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Pre Merge pull request !2052 from guopeian/aicpu-f

pull/2052/MERGE
guopeian Gitee 3 years ago
parent
commit
c4af9cf388
10 changed files with 665 additions and 154 deletions
  1. +168
    -39
      ge/hybrid/node_executor/aicpu/aicpu_node_executor.cc
  2. +49
    -34
      ge/hybrid/node_executor/aicpu/aicpu_node_executor.h
  3. +12
    -3
      ge/single_op/single_op_model.cc
  4. +1
    -1
      ge/single_op/single_op_model.h
  5. +1
    -4
      ge/single_op/task/aicpu_kernel_task_builder.cc
  6. +142
    -33
      ge/single_op/task/op_task.cc
  7. +37
    -29
      ge/single_op/task/op_task.h
  8. +136
    -9
      tests/ut/ge/hybrid/node_executor/aicpu/aicpu_node_executor_unittest.cc
  9. +71
    -1
      tests/ut/ge/single_op/single_op_model_unittest.cc
  10. +48
    -1
      tests/ut/ge/single_op/single_op_task_unittest.cc

+ 168
- 39
ge/hybrid/node_executor/aicpu/aicpu_node_executor.cc View File

@@ -548,8 +548,8 @@ Status AicpuTfNodeTask::EnsureSessionCreated(uint64_t session_id) {
return SUCCESS;
}

Status AicpuTfNodeTask::ReadResultSummaryAndPrepareMemory(TaskContext &context,
std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
Status AicpuNodeTaskBase::ReadResultSummaryAndPrepareMemory(TaskContext &context,
std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
for (auto i = 0; i < node_item_->num_outputs; ++i) {
auto &result_summary = output_summary_host_[i];
GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
@@ -574,6 +574,30 @@ Status AicpuTfNodeTask::ReadResultSummaryAndPrepareMemory(TaskContext &context,
return SUCCESS;
}

Status AicpuNodeTask::CopyDataToHbm(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
GE_CHK_BOOL_RET_STATUS(out_shape_hbm.size() == static_cast<std::size_t>(node_item_->num_outputs),
INTERNAL_ERROR,
"[Check][Size]Node[%s] has %d outputs but out shape is %zu not equal.",
node_name_.c_str(), node_item_->num_outputs, out_shape_hbm.size());

GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(context, out_shape_hbm));

RECORD_CALLBACK_EVENT(context.GetExecutionContext(), node_name_.c_str(), "[LaunchCopy] Start");
auto rt_ret = rtCpuKernelLaunchWithFlag(reinterpret_cast<const void *>(memcpy_so_name_.c_str()),
reinterpret_cast<const void *>(memcpy_kernel_name_.c_str()),
1, // default core dim is 1
memcpy_args_.get(), memcpy_args_size_,
nullptr, context.GetStream(), RT_KERNEL_DEFAULT);
GE_CHK_RT_RET(rt_ret);

RECORD_CALLBACK_EVENT(context.GetExecutionContext(), node_name_.c_str(), "[LaunchCopy] End");

GE_CHK_RT_RET(rtStreamSynchronize(context.GetStream()));
RECORD_CALLBACK_EVENT(context.GetExecutionContext(), node_name_.c_str(), "[SynchronizeCopy] End");
return SUCCESS;
}

Status AicpuTfNodeTask::CopyDataToHbm(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
GE_CHK_BOOL_RET_STATUS(out_shape_hbm.size() == static_cast<std::size_t>(node_item_->num_outputs),
@@ -593,8 +617,8 @@ Status AicpuTfNodeTask::CopyDataToHbm(TaskContext &context,
return SUCCESS;
}

Status AicpuTfNodeTask::PrepareCopyInputs(const TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
Status AicpuNodeTaskBase::PrepareCopyInputs(const TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
std::vector<uint64_t> copy_input_release_flag;
std::vector<uint64_t> copy_input_data_size;
std::vector<uint64_t> copy_input_src;
@@ -635,8 +659,8 @@ Status AicpuTfNodeTask::PrepareCopyInputs(const TaskContext &context,
return SUCCESS;
}

Status AicpuTfNodeTask::UpdateShapeByHbmBuffer(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
Status AicpuNodeTaskBase::UpdateShapeByHbmBuffer(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) {
GE_CHK_BOOL_RET_STATUS(out_shape_hbm.size() == static_cast<std::size_t>(node_item_->num_outputs),
INTERNAL_ERROR,
"Node[%s] has %d outputs but out shape is %zu",
@@ -667,7 +691,7 @@ Status AicpuTfNodeTask::UpdateShapeByHbmBuffer(TaskContext &context,
return SUCCESS;
}

Status AicpuTfNodeTask::UpdateShapeAndDataByResultSummary(TaskContext &context) {
Status AicpuNodeTaskBase::UpdateShapeAndDataByResultSummary(TaskContext &context) {
GELOGD("Node[%s] update shape and data by result summary begin.", node_name_.c_str());

std::vector<std::unique_ptr<TensorBuffer>> out_shape_hbm;
@@ -762,7 +786,7 @@ Status AicpuTfNodeTask::LaunchTask(TaskContext &context) {
return SUCCESS;
}

Status AicpuTfNodeTask::TaskCallback(TaskContext &context) {
Status AicpuNodeTaskBase::TaskCallback(TaskContext &context) {
GELOGD("Node[%s] task callback start. is_dynamic=%s, unknown_type=%d.",
node_name_.c_str(), node_item_->is_dynamic ? "true" : "false", unknown_type_);
Status callback_ret = SUCCESS;
@@ -779,14 +803,115 @@ Status AicpuTfNodeTask::TaskCallback(TaskContext &context) {
return callback_ret;
}

Status AicpuNodeTask::SetMemCopyTask(const domi::TaskDef &task_def) {
if (node_item_->num_outputs == 0) {
GELOGD("Node[%s] type[%s] has no output, no need set mem_copy task.",
node_name_.c_str(), node_item_->node_type.c_str());
return SUCCESS;
}

GELOGD("Start to set memcpy task for node[%s].", node_name_.c_str());
const domi::KernelDef &kernel_def = task_def.kernel();
auto &memcpy_args = kernel_def.args();
memcpy_args_size_ = kernel_def.args_size();
memcpy_so_name_ = kernel_def.so_name();
memcpy_kernel_name_ = kernel_def.kernel_name();
if (memcpy_args.size() != memcpy_args_size_) {
REPORT_INNER_ERROR("E19999", "MemCopy task def args.size=%zu, but args_size=%u not equal.",
memcpy_args.size(), memcpy_args_size_);
GELOGE(FAILED, "[Check][Size]MemCopy task def args.size=%zu, but args_size=%u not equal.",
memcpy_args.size(), memcpy_args_size_);
return FAILED;
}

if (memcpy_args_size_ < sizeof(aicpu::AicpuParamHead)) {
REPORT_INNER_ERROR("E19999", "Task def args_size=%u is less than aicpu param head len=%zu.",
memcpy_args_size_, sizeof(aicpu::AicpuParamHead));
GELOGE(FAILED, "[Check][Size] Task def args_size=%u is less than aicpu param head len=%zu.",
memcpy_args_size_, sizeof(aicpu::AicpuParamHead));
return FAILED;
}

memcpy_args_.reset(new(std::nothrow) uint8_t[memcpy_args_size_]());
if (memcpy_args_ == nullptr) {
REPORT_INNER_ERROR("E19999", "new memory failed for Node[MemCopy], task_size[%u].",
memcpy_args_size_);
GELOGE(FAILED, "[Malloc][Memory] failed for Node[MemCopy], task_size[%u].",
memcpy_args_size_);
return FAILED;
}

errno_t sec_ret = memcpy_s(memcpy_args_.get(), memcpy_args_size_, memcpy_args.c_str(), memcpy_args.size());
if (sec_ret != EOK) {
REPORT_INNER_ERROR("E19999",
"memcpy_s argc_ failed for Node[MemCopy], ret: %d", sec_ret);
GELOGE(INTERNAL_ERROR,
"[Update][args] failed for Node[MemCopy], ret: %d", sec_ret);
return sec_ret;
}

auto memcpy_param_head = reinterpret_cast<aicpu::AicpuParamHead *>(memcpy_args_.get());
uint32_t memcpy_io_num = memcpy_param_head->ioAddrNum;
auto memcpy_io_addr = memcpy_args_.get() + sizeof(aicpu::AicpuParamHead);
// if has input and output, need copy to ioaddr
int cpy_ret = memcpy_s(memcpy_io_addr, memcpy_args_size_ - sizeof(aicpu::AicpuParamHead),
&copy_io_addr_[0], sizeof(uint64_t) * memcpy_io_num);
if (cpy_ret != EOK) {
REPORT_INNER_ERROR("E19999", "Node[Memcpoy] memcpy io addr to AicpuParamHead failed,"
"ret=%d, args_size=%u, io nums=%u.",
cpy_ret, memcpy_args_size_, memcpy_io_num);
GELOGE(INTERNAL_ERROR, "[Update][io_addr]Node[MemCopy] memcpy io addr to AicpuParamHead failed,"
"ret=%d, args_size=%u, io nums=%u.",
cpy_ret, memcpy_args_size_, memcpy_io_num);
return INTERNAL_ERROR;
}
GELOGD("Set memcpy task for node[MemCopy] successfully.");
return SUCCESS;
}

Status AicpuNodeTask::InitForDependComputeTask() {
if ((unknown_type_ != DEPEND_COMPUTE) || (node_item_->num_outputs == 0)) {
GELOGD("Node[%s] type[%s] unknown_type is %d, output num is %d.",
node_name_.c_str(), node_item_->node_type.c_str(), unknown_type_, node_item_->num_outputs);
return SUCCESS;
}

output_summary_.resize(node_item_->num_outputs);
constexpr auto result_summary_size = sizeof(aicpu::FWKAdapter::ResultSummary);
for (auto i = 0; i < node_item_->num_outputs; ++i) {
GE_CHK_STATUS_RET(AllocTensorBuffer(result_summary_size, output_summary_[i]),
"[Alloc][TensorBuffer] failed for Node[%s] to copy result summary info, size=%zu.",
node_name_.c_str(), result_summary_size);
}
output_summary_host_.resize(node_item_->num_outputs);

// init for mem copy task
// copy task need copy output_data and output_shape, max len is 2 * output_num
const size_t copy_input_buf_len = node_item_->num_outputs * 2 * sizeof(uint64_t);
GE_CHK_STATUS_RET(AllocTensorBuffer(copy_input_buf_len, copy_input_release_flag_dev_),
"[Alloc][TensorBuffer] failed for Node[%s] to copy task input release_flag, size=%zu",
node_name_.c_str(), copy_input_buf_len);
GE_CHK_STATUS_RET(AllocTensorBuffer(copy_input_buf_len, copy_input_data_size_dev_),
"[Alloc][TensorBuffer] failed for Node[%s] to copy task input data_size, size=%zu",
node_name_.c_str(), copy_input_buf_len);
GE_CHK_STATUS_RET(AllocTensorBuffer(copy_input_buf_len, copy_input_src_dev_),
"[Alloc][TensorBuffer] failed for Node[%s] to copy task input src, size=%zu",
node_name_.c_str(), copy_input_buf_len);
GE_CHK_STATUS_RET(AllocTensorBuffer(copy_input_buf_len, copy_input_dst_dev_),
"[Alloc][TensorBuffer] failed for Node[%s] to copy task input dst, size=%zu",
node_name_.c_str(), copy_input_buf_len);

copy_io_addr_.emplace_back(reinterpret_cast<uintptr_t>(copy_input_release_flag_dev_->GetData()));
copy_io_addr_.emplace_back(reinterpret_cast<uintptr_t>(copy_input_data_size_dev_->GetData()));
copy_io_addr_.emplace_back(reinterpret_cast<uintptr_t>(copy_input_src_dev_->GetData()));
copy_io_addr_.emplace_back(reinterpret_cast<uintptr_t>(copy_input_dst_dev_->GetData()));
return SUCCESS;
}

Status AicpuNodeTask::Init(const HybridModel &model) {
auto node_name = node_name_;
GELOGD("Node[%s] init start.", node_name.c_str());

GE_CHK_BOOL_RET_STATUS(unknown_type_ != DEPEND_COMPUTE, FAILED,
"[Check][Type]Node[%s] unknown type[%d] is depend compute, it's not supported now.",
node_name.c_str(), unknown_type_);

GE_CHK_BOOL_RET_STATUS(task_def_.has_kernel(), FAILED,
"[Check][task_def_]Node[%s] task def does not has kernel.", node_name.c_str());
auto &kernel_def = task_def_.kernel();
@@ -877,7 +1002,9 @@ Status AicpuNodeTask::Init(const HybridModel &model) {
GELOGD("Get op:%s attribute(is_blocking_op), value:%d", op_desc->GetName().c_str(), is_blocking_aicpu_op_);
GE_CHK_STATUS_RET(InitExtInfo(kernel_ext_info, ext_session_id),
"[Init][ExtInfo] failed for Node[%s].", node_name.c_str());

GE_CHK_STATUS_RET(InitForDependComputeTask(),
"[Init][DependComputeTask] failed for Node[%s].",
node_name_.c_str());
if (ext_info_addr_dev_ == nullptr) {
aicpu_param_head->extInfoLength = 0;
aicpu_param_head->extInfoAddr = 0;
@@ -885,7 +1012,11 @@ Status AicpuNodeTask::Init(const HybridModel &model) {
aicpu_param_head->extInfoLength = ext_info_addr_dev_->GetSize();
aicpu_param_head->extInfoAddr = reinterpret_cast<uintptr_t>(ext_info_addr_dev_->GetData());
}

auto task_defs = model.GetTaskDefs(node_item_->node);
GE_CHECK_NOTNULL(task_defs);
if (unknown_type_ == DEPEND_COMPUTE) {
GE_CHK_STATUS_RET_NOLOG(SetMemCopyTask((*task_defs)[1]));
}
GELOGD("Node[%s] init end.", node_name.c_str());
return SUCCESS;
}
@@ -900,21 +1031,36 @@ Status AicpuNodeTask::UpdateIoAddr(TaskContext &context) {
GELOGD("Node[%s] input[%d] = %p, size = %zu", node_name_.c_str(), i, inputData->GetData(), inputData->GetSize());
io_addrs.emplace_back(reinterpret_cast<uintptr_t>(inputData->GetData()));
}
// known shape or not depend compute
if (!node_item_->is_dynamic || unknown_type_ != DEPEND_COMPUTE) {
// unknown type 4 do this in call back.
GE_CHK_STATUS_RET_NOLOG(context.AllocateOutputs());
for (auto j = 0; j < node_item_->num_outputs; ++j) {
auto outputData = context.GetOutput(j);
GE_CHECK_NOTNULL(outputData);
GELOGD("Node[%s] output[%d] addr = %p, size = %zu",
node_name_.c_str(), j, outputData->GetData(), outputData->GetSize());
io_addrs.emplace_back(reinterpret_cast<uintptr_t>(outputData->GetData()));
}
} else {
// unknown type 4 use result summary update ioaddr.
GELOGD("Node[%s] is depend compute node, use result summary as out addr.", node_name_.c_str());
GE_CHK_BOOL_RET_STATUS(output_summary_.size() == static_cast<std::size_t>(node_item_->num_outputs),
INTERNAL_ERROR,
"[Check][Size]Node[%s] has %d output but %zu output summary not equal.",
node_name_.c_str(), node_item_->num_outputs, output_summary_.size());

GE_CHK_STATUS_RET_NOLOG(context.AllocateOutputs());
for (auto j = 0; j < node_item_->num_outputs; ++j) {
auto outputData = context.GetOutput(j);
GE_CHECK_NOTNULL(outputData);
GELOGD("Node[%s] output[%d] addr = %p, size = %zu", node_name_.c_str(), j,
outputData->GetData(), outputData->GetSize());
io_addrs.emplace_back(reinterpret_cast<uintptr_t>(outputData->GetData()));
for (auto j = 0; j < node_item_->num_outputs; ++j) {
void *summary_addr = output_summary_[j]->GetData();
io_addrs.emplace_back(reinterpret_cast<uintptr_t>(summary_addr));
}
}

auto io_addr = args_.get() + sizeof(aicpu::AicpuParamHead);
// if has input and output, need copy to ioaddr
int cpy_ret = memcpy_s(io_addr, args_size_ - sizeof(aicpu::AicpuParamHead),
&io_addrs[0], sizeof(uint64_t) * io_addrs.size());
GE_IF_BOOL_EXEC(cpy_ret != 0,
GE_IF_BOOL_EXEC(cpy_ret != EOK,
REPORT_INNER_ERROR("E19999", "Node[%s] memcpy io addr to AicpuParamHead failed,"
"ret=%d, args_size=%u, io nums=%zu.",
node_name_.c_str(), cpy_ret, args_size_, io_addrs.size());
@@ -951,23 +1097,6 @@ Status AicpuNodeTask::LaunchTask(TaskContext &context) {
return SUCCESS;
}

Status AicpuNodeTask::TaskCallback(TaskContext &context) {
GELOGD("Node[%s] task callback start, is_dynamic = %s, unknown_type=%d.",
node_name_.c_str(), node_item_->is_dynamic ? "true" : "false", unknown_type_);
Status callback_ret = SUCCESS;

// check need update shape, call update shape.
if (node_item_->is_dynamic && unknown_type_ == DEPEND_SHAPE_RANGE) {
// check result
callback_ret = UpdateOutputShapeFromExtInfo(context);
} else {
GELOGD("Node[%s] unknown shape type is %d no need update output shape.",
node_name_.c_str(), unknown_type_);
}
GELOGD("Node[%s] task callback end.", node_name_.c_str());
return callback_ret;
}

Status AiCpuNodeExecutor::PrepareTask(NodeTask &task, TaskContext &context) const {
// malloc HBM memory at Init, here just update them
RECORD_EXECUTION_EVENT(context.GetExecutionContext(), context.GetNodeName(), "[AiCpuNodeExecutorPrepareTask] Start");


+ 49
- 34
ge/hybrid/node_executor/aicpu/aicpu_node_executor.h View File

@@ -55,11 +55,33 @@ class AicpuNodeTaskBase : public NodeTask {

virtual Status LaunchTask(TaskContext &context) = 0;

virtual Status TaskCallback(TaskContext &context) = 0;
virtual Status InitForDependComputeTask() = 0;

Status TaskCallback(TaskContext &context);

virtual Status UpdateShapeAndDataByResultSummary(TaskContext &context);

virtual Status UpdateIoAddr(TaskContext &context) = 0;

static Status AllocTensorBuffer(size_t size, std::unique_ptr<TensorBuffer> &tensor_buffer);
virtual Status CopyDataToHbm(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) = 0;

///
/// read result summary and prepare copy task memory.
/// @param context task context
/// @param out_shape_hbm if scalar, TensorBuffer->data is null, size=0
/// @return SUCCESS:success other:failed
///
Status ReadResultSummaryAndPrepareMemory(TaskContext &context,
std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);

Status UpdateShapeByHbmBuffer(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);

Status PrepareCopyInputs(const TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);

Status DistributeWaitTaskForAicpuBlockingOp(rtStream_t stream);
Status CheckDeviceSupportBlockingAicpuOpProcess(bool &is_support);
@@ -83,6 +105,13 @@ class AicpuNodeTaskBase : public NodeTask {
// ext info addr, device mem
std::unique_ptr<TensorBuffer> ext_info_addr_dev_;

std::vector<std::unique_ptr<TensorBuffer>> output_summary_;
std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;

std::unique_ptr<TensorBuffer> copy_input_release_flag_dev_;
std::unique_ptr<TensorBuffer> copy_input_data_size_dev_;
std::unique_ptr<TensorBuffer> copy_input_src_dev_;
std::unique_ptr<TensorBuffer> copy_input_dst_dev_;
// for blocking aicpu op
bool is_blocking_aicpu_op_ = false;
rtEvent_t rt_event_ = nullptr;
@@ -101,33 +130,14 @@ class AicpuTfNodeTask : public AicpuNodeTaskBase {

Status LaunchTask(TaskContext &context) override;

Status TaskCallback(TaskContext &context) override;

Status UpdateIoAddr(TaskContext &context) override;

private:
Status SetMemCopyTask(const domi::TaskDef &task_def);
Status InitForDependComputeTask() override;

Status InitForDependComputeTask();

Status UpdateShapeAndDataByResultSummary(TaskContext &context);

///
/// read result summary and prepare copy task memory.
/// @param context task context
/// @param out_shape_hbm if scalar, TensorBuffer->data is null, size=0
/// @return SUCCESS:success other:failed
///
Status ReadResultSummaryAndPrepareMemory(TaskContext &context,
std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);
Status CopyDataToHbm(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);

Status UpdateShapeByHbmBuffer(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);

Status PrepareCopyInputs(const TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm);
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) override;
private:
Status SetMemCopyTask(const domi::TaskDef &task_def);

static Status EnsureSessionCreated(uint64_t session_id);
static uint64_t GetStepIdAddr(const HybridModel &model);
@@ -142,16 +152,7 @@ class AicpuTfNodeTask : public AicpuNodeTaskBase {

// just used for depend DEPEND_COMPUTE op
std::unique_ptr<TensorBuffer> copy_task_args_buf_;

std::vector<std::unique_ptr<TensorBuffer>> output_summary_;
std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;

std::unique_ptr<TensorBuffer> copy_ioaddr_dev_;

std::unique_ptr<TensorBuffer> copy_input_release_flag_dev_;
std::unique_ptr<TensorBuffer> copy_input_data_size_dev_;
std::unique_ptr<TensorBuffer> copy_input_src_dev_;
std::unique_ptr<TensorBuffer> copy_input_dst_dev_;
bool need_sync_ = false;

std::unique_ptr<TensorBuffer> copy_workspace_buf_;
@@ -170,14 +171,28 @@ class AicpuNodeTask : public AicpuNodeTaskBase {

Status LaunchTask(TaskContext &context) override;

Status TaskCallback(TaskContext &context) override;
Status CopyDataToHbm(TaskContext &context,
const std::vector<std::unique_ptr<TensorBuffer>> &out_shape_hbm) override;

Status UpdateIoAddr(TaskContext &context) override;

Status InitForDependComputeTask() override;
private:
Status SetMemCopyTask(const domi::TaskDef &task_def);

protected:
// host mem
std::unique_ptr<uint8_t[]> args_;
// host memcpy mem
std::unique_ptr<uint8_t[]> memcpy_args_;

std::string memcpy_so_name_;

std::string memcpy_kernel_name_;
// args size
uint32_t memcpy_args_size_ = 0;

std::vector<uint64_t> copy_io_addr_;
// args size
uint32_t args_size_ = 0;
};


+ 12
- 3
ge/single_op/single_op_model.cc View File

@@ -333,7 +333,7 @@ Status SingleOpModel::BuildTaskList(StreamResource *stream_resource, SingleOp &s
single_op.tasks_.emplace_back(tbe_task);
} else if (kernel_type == ccKernelType::AI_CPU || kernel_type == ccKernelType::CUST_AI_CPU) {
GELOGD("Building AICPU_CC task");
OpTask *task = nullptr;
AiCpuCCTask *task = nullptr;
uint64_t singleop_kernel_id = aicpu_kernel_id++;
GELOGI("Build singleOp CCTask, kernel_id = %lu", singleop_kernel_id);
GE_CHK_STATUS_RET_NOLOG(BuildCpuKernelTask(task_def.kernel(), &task, singleop_kernel_id));
@@ -489,7 +489,7 @@ Status SingleOpModel::BuildKernelExTask(const domi::KernelExDef &kernel_def, AiC
return SUCCESS;
}

Status SingleOpModel::BuildCpuKernelTask(const domi::KernelDef &kernel_def, OpTask **task, uint64_t kernel_id) {
Status SingleOpModel::BuildCpuKernelTask(const domi::KernelDef &kernel_def, AiCpuCCTask **task, uint64_t kernel_id) {
const auto &context = kernel_def.context();
auto iter = op_list_.find(context.op_index());
if (iter == op_list_.end()) {
@@ -611,10 +611,19 @@ Status SingleOpModel::BuildTaskListForDynamicOp(StreamResource *stream_resource,
} else if (lib_name == kEngineNameAiCpu) {
const auto &task_def = task_defs[0];
GELOGD("Building AICPU_CC task");
OpTask *task = nullptr;
AiCpuCCTask *task = nullptr;
uint64_t dynamic_singleop_kernel_id = aicpu_kernel_id++;
GELOGI("Build dynamic singleOp CCTask, kernel_id = %lu", dynamic_singleop_kernel_id);
GE_CHK_STATUS_RET_NOLOG(BuildCpuKernelTask(task_def.kernel(), &task, dynamic_singleop_kernel_id));
if (task->GetUnknownType() == DEPEND_COMPUTE) {
if (task_defs.size() < kNumTaskWithMemCpyTask) {
GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Task]The copy task of the fourth operator was not found.");
REPORT_INNER_ERROR("E19999", "The copy task of the fourth operator was not found.");
return ACL_ERROR_GE_PARAM_INVALID;
}
const TaskDef &copy_task_def = task_defs[1];
GE_CHK_STATUS_RET_NOLOG(task->SetMemCopyTask(copy_task_def.kernel()));
}
task->SetModelArgs(model_name_, model_id_);
single_op.op_task_.reset(task);
} else if (lib_name == kEngineNameAiCpuTf) {


+ 1
- 1
ge/single_op/single_op_model.h View File

@@ -71,7 +71,7 @@ class SingleOpModel {
Status BuildKernelTask(const domi::TaskDef &task_def, TbeOpTask **task);
Status BuildAtomicTask(const domi::TaskDef &task_def, AtomicAddrCleanOpTask **task);
Status BuildKernelExTask(const domi::KernelExDef &kernel_def, AiCpuTask **task, uint64_t kernel_id);
Status BuildCpuKernelTask(const domi::KernelDef &kernel_def, OpTask **task, uint64_t kernel_id);
Status BuildCpuKernelTask(const domi::KernelDef &kernel_def, AiCpuCCTask **task, uint64_t kernel_id);

static void ParseOpModelParams(ModelHelper &model_helper, SingleOpModelParam &param);
void ParseArgTable(OpTask *task, SingleOp &op);


+ 1
- 4
ge/single_op/task/aicpu_kernel_task_builder.cc View File

@@ -102,11 +102,8 @@ Status AiCpuCCTaskBuilder::BuildTask(AiCpuCCTask &task, uint64_t kernel_id, cons
return ret;
}
GE_CHK_STATUS_RET(task.SetInputConst(), "[Set][InputConst] failed.");
GE_CHK_STATUS_RET(task.InitForSummaryAndCopy(), "[Init][SummaryAndCopy] failed.");

if (task.GetUnknownType() == DEPEND_COMPUTE) {
GELOGE(FAILED, "[Get][UnknownType] is depend compute, it's not supported now.");
return FAILED;
}
auto aicpu_param_head = reinterpret_cast<aicpu::AicpuParamHead *>(task.args_.get());
if (task.ext_info_addr_dev_ != nullptr) {
aicpu_param_head->extInfoLength = kernel_ext_info.size();


+ 142
- 33
ge/single_op/task/op_task.cc View File

@@ -567,6 +567,16 @@ AiCpuBaseTask::~AiCpuBaseTask() {
if (rt_event_ != nullptr) {
(void)rtEventDestroy(rt_event_);
}
FreeHbm(copy_input_release_flag_dev_);
FreeHbm(copy_input_data_size_dev_);
FreeHbm(copy_input_src_dev_);
FreeHbm(copy_input_dst_dev_);
for (auto summary : output_summary_) {
FreeHbm(summary);
}
for (auto out_shape : out_shape_hbm_) {
FreeHbm(out_shape);
}
}

Status AiCpuBaseTask::UpdateEventIdForBlockingAicpuOp() {
@@ -878,17 +888,7 @@ AiCpuTask::~AiCpuTask() {
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) {
@@ -926,7 +926,7 @@ Status AiCpuTask::LaunchKernel(rtStream_t stream) {
return SUCCESS;
}

Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
Status AiCpuBaseTask::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;
@@ -955,7 +955,6 @@ Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
}

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,
@@ -967,7 +966,7 @@ Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
return SUCCESS;
}

Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
Status AiCpuBaseTask::ReadResultSummaryAndPrepareMemory() {
for (size_t i = 0; i < num_outputs_; ++i) {
auto &result_summary = output_summary_host_[i];

@@ -984,6 +983,19 @@ Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
return SUCCESS;
}

Status AiCpuCCTask::CopyDataToHbm(vector<DataBuffer> &outputs,
rtStream_t stream) {
GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
auto ret = rtCpuKernelLaunchWithFlag(static_cast<const void *>(memcpy_so_name_.data()),
static_cast<const void *>(memcpy_kernel_name_.data()),
block_dim_, memcpy_args_.get(), memcpy_args_size_,
nullptr, stream, RT_KERNEL_DEFAULT);
GE_CHK_RT_RET(ret);
GE_CHK_RT_RET(rtStreamSynchronize(stream));
return SUCCESS;
}

Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
rtStream_t stream) {
GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
@@ -994,7 +1006,7 @@ Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
return SUCCESS;
}

Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
Status AiCpuBaseTask::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;
@@ -1023,9 +1035,9 @@ Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
}


Status AiCpuTask::UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &outputs,
rtStream_t stream) {
Status AiCpuBaseTask::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;
@@ -1151,6 +1163,119 @@ Status AiCpuTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
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));
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 AiCpuCCTask::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));

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_));
return SUCCESS;
}

Status AiCpuCCTask::SetMemCopyTask(const domi::KernelDef &kernel_def) {
auto &memcpy_args = kernel_def.args();
memcpy_args_size_ = kernel_def.args_size();
memcpy_so_name_ = kernel_def.so_name();
memcpy_kernel_name_ = kernel_def.kernel_name();
if (memcpy_args.size() != memcpy_args_size_) {
REPORT_INNER_ERROR("E19999", "MemCopy task def args.size=%zu, but args_size=%u not equal.",
memcpy_args.size(), memcpy_args_size_);
GELOGE(FAILED, "[Check][Size]MemCopy task def args.size=%zu, but args_size=%u not equal.",
memcpy_args.size(), memcpy_args_size_);
return FAILED;
}
if (memcpy_args_size_ < sizeof(aicpu::AicpuParamHead)) {
REPORT_INNER_ERROR("E19999",
"Task def args_size=%u is less than aicpu param head len=%zu.",
memcpy_args_size_, sizeof(aicpu::AicpuParamHead));
GELOGE(FAILED,
"[Check][Size] Task def args_size=%u is less than aicpu param head len=%zu.",
memcpy_args_size_, sizeof(aicpu::AicpuParamHead));
return FAILED;
}

memcpy_args_.reset(new(std::nothrow) uint8_t[memcpy_args_size_]());
if (memcpy_args_ == nullptr) {
REPORT_INNER_ERROR("E19999", "new memory failed for Node[MemCopy], task_size[%u].",
memcpy_args_size_);
GELOGE(FAILED, "[Malloc][Memory] failed for Node[MemCopy], task_size[%u].",
memcpy_args_size_);
return FAILED;
}

errno_t sec_ret = memcpy_s(memcpy_args_.get(), memcpy_args_size_, memcpy_args.c_str(), memcpy_args.size());
if (sec_ret != EOK) {
REPORT_INNER_ERROR("E19999",
"memcpy_s argc_ failed for Node[MemCopy], ret: %d", sec_ret);
GELOGE(INTERNAL_ERROR,
"[Update][args] failed for Node[MemCopy], ret: %d", sec_ret);
return sec_ret;
}
auto memcpy_param_head = reinterpret_cast<aicpu::AicpuParamHead *>(memcpy_args_.get());
uint32_t memcpy_io_num = memcpy_param_head->ioAddrNum;
auto memcpy_io_addr = memcpy_args_.get() + sizeof(aicpu::AicpuParamHead);
// if has input and output, need copy to ioaddr
int cpy_ret = memcpy_s(memcpy_io_addr, memcpy_args_size_ - sizeof(aicpu::AicpuParamHead),
&copy_io_addr_[0], sizeof(uint64_t) * memcpy_io_num);
if (cpy_ret != 0) {
REPORT_INNER_ERROR("E19999", "Node[Memcpoy] memcpy io addr to AicpuParamHead failed,"
"ret=%d, args_size=%u, io nums=%u.",
cpy_ret, memcpy_args_size_, memcpy_io_num);
GELOGE(INTERNAL_ERROR, "[Update][io_addr]Node[MemCopy] memcpy io addr to AicpuParamHead failed,"
"ret=%d, args_size=%u, io nums=%u.",
cpy_ret, memcpy_args_size_, memcpy_io_num);
return INTERNAL_ERROR;
}
GELOGD("Set memcpy task for node[MemCopy] successfully.");
return SUCCESS;
}

Status AiCpuBaseTask::UpdateArgTable(const SingleOpModelParam &param) {
// aicpu do not have workspace, for now
return DoUpdateArgTable(param, false);
@@ -1209,22 +1334,6 @@ Status AiCpuCCTask::LaunchKernel(rtStream_t stream) {
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_;


+ 37
- 29
ge/single_op/task/op_task.h View File

@@ -77,12 +77,12 @@ class OpTask {
class TbeOpTask : public OpTask {
public:
~TbeOpTask() override;
Status LaunchKernel(rtStream_t stream) override;
Status 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) override;
Status LaunchKernel(rtStream_t stream) override;
void GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) override;
void SetSmDesc(void *sm_desc);
void SetStubFunc(const std::string &name, const void *stub_func);
@@ -167,7 +167,6 @@ class AiCpuBaseTask : public OpTask {
UnknowShapeOpType GetUnknownType() const { return unknown_type_; }
Status UpdateArgTable(const SingleOpModelParam &param) override;
const std::string &GetTaskType() const override;

protected:
Status UpdateIoAddr(const std::vector<DataBuffer> &inputs, const std::vector<DataBuffer> &outputs);
Status SetInputConst();
@@ -178,6 +177,16 @@ class AiCpuBaseTask : public OpTask {
rtStream_t stream);
Status UpdateOutputShape(vector<GeTensorDesc> &output_desc);
Status UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc);
Status UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &outputs,
rtStream_t stream);
Status ReadResultSummaryAndPrepareMemory();

Status PrepareCopyInputs(vector<DataBuffer> &outputs);

Status UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc);

virtual Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream) = 0;
// for blocking aicpu op
Status DistributeWaitTaskForAicpuBlockingOp(rtStream_t stream);
Status UpdateEventIdForBlockingAicpuOp();
@@ -193,6 +202,15 @@ class AiCpuBaseTask : public OpTask {
// for blocking aicpu op
bool is_blocking_aicpu_op_ = false;
rtEvent_t rt_event_ = nullptr;
std::vector<void *> output_summary_;
std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;

void *copy_input_release_flag_dev_ = nullptr;
void *copy_input_data_size_dev_ = nullptr;
void *copy_input_src_dev_ = nullptr;
void *copy_input_dst_dev_ = nullptr;

vector<void *> out_shape_hbm_;
};

class AiCpuTask : public AiCpuBaseTask {
@@ -202,7 +220,6 @@ class AiCpuTask : public AiCpuBaseTask {

Status LaunchKernel(rtStream_t stream) override;
void GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) override;

Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
const std::vector<DataBuffer> &input_buffers,
std::vector<GeTensorDesc> &output_desc,
@@ -213,15 +230,7 @@ class AiCpuTask : public AiCpuBaseTask {
private:
// for copy task.
Status InitForSummaryAndCopy();
Status UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
vector<DataBuffer> &outputs,
rtStream_t stream);
Status ReadResultSummaryAndPrepareMemory();

Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream);
Status PrepareCopyInputs(vector<DataBuffer> &outputs);

Status UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc);
Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream) override;

friend class AiCpuTaskBuilder;
void *workspace_addr_ = nullptr;
@@ -241,17 +250,8 @@ class AiCpuTask : public AiCpuBaseTask {
void *copy_task_args_buf_ = nullptr;
void *copy_workspace_buf_ = nullptr;

std::vector<void *> output_summary_;
std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;

void *copy_ioaddr_dev_ = nullptr;

void *copy_input_release_flag_dev_ = nullptr;
void *copy_input_data_size_dev_ = nullptr;
void *copy_input_src_dev_ = nullptr;
void *copy_input_dst_dev_ = nullptr;

vector<void *> out_shape_hbm_;
uint64_t kernel_id_ = 0;
};

@@ -261,8 +261,13 @@ class AiCpuCCTask : public AiCpuBaseTask {
~AiCpuCCTask() override;
AiCpuCCTask(const AiCpuCCTask &) = delete;
AiCpuCCTask &operator=(const AiCpuCCTask &) = delete;
Status SetMemCopyTask(const domi::KernelDef &kernel_def);
Status LaunchKernel(rtStream_t stream) override;
Status 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) override;
void GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) override;
const void *GetArgs() const;
void SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size);
@@ -270,13 +275,9 @@ class AiCpuCCTask : public AiCpuBaseTask {
void SetkernelName(const std::string &kernel_Name);
void SetIoAddr(uintptr_t *io_addr);
size_t GetArgSize() const;

Status 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) override;

private:
Status InitForSummaryAndCopy();
Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream) override;
private:
friend class AiCpuCCTaskBuilder;
std::string so_name_;
@@ -290,6 +291,13 @@ private:
uint32_t dump_flag_ = RT_KERNEL_DEFAULT;
std::string op_type_;
uint64_t kernel_id_ = 0;
// host memcpy mem
std::unique_ptr<uint8_t[]> memcpy_args_;
std::string memcpy_so_name_;
std::string memcpy_kernel_name_;
std::vector<uint64_t> copy_io_addr_;
// args size
uint32_t memcpy_args_size_ = 0;
};

class MemcpyAsyncTask : public OpTask {


+ 136
- 9
tests/ut/ge/hybrid/node_executor/aicpu/aicpu_node_executor_unittest.cc View File

@@ -152,20 +152,147 @@ TEST_F(UtestAicpuNodeExecutor, aicpu_tf_node_task) {
domi::TaskDef task_def2;
task_def2.set_type(RT_MODEL_TASK_ALL_KERNEL);
task_def2.mutable_kernel()->set_args(reinterpret_cast<const char *>(&args), args.head.length);
task_def2.mutable_kernel()->set_args_size(args.head.length);
domi::KernelDef *kernel_def = task_def2.mutable_kernel();
kernel_def->set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def->set_args_size(args.head.length);
AicpuExtInfo aicpu_ext_info2;
aicpu_ext_info2.infoType = aicpu::FWKAdapter::FWK_ADPT_EXT_SHAPE_TYPE;
aicpu_ext_info2.infoLen = sizeof(int32_t);
memcpy_s(aicpu_ext_info2.infoMsg, sizeof(int32_t), &type, sizeof(int32_t));
char *ext_mem2 = (char*)malloc(sizeof(AicpuExtInfo) + sizeof(int32_t));
memcpy_s(ext_mem2, sizeof(AicpuExtInfo) + sizeof(int32_t), &aicpu_ext_info2, sizeof(AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info(ext_mem2, sizeof(AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info_size(sizeof(AicpuExtInfo) + sizeof(int32_t));
hybrid_model.task_defs_[node] = std::vector<domi::TaskDef>({task_def2, task_def2});
AicpuNodeTask aicpu_node_task(node_item, task_def2);
ASSERT_EQ(aicpu_node_task.Init(hybrid_model), SUCCESS);
ASSERT_EQ(aicpu_node_task.UpdateIoAddr(*node_state->GetTaskContext()), SUCCESS);
ASSERT_EQ(aicpu_node_task.LaunchTask(*node_state->GetTaskContext()), SUCCESS);
node_item->is_dynamic = false;
ASSERT_EQ(aicpu_node_task.UpdateIoAddr(*node_state->GetTaskContext()), SUCCESS);
//kernel_ex_def->set_allocated_kernel_ext_info(nullptr);
free(ext_mem);
free(ext_mem2);
}
hybrid_model.task_defs_[node] = std::vector<domi::TaskDef>({task_def2});
TEST_F(UtestAicpuNodeExecutor, aicpu_memcopy_task) {
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test");
GeModelPtr ge_sub_model = std::make_shared<GeModel>();
GeRootModelPtr ge_root_model = std::make_shared<GeRootModel>(graph);
ge_root_model->SetModelName("test_name");
ge_root_model->SetSubgraphInstanceNameToModel("sub", ge_sub_model);
HybridModel hybrid_model(ge_root_model);
NodePtr node = CreateNode(graph, "frameworkop", FRAMEWORK_OP_TYPE, 4, 2);
std::unique_ptr<NodeItem> new_node;
ASSERT_EQ(NodeItem::Create(node, new_node), SUCCESS);
NodeItem *node_item = new_node.get();
AicpuTaskStruct args;
args.head.length = sizeof(args);
args.head.ioAddrNum = 6;
domi::TaskDef task_def;
task_def.set_type(RT_MODEL_TASK_ALL_KERNEL);
domi::KernelDef *kernel_def = task_def.mutable_kernel();
kernel_def->set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def->set_args_size(args.head.length);
node_item->num_outputs = 0;
AicpuNodeTask aicpu_node_task(node_item, task_def);
ASSERT_EQ(aicpu_node_task.Init(hybrid_model), FAILED);
ASSERT_EQ(aicpu_node_task.LaunchTask(*node_state->GetTaskContext()), SUCCESS);
ASSERT_EQ(aicpu_node_task.SetMemCopyTask(task_def), SUCCESS);
node_item->num_outputs = 1;
AicpuNodeTask aicpu_node_task2(node_item, task_def);
ASSERT_EQ(aicpu_node_task2.SetMemCopyTask(task_def), INTERNAL_ERROR);
kernel_def->set_args_size(0);
ASSERT_EQ(aicpu_node_task2.SetMemCopyTask(task_def), FAILED);
char* args2 = "123";
kernel_def->set_args(reinterpret_cast<const char *>(&args2), 3);
kernel_def->set_args_size(3);
ASSERT_EQ(aicpu_node_task2.SetMemCopyTask(task_def), FAILED);
}
TEST_F(UtestAicpuNodeExecutor, aicpu_copy_data_to_hbm) {
ComputeGraphPtr graph = std::make_shared<ComputeGraph>("test");
GeModelPtr ge_sub_model = std::make_shared<GeModel>();
GeRootModelPtr ge_root_model = std::make_shared<GeRootModel>(graph);
ge_root_model->SetModelName("test_name");
ge_root_model->SetSubgraphInstanceNameToModel("sub", ge_sub_model);
HybridModel hybrid_model(ge_root_model);
//kernel_ex_def->set_allocated_kernel_ext_info(nullptr);
NodePtr node = CreateNode(graph, "frameworkop", FRAMEWORK_OP_TYPE, 4, 2);
free(ext_mem);
std::unique_ptr<NodeItem> new_node;
ASSERT_EQ(NodeItem::Create(node, new_node), SUCCESS);
NodeItem *node_item = new_node.get();
hybrid_model.node_items_[node] = std::move(new_node);
node_item->input_start = 0;
node_item->output_start = 0;
node_item->is_dynamic = true;
node_item->shape_inference_type = DEPEND_COMPUTE;
node_item->num_outputs = 2;
GraphItem graph_item;
graph_item.node_items_.emplace_back(node_item);
graph_item.total_inputs_ = 4;
graph_item.total_outputs_ = 2;
GraphExecutionContext graph_context;
SubgraphContext subgraph_context(&graph_item, &graph_context);
ASSERT_EQ(subgraph_context.Init(), SUCCESS);
graph_context.callback_manager = std::unique_ptr<CallbackManager>(new CallbackManager());
auto node_state = subgraph_context.GetOrCreateNodeState(node_item);
ASSERT_NE(node_state, nullptr);
for (int i=0; i<4; ++i) {
uint64_t value_0 = 512;
TensorValue in_tensor0(&value_0, sizeof(value_0));
subgraph_context.SetInput(*node_item, 0, in_tensor0);
}
uint64_t value_0 = 512;
TensorValue out_tensor0(&value_0, sizeof(value_0));
subgraph_context.SetOutput(*node_item, 0, out_tensor0);
uint64_t value_1 = 512;
TensorValue out_tensor1(&value_1, sizeof(value_1));
subgraph_context.SetOutput(*node_item, 1, out_tensor1);
// task
domi::TaskDef task_def;
AicpuTaskStruct args;
args.head.length = sizeof(args);
args.head.ioAddrNum = 6;
task_def.set_type(RT_MODEL_TASK_ALL_KERNEL);
domi::KernelDef *kernel_def = task_def.mutable_kernel();
kernel_def->set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def->set_args_size(args.head.length);
AicpuExtInfo aicpu_ext_info;
aicpu_ext_info.infoType = aicpu::FWKAdapter::FWK_ADPT_EXT_SHAPE_TYPE;
aicpu_ext_info.infoLen = sizeof(int32_t);
int32_t type = node_item->shape_inference_type;
memcpy_s(aicpu_ext_info.infoMsg, sizeof(int32_t), &type, sizeof(int32_t));
char *ext_mem = (char*)malloc(sizeof(AicpuExtInfo) + sizeof(int32_t));
memcpy_s(ext_mem, sizeof(AicpuExtInfo) + sizeof(int32_t), &aicpu_ext_info, sizeof(AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info(ext_mem, sizeof(AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info_size(sizeof(AicpuExtInfo) + sizeof(int32_t));
hybrid_model.task_defs_[node] = std::vector<domi::TaskDef>({task_def, task_def});
AicpuNodeTask aicpu_node_task(node_item, task_def);
std::vector<std::unique_ptr<TensorBuffer>> out_shape_hbm;
ASSERT_EQ(aicpu_node_task.Init(hybrid_model), SUCCESS);
for (int i = 0; i < node_item->num_outputs; i++) {
auto &summary = aicpu_node_task.output_summary_host_[i];
summary.shape_data_ptr = 0;
summary.shape_data_size = 1;
summary.raw_data_ptr = 0;
summary.raw_data_size = 1;
}
for (int i = 0; i < node_item->num_outputs; i++) {
std::unique_ptr<TensorBuffer> shape_buffer;
AicpuNodeTask::AllocTensorBuffer(1, shape_buffer);
out_shape_hbm.emplace_back(std::move(shape_buffer));
}
ASSERT_EQ(aicpu_node_task.CopyDataToHbm(*node_state->GetTaskContext(), out_shape_hbm), SUCCESS);
free(ext_mem);
}
TEST_F(UtestAicpuNodeExecutor, aicpu_blocking_node_task) {
@@ -231,7 +358,7 @@ TEST_F(UtestAicpuNodeExecutor, aicpu_blocking_node_task) {
kernel_def.set_args_size(args.head.length);
domi::KernelDef *kernel_def_tmp = task_def.mutable_kernel();
*kernel_def_tmp = kernel_def;
hybrid_model.task_defs_[node] = std::vector<domi::TaskDef>({task_def});
AicpuNodeTask aicpu_node_task(node_item, task_def);
ASSERT_EQ(aicpu_node_task.Init(hybrid_model), SUCCESS);
ASSERT_EQ(aicpu_node_task.LaunchTask(*node_state->GetTaskContext()), SUCCESS);
@@ -314,7 +441,7 @@ TEST_F(UtestAicpuNodeExecutor, aicpu_blocking_node_task_fail) {
kernel_def.set_args_size(args.head.length);
domi::KernelDef *kernel_def_tmp = task_def.mutable_kernel();
*kernel_def_tmp = kernel_def;
hybrid_model.task_defs_[node] = std::vector<domi::TaskDef>({task_def});
AicpuNodeTask aicpu_node_task(node_item, task_def);
RTS_STUB_RETURN_VALUE(rtGetDevice, rtError_t, 0x78000001);


+ 71
- 1
tests/ut/ge/single_op/single_op_model_unittest.cc View File

@@ -23,6 +23,7 @@
#include "graph/utils/graph_utils.h"
#include "runtime/rt.h"
#include "single_op/single_op_model.h"
#include "aicpu/common/aicpu_task_struct.h"
#include "single_op/task/tbe_task_builder.h"
#include "single_op/task/rts_kernel_task_builder.h"
#include "single_op/task/op_task.h"
@@ -43,6 +44,10 @@ constexpr char const *kAttrSupportDynamicShape = "support_dynamicshape";
const char *const kEngineNameAiCore = "AIcoreEngine";
const char *const kEngineNameAiCpu = "aicpu_ascend_kernel";
const char *const kEngineNameAiCpuTf = "aicpu_tf_kernel";
struct AicpuTaskStruct {
aicpu::AicpuParamHead head;
uint64_t io_addrp[6];
}__attribute__((packed));
} // namespace

class UtestSingleOpModel : public testing::Test {
@@ -315,7 +320,7 @@ TEST_F(UtestSingleOpModel, BuildTaskList) {
ASSERT_EQ(mem_task.LaunchKernel(0), SUCCESS);
}

TEST_F(UtestSingleOpModel, build_dynamic_task) {
TEST_F(UtestSingleOpModel, build_dynamic_task01) {
ComputeGraphPtr graph = make_shared<ComputeGraph>("single_op");
GeModelPtr ge_model = make_shared<GeModel>();
ge_model->SetGraph(GraphUtils::CreateGraphFromComputeGraph(graph));
@@ -366,3 +371,68 @@ TEST_F(UtestSingleOpModel, build_dynamic_task) {
op_desc->SetOpKernelLibName(kEngineNameAiCpu);
model.BuildTaskListForDynamicOp(res, single_op);
}
TEST_F(UtestSingleOpModel, build_dynamic_task02) {
ComputeGraphPtr graph = make_shared<ComputeGraph>("single_op");
GeModelPtr ge_model = make_shared<GeModel>();
ge_model->SetGraph(GraphUtils::CreateGraphFromComputeGraph(graph));
shared_ptr<domi::ModelTaskDef> model_task_def = make_shared<domi::ModelTaskDef>();
ge_model->SetModelTaskDef(model_task_def);
AicpuTaskStruct args;
args.head.length = sizeof(args);
args.head.ioAddrNum = 6;
domi::TaskDef *task_def = model_task_def->add_task();
task_def->set_type(RT_MODEL_TASK_KERNEL);
domi::KernelDef *kernel_def = task_def->mutable_kernel();
kernel_def->set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def->set_args_size(args.head.length);
ge::hybrid::AicpuExtInfo aicpu_ext_info;
aicpu_ext_info.infoType = aicpu::FWKAdapter::FWK_ADPT_EXT_SHAPE_TYPE;
aicpu_ext_info.infoLen = sizeof(int32_t);
int32_t type = ge::DEPEND_COMPUTE;
memcpy_s(aicpu_ext_info.infoMsg, sizeof(int32_t), &type, sizeof(int32_t));
char *ext_mem = (char*)malloc(sizeof(ge::hybrid::AicpuExtInfo) + sizeof(int32_t));
memcpy_s(ext_mem, sizeof(ge::hybrid::AicpuExtInfo) + sizeof(int32_t), &aicpu_ext_info,
sizeof(ge::hybrid::AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info(ext_mem, sizeof(ge::hybrid::AicpuExtInfo) + sizeof(int32_t));
kernel_def->set_kernel_ext_info_size(sizeof(ge::hybrid::AicpuExtInfo) + sizeof(int32_t));
domi::KernelContext *context = kernel_def->mutable_context();
context->set_kernel_type(6); // ccKernelType::AI_CPU

string model_data_str = "dynamic_model";
SingleOpModel model("model", model_data_str.c_str(), model_data_str.size());
std::mutex stream_mu;
rtStream_t stream = nullptr;
rtStreamCreate(&stream, 0);
DynamicSingleOp single_op(0, &stream_mu, stream);
model.model_helper_.model_ = ge_model;
auto op_desc = std::make_shared<ge::OpDesc>("add", "Add");
AttrUtils::SetInt(op_desc, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, ge::DEPEND_COMPUTE);
NodePtr node = graph->AddNode(op_desc);
model.op_list_[0] = node;
StreamResource *res = new (std::nothrow) StreamResource(1);

ASSERT_EQ(model.ParseTasks(), SUCCESS);
model.node_tasks_[node] = { *task_def, *task_def };
op_desc->SetOpKernelLibName(kEngineNameAiCpu);
model.BuildTaskListForDynamicOp(res, single_op);
model.node_tasks_[node] = { *task_def};
model.BuildTaskListForDynamicOp(res, single_op);
}

TEST_F(UtestSingleOpModel, build_memcpoy_task) {
AicpuTaskStruct args;
args.head.length = sizeof(args);
args.head.ioAddrNum = 6;
domi::KernelDef kernel_def;
kernel_def.set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def.set_args_size(args.head.length);
AiCpuCCTask aicpu_task;
ASSERT_EQ(aicpu_task.SetMemCopyTask(kernel_def), INTERNAL_ERROR);
kernel_def.set_args_size(0);
ASSERT_EQ(aicpu_task.SetMemCopyTask(kernel_def), FAILED);
char* args2 = "123";
kernel_def.set_args(reinterpret_cast<const char *>(&args2), 3);
kernel_def.set_args_size(3);
ASSERT_EQ(aicpu_task.SetMemCopyTask(kernel_def), FAILED);
}

+ 48
- 1
tests/ut/ge/single_op/single_op_task_unittest.cc View File

@@ -16,7 +16,7 @@

#include <gtest/gtest.h>
#include <vector>
#include <iostream>
#include "graph/load/model_manager/model_utils.h"
#include "graph/utils/graph_utils.h"
#include "hybrid/node_executor/aicpu/aicpu_ext_info.h"
@@ -25,6 +25,7 @@
#define protected public
#define private public
#include "single_op/single_op_model.h"
#include "aicpu/common/aicpu_task_struct.h"
#include "single_op/task/tbe_task_builder.h"
#include "single_op/task/op_task.h"
#include "single_op/task/tbe_task_builder.h"
@@ -38,6 +39,13 @@ using namespace testing;
using namespace ge;
using namespace optiling;

namespace {
struct AicpuTaskStruct {
aicpu::AicpuParamHead head;
uint64_t io_addrp[3];
}__attribute__((packed));
} // namespace

class UtestSingleOpTask : public testing::Test {
protected:
void SetUp() {
@@ -196,6 +204,45 @@ TEST_F(UtestSingleOpTask, test_atomic_exec) {
task.CalcTilingInfo(run_info);
}

TEST_F(UtestSingleOpTask, test_aicpu_task_launch_kernel) {
AiCpuCCTask task;
rtStream_t stream;
ASSERT_EQ(rtStreamCreate(&stream, 0), RT_ERROR_NONE);
task.num_inputs_ = 2;
task.num_outputs_ = 1;
task.input_is_const_ = {true, false};
int total_addr = 3;
uint32_t* addrs[total_addr] = {nullptr, nullptr, nullptr};
task.io_addr_ = reinterpret_cast<uintptr_t*>(addrs);
task.io_addr_num_ = total_addr;
vector<DataBuffer> outputs(1, DataBuffer());
outputs[0].data = 0;
task.unknown_type_ = ge::DEPEND_COMPUTE;
ASSERT_EQ(task.InitForSummaryAndCopy(), SUCCESS);
auto &summary = task.output_summary_host_[0];
summary.shape_data_ptr = 0;
summary.shape_data_size = 1;
summary.raw_data_ptr = 0;
summary.raw_data_size = 1;
void *shape_buffer = nullptr;
rtMalloc(&shape_buffer, 1, RT_MEMORY_HBM);
task.out_shape_hbm_.emplace_back(shape_buffer);
task.memcpy_so_name_ = "libcpu_kernel.so";
task.memcpy_kernel_name_ = "RunCpuKernel";
AicpuTaskStruct args;
args.head.length = sizeof(args);
args.head.ioAddrNum = 3;
domi::TaskDef task_def;
domi::KernelDef *kernel_def = task_def.mutable_kernel();
kernel_def->set_args(reinterpret_cast<const char *>(&args), args.head.length);
kernel_def->set_args_size(args.head.length);
auto &memcpy_args = kernel_def->args();
task.memcpy_args_size_ = kernel_def->args_size();
task.memcpy_args_.reset(new(std::nothrow) uint8_t[task.memcpy_args_size_]());
memcpy_s(task.memcpy_args_.get(), task.memcpy_args_size_, memcpy_args.c_str(), memcpy_args.size());
ASSERT_EQ(task.CopyDataToHbm(outputs, stream), SUCCESS);
}

TEST_F(UtestSingleOpTask, test_aicpu_task_update_io_addr) {
AiCpuCCTask task;
task.num_inputs_ = 2;


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