indexs.size();
|
|
}
|
|
// set clean workspace address
|
|
if (AnfAlgo::HasNodeAttr(kAttrAtomicWorkspaceIndexs, pre_node)) {
|
|
auto clean_workspaces_indexs = AnfAlgo::GetNodeAttr<std::vector<size_t>>(pre_node, kAttrAtomicWorkspaceIndexs);
|
|
for (const auto &index : clean_workspaces_indexs) {
|
|
auto device_address = AnfAlgo::GetWorkspaceAddr(pre_node, index);
|
|
kernel::AddressPtr workspace = std::make_shared<kernel::Address>();
|
|
MS_EXCEPTION_IF_NULL(workspace);
|
|
workspace->addr = device_address->ptr_;
|
|
MS_EXCEPTION_IF_NULL(workspace->addr);
|
|
workspace->size = device_address->size_;
|
|
kernel_inputs->emplace_back(workspace);
|
|
}
|
|
}
|
|
}
|
|
|
|
bool KernelRuntime::LaunchKernelMod(const session::KernelGraph &graph) {
|
|
auto &kernels = graph.execution_order();
|
|
for (const auto &kernel : kernels) {
|
|
auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
|
|
MS_EXCEPTION_IF_NULL(kernel_mod);
|
|
|
|
AddressPtrList kernel_inputs;
|
|
AddressPtrList kernel_workspaces;
|
|
AddressPtrList kernel_outputs;
|
|
GenLaunchArgs(*kernel_mod, kernel, &kernel_inputs, &kernel_workspaces, &kernel_outputs);
|
|
auto ret = kernel_mod->Launch(kernel_inputs, kernel_workspaces, kernel_outputs, stream_);
|
|
if (!ret) {
|
|
MS_LOG(ERROR) << "Launch kernel failed.";
|
|
return false;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool KernelRuntime::LaunchKernel(const session::KernelGraph *graph) {
|
|
MS_EXCEPTION_IF_NULL(graph);
|
|
if (!LaunchKernelMod(*graph)) {
|
|
MS_LOG(ERROR) << "LaunchKernelMod failed!";
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
void KernelRuntime::ClearGraphRuntimeResource(uint32_t graph_id) {
|
|
MS_LOG(INFO) << "Clear graph:" << graph_id << " runtime resource";
|
|
}
|
|
|
|
bool KernelRuntime::LaunchTaskBasedOnSingleKernel(kernel::KernelModPtr kernel_mod_ptr, AddressPtrList kernel_inputs,
|
|
AddressPtrList kernel_outputs,
|
|
AddressPtrList kernel_workspaces) const {
|
|
MS_EXCEPTION_IF_NULL(kernel_mod_ptr);
|
|
auto ret = kernel_mod_ptr->Launch(kernel_inputs, kernel_workspaces, kernel_outputs, stream_);
|
|
if (!ret) {
|
|
MS_LOG(ERROR) << "Launch kernel failed.";
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
#ifdef ENABLE_DUMP_E2E
|
|
bool KernelRuntime::SetDumpConf() {
|
|
dump_conf_ptr_ = std::make_shared<Dump>();
|
|
MS_EXCEPTION_IF_NULL(dump_conf_ptr_);
|
|
bool ret = dump_conf_ptr_->SetDumpConfFromJsonFile();
|
|
return ret;
|
|
}
|
|
|
|
DumpConfPtr KernelRuntime::GetDumpConf() { return dump_conf_ptr_; }
|
|
#endif
|
|
} // namespace device
|
|
} // namespace mindspore
|