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graphengine/ge/single_op/task/op_task.cc

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/**
* Copyright 2019-2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "single_op/task/op_task.h"
#include <google/protobuf/extension_set.h>
#include <chrono>
#include <thread>
#include "aicpu/common/aicpu_task_struct.h"
#include "common/dump/dump_manager.h"
#include "common/dump/dump_op.h"
#include "common/profiling/profiling_manager.h"
#include "common/formats/formats.h"
#include "common/math/math_util.h"
#include "framework/common/debug/log.h"
#include "register/op_tiling.h"
#include "runtime/rt.h"
#include "build_task_utils.h"
namespace ge {
namespace {
constexpr int kLaunchRetryTimes = 1000;
constexpr int kSleepTime = 10;
constexpr uint64_t kReleaseFlag = 1;
constexpr int kCopyNum = 2;
constexpr uint64_t kInferSessionId = 0;
void FreeHbm(void *var) {
if (var) {
(void)rtFree(var);
}
}
} // namespace
Status OpTask::OpenDump(rtStream_t stream) {
if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
GELOGI("Dump is open in single op, start to set dump info");
std::vector<uint64_t> input_addrs;
std::vector<uint64_t> output_adds;
auto input_size = op_desc_->GetInputsSize();
auto output_size = op_desc_->GetOutputsSize();
uintptr_t *arg_base = nullptr;
size_t arg_num = 0;
GetIoAddr(arg_base, arg_num);
if (arg_num < input_size + output_size) {
GELOGE(ACL_ERROR_GE_INTERNAL_ERROR,
"[Check][Size]io_addrs_for_dump_ size %zu is not equal input and output size %zu",
arg_num, input_size + output_size);
REPORT_INNER_ERROR("E19999", "io_addrs_for_dump_ size %zu is not equal input and output size %zu",
arg_num, input_size + output_size);
return ACL_ERROR_GE_INTERNAL_ERROR;
}
for (size_t i = 0; i < input_size; i++) {
uint64_t input_addr = arg_base[i];
input_addrs.emplace_back(input_addr);
}
for (size_t j = 0; j < output_size; j++) {
uint64_t output_addr = arg_base[input_size + j];
output_adds.emplace_back(output_addr);
}
dump_op_.SetDumpInfo(DumpManager::GetInstance().GetDumpProperties(kInferSessionId),
op_desc_, input_addrs, output_adds, stream);
auto status = dump_op_.LaunchDumpOp();
if (status != SUCCESS) {
GELOGE(status, "[Launch][DumpOp] failed in single op.");
return status;
}
return SUCCESS;
}
GELOGI("Dump is not open in single op");
return SUCCESS;
}
void TbeOpTask::SetStubFunc(const std::string &name, const void *stub_func) {
this->stub_name_ = name;
this->stub_func_ = stub_func;
}
void TbeOpTask::SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
const OpDescPtr &op_desc) {
args_ = std::move(args);
arg_size_ = arg_size;
block_dim_ = block_dim;
op_desc_ = op_desc;
}
void TbeOpTask::SetKernelWithHandleArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
const OpDescPtr &op_desc,
const domi::KernelDefWithHandle &kernel_def_with_handle) {
SetKernelArgs(std::move(args), arg_size, block_dim, op_desc);
original_kernel_key_ = kernel_def_with_handle.original_kernel_key();
node_info_ = kernel_def_with_handle.node_info();
}
void TbeOpTask::SetSmDesc(void *sm_desc) { sm_desc_ = sm_desc; }
void OpTask::SetModelArgs(std::string model_name, uint32_t model_id) {
model_name_ = model_name;
model_id_ = model_id;
}
Status OpTask::GetProfilingArgs(TaskDescInfo &task_desc_info, uint32_t &model_id) {
uint32_t task_id = 0;
uint32_t stream_id = 0;
auto rt_ret = rtGetTaskIdAndStreamID(&task_id, &stream_id);
if (rt_ret != RT_ERROR_NONE) {
GELOGE(RT_FAILED, "[Get][TaskIdAndStreamID] failed, ret: 0x%X.", rt_ret);
REPORT_CALL_ERROR("E19999", "rtGetTaskIdAndStreamID failed, ret: 0x%X.", rt_ret);
return RT_ERROR_TO_GE_STATUS(rt_ret);
}
GE_CHECK_NOTNULL(op_desc_);
string op_name = op_desc_->GetName();
GELOGD("Get profiling args of op [%s] end, task_id[%u], stream_id[%u].", op_name.c_str(), task_id, stream_id);
model_id = model_id_;
task_desc_info.model_name = model_name_;
task_desc_info.block_dim = block_dim_;
task_desc_info.task_id = task_id;
task_desc_info.stream_id = stream_id;
task_desc_info.op_name = op_name;
task_desc_info.op_type = op_desc_->GetType();
auto &prof_mgr = ProfilingManager::Instance();
prof_mgr.GetOpInputOutputInfo(op_desc_, task_desc_info);
return SUCCESS;
}
Status OpTask::UpdateRunInfo() {
return UNSUPPORTED;
}
Status OpTask::DoUpdateArgTable(const SingleOpModelParam &param, bool keep_workspace) {
auto addresses = BuildTaskUtils::GetAddresses(op_desc_, param, keep_workspace);
auto all_addresses = BuildTaskUtils::JoinAddresses(addresses);
uintptr_t *arg_base = nullptr;
size_t arg_num = 0;
GetIoAddr(arg_base, arg_num);
if (arg_num < all_addresses.size()) {
GELOGE(ACL_ERROR_GE_INTERNAL_ERROR,
"[Check][Size][%s] arg number mismatches, expect at least = %zu, but got = %zu.",
op_desc_->GetName().c_str(), all_addresses.size(), arg_num);
REPORT_INNER_ERROR("E19999", "%s arg number mismatches, expect at least = %zu, but got = %zu.",
op_desc_->GetName().c_str(), all_addresses.size(), arg_num);
return ACL_ERROR_GE_INTERNAL_ERROR;
}
for (void *addr : all_addresses) {
*arg_base++ = reinterpret_cast<uintptr_t >(addr);
}
return SUCCESS;
}
Status OpTask::UpdateArgTable(const SingleOpModelParam &param) {
return DoUpdateArgTable(param, true);
}
Status OpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
const vector<DataBuffer> &input_buffers,
vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &output_buffers,
rtStream_t stream) {
return UNSUPPORTED;
}
const std::string &OpTask::GetTaskType() const { return kTaskTypeInvalid; }
TbeOpTask::~TbeOpTask() {
if (sm_desc_ != nullptr) {
(void)rtMemFreeManaged(sm_desc_);
}
if (tiling_buffer_ != nullptr) {
(void)rtFree(tiling_buffer_);
}
}
const void *TbeOpTask::GetArgs() const { return args_.get(); }
size_t TbeOpTask::GetArgSize() const { return arg_size_; }
const std::string &TbeOpTask::GetStubName() const { return stub_name_; }
const std::string &TbeOpTask::GetTaskType() const { return kTaskTypeAicore; }
void TbeOpTask::SetHandle(void *handle) {
this->handle_ = handle;
}
Status TbeOpTask::LaunchKernel(rtStream_t stream) {
GELOGD("To invoke rtKernelLaunch. task = %s, block_dim = %u", this->stub_name_.c_str(), block_dim_);
auto ret = DoLaunchKernel(stream);
int retry_times = 0;
while (ret != RT_ERROR_NONE && retry_times < kLaunchRetryTimes) {
retry_times++;
GELOGW("Retry after %d ms, retry_times: %d", kSleepTime, retry_times);
std::this_thread::sleep_for(std::chrono::milliseconds(kSleepTime));
ret = DoLaunchKernel(stream);
}
if (ret != RT_ERROR_NONE) {
GELOGE(ret, "[Invoke][RtKernelLaunch] failed. ret = %d, task = %s", ret, this->stub_name_.c_str());
REPORT_INNER_ERROR("E19999", "invoke rtKernelLaunch failed, ret = %d, task = %s", ret, this->stub_name_.c_str());
return RT_ERROR_TO_GE_STATUS(ret);
}
GELOGI("[TASK_INFO] %s", this->stub_name_.c_str());
return SUCCESS;
}
Status TbeOpTask::UpdateRunInfo() {
// invoke OpParaCalculate
GELOGD("Start to invoke OpParaCalculate.");
optiling::OpRunInfo run_info;
run_info.block_dim = 0;
auto ret = optiling::OpParaCalculate(*node_, run_info);
if (ret != GRAPH_SUCCESS) {
GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Invoke][OpParaCalculate] failed, ret = %u.", ret);
REPORT_INNER_ERROR("E19999", "invoke OpParaCalculate failed, ret = %u.", ret);
return ACL_ERROR_GE_INTERNAL_ERROR;
}
block_dim_ = run_info.block_dim;
tiling_data_ = run_info.tiling_data.str();
tiling_key_ = run_info.tiling_key;
run_info_workspaces_ = run_info.workspaces;
GELOGD("Done invoking OpParaCalculate successfully. block_dim = %u, tiling size = %zu, tiling_key = %u", block_dim_,
tiling_data_.size(), tiling_key_);
return SUCCESS;
}
Status TbeOpTask::UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor) {
int64_t storage_format_val = static_cast<Format>(FORMAT_RESERVED);
(void)AttrUtils::GetInt(src_tensor, ge::ATTR_NAME_STORAGE_FORMAT, storage_format_val);
auto storage_format = static_cast<Format>(storage_format_val);
if (storage_format == FORMAT_RESERVED) {
GELOGD("Storage format not set. update shape to [%s], and original shape to [%s]",
src_tensor.GetShape().ToString().c_str(), src_tensor.GetOriginShape().ToString().c_str());
dst_tensor.SetShape(src_tensor.GetShape());
dst_tensor.SetOriginShape(src_tensor.GetOriginShape());
} else {
std::vector<int64_t> storage_shape;
if (!AttrUtils::GetListInt(src_tensor, ge::ATTR_NAME_STORAGE_SHAPE, storage_shape)) {
GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Get][ListInt]failed while storage_format was set.");
return ACL_ERROR_GE_INTERNAL_ERROR;
}
GELOGD("Storage format set. update shape to [%s], and original shape to [%s]",
GeShape(storage_shape).ToString().c_str(), src_tensor.GetShape().ToString().c_str());
dst_tensor.SetShape(GeShape(std::move(storage_shape)));
dst_tensor.SetOriginShape(src_tensor.GetShape());
}
return SUCCESS;
}
Status TbeOpTask::UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
auto op_desc = node_->GetOpDesc();
GE_CHECK_NOTNULL(op_desc);
// Set runtime shape to node
for (size_t i = 0; i < input_desc.size(); ++i) {
auto tensor_desc = op_desc->MutableInputDesc(i);
auto &runtime_tensor_desc = input_desc[i];
GE_CHECK_NOTNULL(tensor_desc);
GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
}
for (size_t i = 0; i < output_desc.size(); ++i) {
auto tensor_desc = op_desc->MutableOutputDesc(i);
auto &runtime_tensor_desc = output_desc[i];
GE_CHECK_NOTNULL(tensor_desc);
GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
}
return SUCCESS;
}
Status TbeOpTask::EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, uint32_t max_tiling_size) {
if (tiling_buffer != nullptr) {
uintptr_t *arg_base = nullptr;
size_t arg_num = 0;
GetIoAddr(arg_base, arg_num);
GE_CHECK_NOTNULL(node);
GE_CHECK_NOTNULL(node->GetOpDesc());
uint32_t inputs_num = node->GetOpDesc()->GetInputsSize();
uint32_t outputs_num = node->GetOpDesc()->GetOutputsSize();
uint32_t workspace_nums = node->GetOpDesc()->GetWorkspace().size();
uint32_t tiling_index = inputs_num + outputs_num + workspace_nums;
if (arg_num == 0 || arg_num < tiling_index) {
GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Check][Size]Tiling index %u, arg number %zu is invalid.",
tiling_index, arg_num);
return ACL_ERROR_GE_INTERNAL_ERROR;
}
arg_base[tiling_index] = reinterpret_cast<uintptr_t>(tiling_buffer);
}
node_ = node;
tiling_buffer_ = tiling_buffer;
max_tiling_size_ = max_tiling_size;
return SUCCESS;
}
Status TbeOpTask::AllocateWorkspaces(const vector<int64_t> &workspace_sizes) {
static const std::string kPurpose("malloc workspace memory for dynamic op.");
workspaces_.clear();
if (workspace_sizes.empty()) {
GELOGD("No need to allocate workspace.");
return SUCCESS;
}
int64_t total_size = 0;
std::vector<int64_t> ws_offsets;
for (auto ws_size : workspace_sizes) {
// alignment and padding should be done in OpParaCalculate
if (CheckInt64AddOverflow(total_size, ws_size) != SUCCESS) {
return ACL_ERROR_GE_INTERNAL_ERROR;
}
ws_offsets.emplace_back(total_size);
total_size += ws_size;
}
GELOGD("Total workspace size is %ld", total_size);
GE_CHECK_NOTNULL(stream_resource_);
auto ws_base = stream_resource_->MallocMemory(kPurpose, static_cast<size_t>(total_size));
if (ws_base == nullptr) {
GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Malloc][Memory] failed, size: %ld", total_size);
REPORT_INNER_ERROR("E19999", "MallocMemory failed, size: %ld", total_size);
return ACL_ERROR_GE_MEMORY_ALLOCATION;
}
GELOGD("Done allocating workspace memory successfully.");
for (auto ws_offset : ws_offsets) {
workspaces_.emplace_back(ws_base + ws_offset);
}
return SUCCESS;
}
Status TbeOpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
const vector<DataBuffer> &input_buffers,
vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &output_buffers,
rtStream_t stream) {
GELOGD("[%s] Start to launch kernel", node_->GetName().c_str());
GE_CHK_STATUS_RET_NOLOG(UpdateNodeByShape(input_desc, output_desc));
GE_CHK_STATUS_RET_NOLOG(UpdateRunInfo());
GE_CHK_STATUS_RET(AllocateWorkspaces(run_info_workspaces_), "[Allocate][Workspaces] failed.");
std::vector<void *> args;
for (auto &buffer : input_buffers) {
args.emplace_back(buffer.data);
}
for (auto &buffer : output_buffers) {
args.emplace_back(buffer.data);
}
for (auto &buffer : workspaces_) {
args.emplace_back(buffer);
}
if (tiling_buffer_ != nullptr) {
GELOGD("[%s] Start to copy tiling info. size = %zu", node_->GetName().c_str(), tiling_data_.size());
GE_CHK_RT_RET(rtMemcpyAsync(tiling_buffer_, max_tiling_size_, tiling_data_.data(), tiling_data_.size(),
RT_MEMCPY_HOST_TO_DEVICE_EX, stream));
args.emplace_back(tiling_buffer_);
}
GELOGD("Dst size is %zu, src size is %zu.", arg_size_, args.size() * sizeof(void *));
// node with workspace: build can not get size of workspace, need to update arg_size_ when execute
if (arg_size_ < (args.size() * sizeof(void *))) {
size_t temp_size = args.size() * sizeof(void *);
GELOGD("Need to reset size of args_ from %zu to %zu.", arg_size_, temp_size);
args_.reset(new(std::nothrow) uint8_t[temp_size]());
GE_CHECK_NOTNULL(args_);
arg_size_ = temp_size;
}
if (memcpy_s(args_.get(), arg_size_, args.data(), args.size() * sizeof(void *)) != EOK) {
GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "[Update][KernelArgs] failed for [%s].", node_->GetName().c_str());
REPORT_INNER_ERROR("E19999", "update kernel args failed for %s.", node_->GetName().c_str());
return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
}
GELOGD("[%s] Start to invoke rtKernelLaunch", node_->GetName().c_str());
GE_CHK_STATUS_RET(DoLaunchKernel(stream), "Failed to do launch kernel.");
return SUCCESS;
}
Status TbeOpTask::DoLaunchKernel(rtStream_t stream) {
auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
if (handle_ == nullptr) {
GE_CHK_RT_RET(rtKernelLaunch(stub_func_, block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
sm_desc, stream));
} else {
std::string dev_func = original_kernel_key_ + "_" + std::to_string(tiling_key_);
std::string kernel_info = node_info_ + "/" + std::to_string(tiling_key_);
GE_CHK_RT_RET(rtKernelLaunchWithHandle(handle_, dev_func.c_str(), block_dim_, args_.get(),
static_cast<uint32_t>(arg_size_), sm_desc, stream, kernel_info.c_str()));
}
return SUCCESS;
}
void TbeOpTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
arg_base = reinterpret_cast<uintptr_t *>(args_.get());
arg_count = arg_size_ / sizeof(void *);
if (tiling_buffer_ != nullptr) {
--arg_count;
}
}
AiCpuBaseTask::~AiCpuBaseTask() {
if (ext_info_addr_dev_ != nullptr) {
(void)rtFree(ext_info_addr_dev_);
}
}
Status AiCpuBaseTask::SetExtInfoAndType(const std::string &kernel_ext_info, uint64_t kernel_id) {
if (kernel_ext_info.empty()) {
GELOGI("Kernel_ext_info is empty, no need copy to device.");
return SUCCESS;
}
int32_t unknown_shape_type_val = 0;
(void) AttrUtils::GetInt(op_desc_, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val);
GELOGD("Get unknown_type is %d.", unknown_shape_type_val);
unknown_type_ = static_cast<UnknowShapeOpType>(unknown_shape_type_val);
aicpu_ext_handle_.reset(new(std::nothrow) ::ge::hybrid::AicpuExtInfoHandler(op_desc_->GetName(),
num_inputs_,
num_outputs_,
unknown_type_));
GE_CHK_BOOL_RET_STATUS(aicpu_ext_handle_ != nullptr, ACL_ERROR_GE_MEMORY_ALLOCATION,
"[Malloc][Memory] failed for aicpu_ext_handle!");
Status ret = aicpu_ext_handle_->Parse(kernel_ext_info);
if (ret != SUCCESS) {
GELOGE(ret, "[Parse][Param:kernel_ext_info] failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
REPORT_INNER_ERROR("E19999",
"Parse Param:kernel_ext_info failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
return ret;
}
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateSessionInfo(ULLONG_MAX, kernel_id, false),
"[Update][SessionInfo] failed.");
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateExecuteMode(true), "[Update][ExecuteMode] failed.");
GE_CHK_RT_RET(rtMalloc(&ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(), RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMemcpy(ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(),
aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(),
RT_MEMCPY_HOST_TO_DEVICE));
return SUCCESS;
}
Status AiCpuBaseTask::SetInputConst() {
input_is_const_.clear();
const vector<bool> v_is_input_const = op_desc_->GetIsInputConst();
for (size_t i = 0; i < op_desc_->GetAllInputsSize(); ++i) {
const GeTensorDescPtr tensor_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(i));
if (tensor_desc == nullptr) {
GELOGD("SingleOp: %s, Index: %zu, has no input", op_desc_->GetName().c_str(), i);
continue;
}
if (i < v_is_input_const.size() && v_is_input_const[i]) {
GELOGD("SingleOp: %s, Index: %zu, input is const", op_desc_->GetName().c_str(), i);
input_is_const_.push_back(true);
continue;
}
input_is_const_.push_back(false);
}
return SUCCESS;
}
Status AiCpuBaseTask::UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc,
std::vector<GeTensorDesc> &output_desc,
rtStream_t stream) {
GELOGI("Update ext info begin, unknown_type=%d.", unknown_type_);
GE_CHECK_NOTNULL(aicpu_ext_handle_);
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateExecuteMode(false), "[Update][ExecuteMode] failed.");
if (num_inputs_ == 0 && num_outputs_ == 0) {
GELOGI("No input and output, no need update ext info.");
return SUCCESS;
}
size_t non_const_index = 0;
for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
// get input_desc from op_desc if const input, num_inputs_ is op_desc_ input_size
auto const_input_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(input_index));
GE_CHECK_NOTNULL(const_input_desc);
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, *const_input_desc),
"[Update][InputShapeAndType] failed, input_index:%zu.", input_index);
continue;
}
GE_CHK_BOOL_RET_STATUS(non_const_index < input_desc.size(), ACL_ERROR_GE_PARAM_INVALID,
"[Check][Size]Input_desc size is %zu, but get non_const_index is %zu", input_desc.size(), non_const_index);
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, input_desc[non_const_index]),
"[Update][InputShapeAndType]failed, input_index:%zu.", input_index);
if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
GE_CHK_STATUS_RET(op_desc_->UpdateInputDesc(input_index, input_desc[non_const_index]),
"AiCpuTask Update [%zu]th input desc failed.",input_index);
}
non_const_index++;
}
if (unknown_type_ != DEPEND_COMPUTE) {
for (size_t j = 0; j < num_outputs_; ++j) {
GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateOutputShapeAndType(j, output_desc[j]),
"[Update][OutputShapeAndType] failed, Output:%zu.", j);
if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(j, output_desc[j]),
"AiCpuTask Update [%zu]th output desc failed.",j);
}
}
}
GE_CHK_RT_RET(rtMemcpyAsync(ext_info_addr_dev_,
aicpu_ext_handle_->GetExtInfoLen(), // check size
aicpu_ext_handle_->GetExtInfo(),
aicpu_ext_handle_->GetExtInfoLen(),
RT_MEMCPY_HOST_TO_DEVICE_EX,
stream));
GELOGI("Update ext info end.");
return SUCCESS;
}
Status AiCpuBaseTask::UpdateOutputShape(vector<GeTensorDesc> &output_desc) {
if (num_outputs_ == 0) {
GELOGD("AiCpuBaseTask output_num is 0, no need update output shape.");
return SUCCESS;
}
GELOGD("Start to update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape.");
GE_CHK_RT_RET(rtMemcpy(aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(), ext_info_addr_dev_,
aicpu_ext_handle_->GetExtInfoLen(), RT_MEMCPY_DEVICE_TO_HOST));
for (size_t i = 0; i < num_outputs_; ++i) {
GeShape shape;
DataType data_type;
aicpu_ext_handle_->GetOutputShapeAndType(i, shape, data_type);
GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(shape, output_desc[i]),
"[Update][ShapeToOutputDesc] failed, output:%zu.", i);
if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "[Update][OutputDesc] failed, output:%zu.", i);
}
}
GELOGD("Update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape finished.");
return SUCCESS;
}
Status AiCpuBaseTask::UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc) {
auto shape_old = output_desc.GetShape();
output_desc.SetShape(shape_new);
GELOGD("Update AiCpuBaseTask shape from %s to %s", shape_old.ToString().c_str(), shape_new.ToString().c_str());
auto origin_shape_old = output_desc.GetOriginShape();
auto origin_format = output_desc.GetOriginFormat();
auto format = output_desc.GetFormat();
if (origin_format == format) {
output_desc.SetOriginShape(shape_new);
return SUCCESS;
}
std::vector<int64_t> origin_dims_new;
auto trans_ret = formats::TransShape(format, shape_new.GetDims(),
output_desc.GetDataType(), origin_format, origin_dims_new);
GE_CHK_STATUS_RET(trans_ret,
"[Trans][Shape] failed, AiCpuTask originFormat[%d] is not same as format[%d], shape=%s.",
origin_format, format, shape_new.ToString().c_str());
auto origin_shape_new = GeShape(origin_dims_new);
output_desc.SetOriginShape(origin_shape_new);
GELOGD("AiCpuTask originFormat[%d] is not same as format[%d], need update from %s ro %s.",
origin_format, format, origin_shape_old.ToString().c_str(), origin_shape_new.ToString().c_str());
return SUCCESS;
}
Status AiCpuBaseTask::UpdateIoAddr(const vector<DataBuffer> &inputs, const vector<DataBuffer> &outputs) {
uintptr_t *arg_base = nullptr;
size_t arg_num = 0;
GetIoAddr(arg_base, arg_num);
// input number and output number was check in ValidateParams
size_t non_const_index = 0;
for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
// const input no need update addr
GE_CHECK_NOTNULL(arg_base);
GELOGD("AICpuTask input[%zu] addr = %lu", input_index, *arg_base);
arg_base++;
continue;
}
GE_CHK_BOOL_RET_STATUS(non_const_index < inputs.size(), ACL_ERROR_GE_PARAM_INVALID,
"[Check][Size] Input size is %zu, but get non_const_index is %zu", inputs.size(), non_const_index);
auto addr = inputs[non_const_index].data;
GE_CHECK_NOTNULL(addr);
GELOGD("AICpuTask input[%zu] addr = %p", input_index, addr);
*arg_base++ = reinterpret_cast<uintptr_t>(addr);
non_const_index++;
}
for (size_t i = 0; i < outputs.size(); ++i) {
auto addr = outputs[i].data;
GE_CHECK_NOTNULL(addr);
GELOGD("AICpuTask output[%zu] addr = %p", i, addr);
*arg_base++ = reinterpret_cast<uintptr_t>(addr);
}
return SUCCESS;
}
AiCpuTask::~AiCpuTask() {
FreeHbm(args_);
FreeHbm(io_addr_);
if (dynamic_flag_) {
FreeHbm(workspace_addr_);
}
FreeHbm(copy_workspace_buf_);
FreeHbm(copy_ioaddr_dev_);
FreeHbm(copy_input_release_flag_dev_);
FreeHbm(copy_input_data_size_dev_);
FreeHbm(copy_input_src_dev_);
FreeHbm(copy_input_dst_dev_);
FreeHbm(copy_task_args_buf_);
for (auto summary : output_summary_) {
FreeHbm(summary);
}
for (auto out_shape : out_shape_hbm_) {
FreeHbm(out_shape);
}
}
Status AiCpuTask::LaunchKernel(rtStream_t stream) {
GELOGD("Start to launch kernel. task = %s", this->op_type_.c_str());
auto ret = rtMemcpyAsync(io_addr_,
io_addr_size_,
io_addr_host_.data(),
io_addr_host_.size() * sizeof(void *),
RT_MEMCPY_HOST_TO_DEVICE_EX,
stream);
if (ret != RT_ERROR_NONE) {
GELOGE(ret, "[MemcpyAsync][Date] failed. ret = %d, task = %s", ret, this->op_type_.c_str());
REPORT_CALL_ERROR("E19999", "rtMemcpyAsync data failed, ret = %d, task = %s", ret, this->op_type_.c_str());
return RT_ERROR_TO_GE_STATUS(ret);
}
GELOGI("To invoke rtKernelLaunchEx. task = %s", this->op_type_.c_str());
ret = rtKernelLaunchEx(args_, arg_size_, 0, stream);
if (ret != RT_ERROR_NONE) {
GELOGE(ret, "[Invoke][rtKernelLaunch] failed. ret = %d, task = %s", ret, this->op_type_.c_str());
REPORT_CALL_ERROR("E19999", "invoke rtKernelLaunchEx failed, ret = %d, task = %s", ret, this->op_type_.c_str());
return RT_ERROR_TO_GE_STATUS(ret);
}
GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
GELOGD("Done launch kernel successfully. task = %s", this->op_type_.c_str());
return SUCCESS;
}
Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
std::vector<uint64_t> copy_input_release_flag;
std::vector<uint64_t> copy_input_data_size;
std::vector<uint64_t> copy_input_src;
std::vector<uint64_t> copy_input_dst;
for (size_t i = 0; i < num_outputs_; ++i) {
const auto &summary = output_summary_host_[i];
GELOGI("Node out[%zu] summary, shape data=0x%lx, shape data size=%lu, raw data=0x%lx, raw data size=%lu.",
i, summary.shape_data_ptr, summary.shape_data_size,
summary.raw_data_ptr, summary.raw_data_size);
auto output = outputs[i];
copy_input_release_flag.emplace_back(kReleaseFlag);
if (summary.raw_data_size > 0) {
copy_input_data_size.emplace_back(output.length);
} else {
copy_input_data_size.emplace_back(summary.raw_data_size);
}
copy_input_src.emplace_back(summary.raw_data_ptr);
copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(output.data));
const auto &shape_buffer = out_shape_hbm_[i];
copy_input_release_flag.emplace_back(kReleaseFlag);
copy_input_data_size.emplace_back(summary.shape_data_size);
copy_input_src.emplace_back(summary.shape_data_ptr);
copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(shape_buffer));
}
const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
GE_CHK_RT_RET(rtMemcpy(copy_input_release_flag_dev_, copy_input_buf_len,
copy_input_release_flag.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
GE_CHK_RT_RET(rtMemcpy(copy_input_data_size_dev_, copy_input_buf_len,
copy_input_data_size.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
GE_CHK_RT_RET(rtMemcpy(copy_input_src_dev_, copy_input_buf_len,
copy_input_src.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
GE_CHK_RT_RET(rtMemcpy(copy_input_dst_dev_, copy_input_buf_len,
copy_input_dst.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
return SUCCESS;
}
Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
for (size_t i = 0; i < num_outputs_; ++i) {
auto &result_summary = output_summary_host_[i];
GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary),
RT_MEMCPY_DEVICE_TO_HOST));
auto shape_data_size = result_summary.shape_data_size;
void *shape_buffer = nullptr;
if (shape_data_size > 0) {
GE_CHK_RT_RET(rtMalloc(&shape_buffer, shape_data_size, RT_MEMORY_HBM));
}
out_shape_hbm_.emplace_back(shape_buffer);
}
return SUCCESS;
}
Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
rtStream_t stream) {
GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
GE_CHK_RT_RET(rtKernelLaunchEx(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
RT_KERNEL_DEFAULT, stream));
GE_CHK_RT_RET(rtStreamSynchronize(stream));
return SUCCESS;
}
Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
for (size_t i = 0; i < num_outputs_; ++i) {
const auto &result_summary = output_summary_host_[i];
std::vector<int64_t> shape_dims;
if (result_summary.shape_data_size > 0) {
const auto &shape_hbm = out_shape_hbm_[i];
uint32_t dim_num = result_summary.shape_data_size / sizeof(int64_t);
std::unique_ptr<int64_t[]> shape_addr(new (std::nothrow) int64_t[dim_num]());
GE_CHECK_NOTNULL(shape_addr);
GE_CHK_RT_RET(rtMemcpy(shape_addr.get(), result_summary.shape_data_size, shape_hbm,
result_summary.shape_data_size, RT_MEMCPY_DEVICE_TO_HOST));
for (uint32_t dim_idx = 0; dim_idx < dim_num; ++dim_idx) {
shape_dims.emplace_back(shape_addr[dim_idx]);
GELOGD("Node [%zu]th output dim[%u]=%ld.", i, dim_idx, shape_addr[dim_idx]);
}
}
GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(GeShape(shape_dims), output_desc[i]),
"[Update][ShapeToOutputDesc] failed , output:%zu.", i);
if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "[Update][OutputDesc] failed, output:%zu.", i);
}
}
return SUCCESS;
}
Status AiCpuTask::UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &outputs,
rtStream_t stream) {
if (num_outputs_ == 0) {
GELOGI("Output num is 0, there is no need to update the output and size.");
return SUCCESS;
}
GELOGI("Update shape and data by result summary begin.");
for (auto out_shape : out_shape_hbm_) {
FreeHbm(out_shape);
}
out_shape_hbm_.clear();
GE_CHK_STATUS_RET(ReadResultSummaryAndPrepareMemory(),
"[Read][ResultSummaryAndPrepareMemory] failed.");
GE_CHK_STATUS_RET(CopyDataToHbm(outputs, stream),
"[Copy][DataToHbm] failed.");
GE_CHK_STATUS_RET(UpdateShapeByHbmBuffer(output_desc),
"[Update][ShapeByHbmBuffer] failed.");
for (auto out_shape : out_shape_hbm_) {
FreeHbm(out_shape);
}
out_shape_hbm_.clear();
GELOGI("Update shape and data by result summary end.");
return SUCCESS;
}
Status AiCpuTask::InitForSummaryAndCopy() {
if (unknown_type_ != DEPEND_COMPUTE || num_outputs_ == 0) {
GELOGI("Unknown_type is %d, output num is %zu.", unknown_type_, num_outputs_);
return SUCCESS;
}
output_summary_.resize(num_outputs_);
constexpr auto result_summary_size = sizeof(aicpu::FWKAdapter::ResultSummary);
for (size_t i = 0; i < num_outputs_; ++i) {
GE_CHK_RT_RET(rtMalloc(&output_summary_[i], result_summary_size, RT_MEMORY_HBM));
}
output_summary_host_.resize(num_outputs_);
const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
GE_CHK_RT_RET(rtMalloc(&copy_input_release_flag_dev_, copy_input_buf_len, RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMalloc(&copy_input_data_size_dev_, copy_input_buf_len, RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMalloc(&copy_input_src_dev_, copy_input_buf_len, RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMalloc(&copy_input_dst_dev_, copy_input_buf_len, RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMalloc(&copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL), RT_MEMORY_HBM));
std::vector<uint64_t> copy_io_addr;
copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_release_flag_dev_));
copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_data_size_dev_));
copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_src_dev_));
copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_dst_dev_));
const auto copy_io_addr_size = sizeof(uint64_t) * copy_io_addr.size();
GE_CHK_RT_RET(rtMalloc(&copy_ioaddr_dev_, copy_io_addr_size, RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMemcpy(copy_ioaddr_dev_, copy_io_addr_size,
copy_io_addr.data(), copy_io_addr_size, RT_MEMCPY_HOST_TO_DEVICE));
return SUCCESS;
}
Status AiCpuTask::SetMemCopyTask(const domi::KernelExDef &kernel_def) {
if (kernel_def.args_size() > sizeof(STR_FWK_OP_KERNEL)) {
GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Size]sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
REPORT_INNER_ERROR("E19999", "[sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
return ACL_ERROR_GE_PARAM_INVALID;
}
GE_CHK_RT_RET(rtMalloc(&copy_workspace_buf_, kernel_def.task_info_size(), RT_MEMORY_HBM));
GE_CHK_RT_RET(rtMemcpy(copy_workspace_buf_, kernel_def.task_info_size(),
kernel_def.task_info().data(), kernel_def.task_info_size(), RT_MEMCPY_HOST_TO_DEVICE));
STR_FWK_OP_KERNEL aicpu_task = {0};
auto sec_ret = memcpy_s(&aicpu_task, sizeof(STR_FWK_OP_KERNEL),
kernel_def.args().data(), kernel_def.args().size());
if (sec_ret != EOK) {
GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "[Update][TaskArgs] failed, ret: %d", sec_ret);
REPORT_INNER_ERROR("E19999", "update STR_FWK_OP_KERNEL args failed because memcpy_s return %d.", sec_ret);
return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
}
aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = reinterpret_cast<uintptr_t>(copy_ioaddr_dev_);
aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = reinterpret_cast<uintptr_t>(copy_workspace_buf_);
aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
GE_CHK_RT_RET(rtMemcpy(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
&aicpu_task, sizeof(STR_FWK_OP_KERNEL), RT_MEMCPY_HOST_TO_DEVICE));
return SUCCESS;
}
Status AiCpuTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
const std::vector<DataBuffer> &input_buffers,
std::vector<GeTensorDesc> &output_desc,
std::vector<DataBuffer> &output_buffers,
rtStream_t stream) {
GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
if (unknown_type_ == DEPEND_COMPUTE) {
std::vector<DataBuffer> summary_buffers;
for (size_t i = 0; i < num_outputs_; ++i) {
summary_buffers.emplace_back(output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary), false);
}
GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, summary_buffers));
} else {
GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
}
GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
if (unknown_type_ == DEPEND_SHAPE_RANGE) {
GE_CHK_RT_RET(rtStreamSynchronize(stream));
GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
} else if (unknown_type_ == DEPEND_COMPUTE) {
GE_CHK_RT_RET(rtStreamSynchronize(stream));
GE_CHK_STATUS_RET_NOLOG(UpdateShapeAndDataByResultSummary(output_desc, output_buffers, stream));
}
return SUCCESS;
}
Status AiCpuBaseTask::UpdateArgTable(const SingleOpModelParam &param) {
// aicpu do not have workspace, for now
return DoUpdateArgTable(param, false);
}
const std::string &AiCpuBaseTask::GetTaskType() const { return kTaskTypeAicpu; }
void AiCpuTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
arg_base = reinterpret_cast<uintptr_t *>(io_addr_host_.data());
arg_count = io_addr_host_.size();
}
void AiCpuCCTask::SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size) {
args_ = std::move(args);
arg_size_ = arg_size;
// The blockdim value is defult "1" for rtCpuKernelLaunch
block_dim_ = 1;
}
void AiCpuCCTask::SetSoName(const std::string &so_name) { so_name_ = so_name; }
void AiCpuCCTask::SetkernelName(const std::string &kernel_Name) { kernel_name_ = kernel_Name; }
void AiCpuCCTask::SetIoAddr(uintptr_t *io_addr) { io_addr_ = io_addr; }
const void *AiCpuCCTask::GetArgs() const { return args_.get(); }
size_t AiCpuCCTask::GetArgSize() const { return arg_size_; }
AiCpuCCTask::~AiCpuCCTask() {
}
Status AiCpuCCTask::LaunchKernel(rtStream_t stream) {
GELOGI("To invoke rtCpuKernelLaunch. block_dim = %u, so_name is %s, kernel_name is %s", block_dim_, so_name_.data(),
kernel_name_.data());
// sm_desc is nullptr, because l2 buffer does not support
auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
auto ret = rtCpuKernelLaunchWithFlag(static_cast<const void *>(so_name_.data()),
static_cast<const void *>(kernel_name_.data()),
block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
sm_desc, stream, dump_flag_);
if (ret != RT_ERROR_NONE) {
GELOGE(ret, "[Invoke][rtCpuKernelLaunchWithFlag] failed. ret = %d.", ret);
REPORT_CALL_ERROR("E19999", "invoke rtCpuKernelLaunchWithFlag failed, ret:%d.", ret);
return RT_ERROR_TO_GE_STATUS(ret);
}
GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
GELOGD("Invoke rtCpuKernelLaunch succeeded");
return SUCCESS;
}
Status AiCpuCCTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
const std::vector<DataBuffer> &input_buffers,
std::vector<GeTensorDesc> &output_desc,
std::vector<DataBuffer> &output_buffers,
rtStream_t stream) {
GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
if (unknown_type_ == DEPEND_SHAPE_RANGE) {
GE_CHK_RT_RET(rtStreamSynchronize(stream));
GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
}
return SUCCESS;
}
void AiCpuCCTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
arg_base = io_addr_;
arg_count = io_addr_num_;
}
} // namespace ge
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