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mindspore/mindspore/ccsrc/device/kernel_runtime.cc

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/**
* Copyright 2019 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 "device/kernel_runtime.h"
#include <utility>
#include <numeric>
#include <functional>
#include "common/utils.h"
#include "common/trans.h"
#include "utils/utils.h"
#include "utils/context/ms_context.h"
#include "operator/ops.h"
#include "pipeline/parse/python_adapter.h"
#include "session/kernel_graph.h"
#include "session/anf_runtime_algorithm.h"
#include "kernel/common_utils.h"
#include "kernel/oplib/oplib.h"
#include "ir/value.h"
using mindspore::kernel::Address;
using mindspore::kernel::AddressPtr;
namespace mindspore {
namespace device {
KernelRuntime::~KernelRuntime() {
#ifdef ENABLE_DUMP_E2E
dump_conf_ptr_ = nullptr;
#endif
}
bool KernelRuntime::Run(session::KernelGraph *graph) {
bool ret = false;
auto context_ptr = MsContext::GetInstance();
MS_EXCEPTION_IF_NULL(context_ptr);
#if defined(_WIN32) || defined(_WIN64)
auto start_time = std::chrono::steady_clock::now();
#else
struct timeval start_time, end_time;
(void)gettimeofday(&start_time, nullptr);
#endif
bool is_task_sink = context_ptr->enable_task_sink();
if (is_task_sink) {
ret = RunTask(graph);
} else {
ret = LaunchKernel(graph);
}
#if defined(_WIN32) || defined(_WIN64)
auto end_time = std::chrono::steady_clock::now();
std::chrono::duration<double, std::ratio<1, 1000000>> cost = end_time - start_time;
MS_LOG(INFO) << "Call MS Run Success in " << cost.count() << " us";
#else
(void)gettimeofday(&end_time, nullptr);
const uint64_t kUSecondInSecond = 1000000;
uint64_t cost = kUSecondInSecond * static_cast<uint64_t>(end_time.tv_sec - start_time.tv_sec);
cost += static_cast<uint64_t>(end_time.tv_usec - start_time.tv_usec);
MS_LOG(INFO) << "Call MS Run Success in " << cost << " us";
#endif
return ret;
}
// for D to impl
bool KernelRuntime::DumpData(mindspore::session::KernelGraph *graph) {
if (graph != nullptr) {
return true;
}
return false;
}
// for D to impl
bool KernelRuntime::GenTask(const session::KernelGraph *graph) {
if (graph != nullptr) {
return true;
}
return false;
}
bool KernelRuntime::LoadTask(const session::KernelGraph *graph) {
if (graph != nullptr) {
return true;
}
return false;
}
// for D to impl
bool KernelRuntime::RunTask(const session::KernelGraph *graph) {
if (graph != nullptr) {
return true;
}
return false;
}
size_t KernelRuntime::CountNodeDeviceMemorySize(const mindspore::AnfNodePtr &node, size_t output_index) {
MS_EXCEPTION_IF_NULL(node);
if (output_index >= AnfAlgo::GetOutputTensorNum(node)) {
MS_EXCEPTION(ArgumentError) << "output index [" << output_index << "] large than the output size ["
<< AnfAlgo::GetOutputTensorNum(node) << "] of node!";
}
TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(node, output_index);
if (output_type_id == kTypeUnknown) {
output_type_id = AnfAlgo::GetOutputInferDataType(node, output_index);
}
size_t type_size = GetTypeByte(TypeIdToType(output_type_id));
std::vector<size_t> shape = AnfAlgo::GetOutputDeviceShape(node, output_index);
auto format = AnfAlgo::GetOutputFormat(node, output_index);
if (shape.empty() && format != kOpFormat_DEFAULT) {
shape = trans::PaddingShapeTo4d(shape, AnfAlgo::GetOutputReshapeType(node, output_index));
shape = trans::TransShapeToDevice(shape, format);
}
// scalar's output shape is a empty vector
size_t tensor_size = std::accumulate(shape.begin(), shape.end(), type_size, std::multiplies<size_t>());
return tensor_size;
}
void KernelRuntime::AssignMemory(session::KernelGraph *graph) {
auto context_ptr = MsContext::GetInstance();
MS_EXCEPTION_IF_NULL(context_ptr);
MS_EXCEPTION_IF_NULL(mem_manager_);
mem_manager_->ResetDynamicMemory();
AssignStaticMemory(graph);
AssignDynamicMemory(graph);
UpdateRefNodeOutputMem(graph);
}
void KernelRuntime::RunOpAssignMemory(const std::vector<tensor::TensorPtr> &input_tensors,
session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
// assign memory for input nodes
RunOpAssignInputMemory(input_tensors, graph);
AssignStaticMemoryValueNode(graph);
for (const auto &cnode : graph->execution_order()) {
// assign memory for output nodes
RunOpAssignOutputMemory(cnode);
// assign memory for workspace
RunOpAssignWorkSpaceMemory(cnode);
}
UpdateRefNodeOutputMem(graph);
}
void KernelRuntime::AssignStaticMemory(session::KernelGraph *graph) {
AssignStaticMemoryInput(graph);
AssignStaticMemoryValueNode(graph);
AssignStaticMemoryOutput(graph);
}
void KernelRuntime::RunOpAssignInputMemory(const std::vector<tensor::TensorPtr> &input_tensors,
const session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
MS_EXCEPTION_IF_NULL(mem_manager_);
for (size_t input_index = 0; input_index < graph->inputs().size(); ++input_index) {
auto item = graph->inputs()[input_index];
MS_EXCEPTION_IF_NULL(item);
if (!item->isa<Parameter>()) {
continue;
}
auto output_size = AnfAlgo::GetOutputTensorNum(item);
for (size_t index = 0; index < output_size; index++) {
MS_EXCEPTION_IF_NULL(input_tensors[input_index]);
if (input_tensors[input_index]->device_address().get() != nullptr) {
AnfAlgo::SetOutputAddr(input_tensors[input_index]->device_address(), index, item.get());
continue;
}
TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
if (output_type_id == kTypeUnknown) {
output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
}
auto tensor_size = CountNodeDeviceMemorySize(item, index);
auto device_address =
CreateDeviceAddress(nullptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
MS_EXCEPTION_IF_NULL(device_address);
auto ret = mem_manager_->MallocMemFromMemPool(device_address, tensor_size);
if (!ret) {
MS_LOG(EXCEPTION) << "Malloc device memory failed.";
}
AnfAlgo::SetOutputAddr(device_address, index, item.get());
}
}
}
void KernelRuntime::RunOpAssignOutputMemory(const AnfNodePtr &kernel) {
MS_EXCEPTION_IF_NULL(kernel);
MS_EXCEPTION_IF_NULL(mem_manager_);
auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
MS_EXCEPTION_IF_NULL(kernel_mod);
auto output_sizes = kernel_mod->GetOutputSizeList();
if (output_sizes.empty()) {
return;
}
if (AnfAlgo::GetCNodeName(kernel) == "ApplyMomentum") {
auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, 0);
AnfAlgo::SetOutputAddr(device_address, 0, kernel.get());
AnfAlgo::SetOutputAddr(device_address, 1, kernel.get());
return;
}
for (size_t i = 0; i < output_sizes.size(); ++i) {
if (AnfAlgo::OutputAddrExist(kernel, i)) {
continue;
}
std::string output_format = AnfAlgo::GetOutputFormat(kernel, i);
auto output_type = AnfAlgo::GetOutputDeviceDataType(kernel, i);
auto device_address = CreateDeviceAddress(nullptr, output_sizes[i], output_format, output_type);
MS_EXCEPTION_IF_NULL(device_address);
auto ret = mem_manager_->MallocMemFromMemPool(device_address, output_sizes[i]);
if (!ret) {
MS_LOG(EXCEPTION) << "Malloc device memory failed.";
}
AnfAlgo::SetOutputAddr(device_address, i, kernel.get());
}
}
void KernelRuntime::RunOpAssignWorkSpaceMemory(const AnfNodePtr &kernel) {
MS_EXCEPTION_IF_NULL(kernel);
MS_EXCEPTION_IF_NULL(mem_manager_);
if (kernel->isa<CNode>()) {
auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
MS_EXCEPTION_IF_NULL(kernel_mod);
auto workspace_lists = kernel_mod->GetWorkspaceSizeList();
for (size_t i = 0; i < workspace_lists.size(); ++i) {
auto device_address = CreateDeviceAddress(nullptr, workspace_lists[i], "", kTypeUnknown);
MS_EXCEPTION_IF_NULL(device_address);
auto ret = mem_manager_->MallocMemFromMemPool(device_address, workspace_lists[i]);
if (!ret) {
MS_LOG(EXCEPTION) << "Malloc device memory failed.";
}
AnfAlgo::SetWorkspaceAddr(device_address, i, kernel.get());
}
}
}
void KernelRuntime::AssignStaticMemoryInput(const session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
MS_EXCEPTION_IF_NULL(mem_manager_);
for (auto &item : graph->inputs()) {
MS_EXCEPTION_IF_NULL(item);
if (!item->isa<Parameter>()) {
continue;
}
if (AnfAlgo::OutputAddrExist(item, 0)) {
continue;
}
auto output_size = AnfAlgo::GetOutputTensorNum(item);
for (size_t index = 0; index < output_size; index++) {
TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
// if graph output is a weight and doesn't link to any cnode, it's data type will be unknown
if (output_type_id == kTypeUnknown) {
MS_LOG(WARNING) << "It is not suggested to use a lonely weight parameter as the output of graph";
output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
}
auto tensor_size = CountNodeDeviceMemorySize(item, index);
auto ptr = mem_manager_->MallocMem(kStaticMem, tensor_size);
auto address = CreateDeviceAddress(ptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
AnfAlgo::SetOutputAddr(address, index, item.get());
}
}
}
void KernelRuntime::AssignStaticMemoryOutput(const session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
auto nodes = AnfAlgo::GetAllOutput(graph->output(), {prim::kPrimTupleGetItem});
for (const auto &node : nodes) {
auto item_with_index = AnfAlgo::VisitKernelWithReturnType(node, 0, true);
MS_EXCEPTION_IF_NULL(item_with_index.first);
if (!item_with_index.first->isa<CNode>() || !AnfAlgo::IsRealKernel(item_with_index.first)) {
continue;
}
AssignNodeOutputMem(kStaticMem, item_with_index.first, SizeToInt(item_with_index.second));
}
}
void KernelRuntime::UpdateRefNodeOutputMem(const session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
auto &kernels = graph->execution_order();
for (auto &kernel : kernels) {
MS_EXCEPTION_IF_NULL(kernel);
auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
MS_EXCEPTION_IF_NULL(kernel_mod);
auto output_sizes = kernel_mod->GetOutputSizeList();
if (output_sizes.empty()) {
MS_LOG(INFO) << "This kernel has no output size.";
continue;
}
for (size_t i = 0; i < output_sizes.size(); ++i) {
session::AnfWithOutIndex out_pair(kernel, i);
if (graph->IsInRefOutputMap(out_pair)) {
auto origin_pair = graph->GetRefCorrespondOutput(out_pair);
MS_EXCEPTION_IF_NULL(origin_pair.first);
auto origin_node_output_addr = AnfAlgo::GetMutableOutputAddr(origin_pair.first, origin_pair.second);
MS_EXCEPTION_IF_NULL(origin_node_output_addr);
auto cur_node_output_addr = AnfAlgo::GetMutableOutputAddr(kernel, i);
if (origin_node_output_addr.get() != cur_node_output_addr.get()) {
MS_LOG(INFO) << "REF address is not same, ref node output need address update";
MS_LOG(INFO) << "REF origin op is " << origin_pair.first->DebugString() << ", output index is "
<< origin_pair.second << ", cur op is " << kernel->DebugString() << ", out index is " << i;
AnfAlgo::SetOutputAddr(origin_node_output_addr, i, kernel.get());
}
}
}
}
}
void KernelRuntime::AssignCommunicationNodeOutputMem(int flag, 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);
auto output_sizes = kernel_mod->GetOutputSizeList();
if (output_sizes.empty()) {
MS_LOG(INFO) << "This kernel[" << node->DebugString() << "] has no output size.";
return;
}
auto context_ptr = MsContext::GetInstance();
MS_EXCEPTION_IF_NULL(context_ptr);
size_t total_size = 0;
std::vector<size_t> align_size_list;
for (uint64_t mem_size : output_sizes) {
if (context_ptr->enable_hccl()) {
mem_size = mem_manager_->GetCommonAlignSize(mem_size);
}
total_size += mem_size;
align_size_list.emplace_back(mem_size);
}
uint8_t *output_ptr = mem_manager_->MallocOutputMem(node, 0, flag, total_size);
for (size_t j = 0; j < align_size_list.size(); ++j) {
std::string output_format = AnfAlgo::GetOutputFormat(node, j);
auto output_type = AnfAlgo::GetOutputDeviceDataType(node, j);
auto address = CreateDeviceAddress(output_ptr, output_sizes[j], output_format, output_type);
AnfAlgo::SetOutputAddr(address, j, node.get());
output_ptr += align_size_list[j];
}
}
void KernelRuntime::UpdateCommunicationOpInputMem(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<mindspore::device::DeviceAddress *, size_t>> addr_size;
for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(node); ++i) {
auto address = AnfAlgo::GetPrevNodeMutableOutputAddr(node, i);
MS_EXCEPTION_IF_NULL(address);
auto mem_size = address->size();
if (context_ptr->enable_hccl()) {
mem_size = mem_manager_->GetCommonAlignSize(mem_size);
}
total_size += mem_size;
addr_size.emplace_back(address.get(), mem_size);
}
uint8_t *input_ptr = mem_manager_->MallocOutputMem(node, 0, kDynamicMem, total_size);
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(int flag, const AnfNodePtr &node, int index) {
MS_EXCEPTION_IF_NULL(node);
MS_EXCEPTION_IF_NULL(mem_manager_);
if (AnfAlgo::IsCommunicationOp(node)) {
UpdateCommunicationOpInputMem(node);
AssignCommunicationNodeOutputMem(flag, node);
return;
}
if (AnfAlgo::IsGetNext(NOT_NULL(node)) && flag == kReuseDynamicMem) {
MS_LOG(INFO) << "GetNext disable mem_reuse";
flag = 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 (AnfAlgo::OutputAddrExist(node, i)) {
MS_LOG(INFO) << "Already malloc index:" << i;
continue;
}
auto ptr = mem_manager_->MallocOutputMem(node, i, flag, output_sizes[i]);
if (ptr == nullptr) {
// reused ptr, no need alloc, continue;
continue;
}
std::string output_format = AnfAlgo::GetOutputFormat(node, i);
auto output_type = AnfAlgo::GetOutputDeviceDataType(node, i);
AnfAlgo::SetOutputAddr(CreateDeviceAddress(ptr, output_sizes[i], output_format, output_type), 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 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);
auto ptr = mem_manager_->MallocMem(kStaticMem, node_size);
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 address = CreateDeviceAddress(ptr, node_size, AnfAlgo::GetOutputFormat(value_node, output_idx), output_type_id);
MS_EXCEPTION_IF_NULL(address);
AnfAlgo::SetOutputAddr(address, output_idx, value_node.get());
if (!address->SyncHostToDevice(trans::GetRuntimePaddingShape(value_node, 0), tensor_size, tensor->data_type(),
tensor->data_c(false))) {
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_);
for (auto &value_node : graph->graph_value_nodes()) {
MS_EXCEPTION_IF_NULL(value_node);
if (AnfAlgo::OutputAddrExist(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();
auto ptr = mem_manager_->MallocMem(kStaticMem, tensor_size);
auto address = CreateDeviceAddress(ptr, tensor_size, kOpFormat_DEFAULT, kNumberTypeUInt8);
MS_EXCEPTION_IF_NULL(address);
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_flag = kDynamicMem;
if (is_enable_mem_reuse) {
mem_manager_->MallocReusedDynamicMem(graph);
mem_flag = kReuseDynamicMem;
}
auto &kernels = graph->execution_order();
for (auto &kernel : kernels) {
AssignNodeOutputMem(mem_flag, kernel, kGetAllOuts);
AssignWorkSpaceMem(mem_flag, kernel);
}
}
void KernelRuntime::AssignWorkSpaceMem(int flag, 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, flag, 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);
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.";
}
auto pre_node = cnode->inputs()[1];
// set clean output address
if (AnfAlgo::HasNodeAttr(kAttrAutomicOutputIndexs, pre_node)) {
auto clean_output_indexs = AnfAlgo::GetNodeAttr<std::vector<size_t>>(pre_node, kAttrAutomicOutputIndexs);
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(kAttrAutomicWorkspaceSize, pre_node)) {
auto clean_workspaces = AnfAlgo::GetNodeAttr<int>(pre_node, kAttrAutomicWorkspaceSize);
if (clean_workspaces != 0) {
auto device_address = AnfAlgo::GetWorkspaceAddr(pre_node, 0);
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);
}
MS_LOG(INFO) << "AtomicAddClean clean workspace size" << clean_workspaces;
}
}
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);
#if defined(_WIN32) || defined(_WIN64)
auto start_time = std::chrono::steady_clock::now();
#else
struct timeval start_time, end_time;
(void)gettimeofday(&start_time, nullptr);
#endif
auto ret =
kernel_mod->Launch(kernel_inputs, kernel_workspaces, kernel_outputs, reinterpret_cast<uintptr_t>(stream_));
if (!ret) {
MS_LOG(ERROR) << "Launch kernel failed.";
return false;
} else {
if (AnfAlgo::GetKernelType(kernel) == TBE_KERNEL && !SyncStream()) {
MS_LOG(EXCEPTION) << "SyncStream failed.";
}
#if defined(_WIN32) || defined(_WIN64)
auto end_time = std::chrono::steady_clock::now();
std::chrono::duration<double, std::ratio<1, 1000000>> cost = end_time - start_time;
MS_LOG(DEBUG) << "d " << kernel->fullname_with_scope() << " in " << cost.count() << " us";
#else
(void)gettimeofday(&end_time, nullptr);
const uint64_t kUSecondInSecond = 1000000;
uint64_t cost = kUSecondInSecond * static_cast<uint64_t>(end_time.tv_sec - start_time.tv_sec);
cost += static_cast<uint64_t>(end_time.tv_usec - start_time.tv_usec);
MS_LOG(DEBUG) << "d " << kernel->fullname_with_scope() << " in " << cost << " us";
#endif
}
}
return true;
}
bool KernelRuntime::LaunchKernel(const session::KernelGraph *graph) {
MS_EXCEPTION_IF_NULL(graph);
if (!LaunchKernelMod(*graph)) {
MS_LOG(ERROR) << "LaunchKernelMod failed!";
return false;
}
if (!SyncStream()) {
MS_LOG(ERROR) << "SyncStream 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
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