@@ -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), | |||
©_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"); | |||
@@ -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; | |||
}; | |||
@@ -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 ©_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) { | |||
@@ -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 ¶m); | |||
void ParseArgTable(OpTask *task, SingleOp &op); | |||
@@ -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(); | |||
@@ -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(©_input_release_flag_dev_, copy_input_buf_len, RT_MEMORY_HBM)); | |||
GE_CHK_RT_RET(rtMalloc(©_input_data_size_dev_, copy_input_buf_len, RT_MEMORY_HBM)); | |||
GE_CHK_RT_RET(rtMalloc(©_input_src_dev_, copy_input_buf_len, RT_MEMORY_HBM)); | |||
GE_CHK_RT_RET(rtMalloc(©_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), | |||
©_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 ¶m) { | |||
// 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_; | |||
@@ -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 ¶m) 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 { | |||
@@ -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); | |||
@@ -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); | |||
} |
@@ -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; | |||