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@ -20,6 +20,11 @@
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#include "graph/utils/type_utils.h"
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#include "graph/ge_context.h"
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#include "omm/csa_interact.h"
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#include "graph/debug/ge_attr_define.h"
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#include "graph/manager/graph_caching_allocator.h"
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#include "graph/manager/graph_mem_allocator.h"
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#include "graph/manager/rdma_pool_allocator.h"
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#include "graph/manager/host_mem_allocator.h"
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namespace ge {
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namespace hybrid {
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@ -27,6 +32,9 @@ namespace {
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const int kDataOutputIndex = 0;
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const size_t kMinimumPiplineStages = 2;
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const int kDefaultLoopCount = 10;
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//const uint32_t kPlacementHost = 0;
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const uint32_t kPlacementDevice = 1;
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const char *const kLazyRecompile = "lazy_recompile";
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}
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HybridModelAsyncExecutor::HybridModelAsyncExecutor(HybridModel *model)
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: model_(model), run_flag_(false), data_dumper_(nullptr) {
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@ -71,6 +79,8 @@ Status HybridModelAsyncExecutor::Start(const std::shared_ptr<ModelListener> &lis
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GetThreadLocalContext() = *executor_->GetContext()->ge_context;
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GetContext().SetSessionId(executor_->GetContext()->session_id);
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GetContext().SetContextId(executor_->GetContext()->context_id);
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GE_CHECK_NOTNULL(executor_->GetContext()->ge_context);
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GetThreadLocalContext() = *executor_->GetContext()->ge_context;
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return RunInternal();
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});
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@ -198,7 +208,7 @@ Status HybridModelAsyncExecutor::HandleResult(Status exec_ret,
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HybridModelExecutor::ExecuteArgs &args,
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OutputData *output_data) {
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GELOGD("Start to handle result. model id = %u, data index = %u, execution ret = %u", model_id_, data_id, exec_ret);
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std::vector<ge::OutputTensorInfo> output_tensor_info_list;
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std::vector<ge::Tensor> output_tensor_info_list;
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if (args.is_eos) {
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GELOGI("End of sequence, model id = %u", model_id_);
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GE_CHK_STATUS_RET_NOLOG(OnComputeDone(data_id, END_OF_SEQUENCE, output_tensor_info_list));
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@ -369,7 +379,7 @@ Status HybridModelAsyncExecutor::InitInputDesc() {
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}
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Status HybridModelAsyncExecutor::OnComputeDone(uint32_t data_index, uint32_t result_code,
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std::vector<ge::OutputTensorInfo> &outputs) {
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std::vector<ge::Tensor> &outputs) {
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GELOGD("OnComputeDone. model id = %u, data index = %u, execution ret = %u", model_id_, data_index, result_code);
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if (listener_ != nullptr) {
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GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_index, result_code, outputs),
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@ -381,7 +391,7 @@ Status HybridModelAsyncExecutor::OnComputeDone(uint32_t data_index, uint32_t res
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Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &args,
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OutputData *output_data,
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std::vector<ge::OutputTensorInfo> &outputs) {
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std::vector<ge::Tensor> &outputs) {
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// copy output data from op to designated position
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std::vector<ConstGeTensorDescPtr> &output_tensor_desc_list = args.output_desc;
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std::vector<TensorValue> &output_tensors = args.outputs;
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@ -396,6 +406,12 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
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}
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GELOGD("Number of outputs = %zu", output_tensor_desc_list.size());
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string execute_mode;
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auto result = ge::GetContext().GetOption(OPTION_EXEC_DYNAMIC_EXECUTE_MODE, execute_mode);
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if (result != SUCCESS) {
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GELOGW("Can not get dynamic execute mode attr");
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}
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GELOGD("The dynamic execute is %s", execute_mode.c_str());
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for (size_t i = 0; i < output_tensors.size(); ++i) {
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GELOGD("Start to process output[%zu]", i);
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auto &output_tensor = output_tensors[i];
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@ -430,11 +446,12 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
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return INTERNAL_ERROR;
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}
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ge::OutputTensorInfo output;
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output.data_type = static_cast<uint32_t>(tensor_desc->GetDataType());
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output.dims = tensor_desc->GetShape().GetDims();
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output.length = output_size;
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ge::Shape shape(tensor_desc->GetShape().GetDims());
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TensorDesc desc;
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desc.SetShape(shape);
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ge::Tensor tensor(desc);
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if (output_size > 0) {
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if (execute_mode != kLazyRecompile) {
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std::unique_ptr<uint8_t[]> data_buf(new(std::nothrow) uint8_t[output_size]);
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GE_CHECK_NOTNULL(data_buf);
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GE_CHK_RT_RET(rtMemcpy(data_buf.get(),
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@ -442,15 +459,34 @@ Status HybridModelAsyncExecutor::CopyOutputs(HybridModelExecutor::ExecuteArgs &a
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output_tensor.GetData(),
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output_size,
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RT_MEMCPY_DEVICE_TO_HOST));
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output.data = std::move(data_buf);
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output_data->blobs.emplace_back(data_buf.get(), static_cast<uint32_t>(output_size), false);
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tensor.SetData(data_buf.get(), static_cast<size_t>(output_size),[](uint8_t *ptr) {
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ptr = nullptr;});
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output_data->blobs.emplace_back(data_buf.get(), static_cast<uint32_t>(output_size), 0, false);
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} else {
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auto mem_type = output_tensor.GetMemType();
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auto deleter = [=] (uint8_t *device_data) {
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if (device_data != nullptr) {
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GELOGI("Deallocating buffer successfully. addr = %p", device_data);
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if (mem_type == RDMA_HBM) {
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MemManager::Instance().RdmaPoolInstance(RT_MEMORY_HBM).Free(device_data, device_id_);
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} else if (mem_type == HOST_DDR) {
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MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Free(device_data);
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} else {
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MemManager::Instance().CachingInstance(RT_MEMORY_HBM).Free(device_data, device_id_);
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}
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}
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};
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tensor.GetTensorDesc().SetPlacement(kPlacementDevice);
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tensor.SetData(reinterpret_cast<uint8_t *>(output_tensor.Release()),static_cast<size_t>(output_size), deleter);
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output_data->blobs.emplace_back(output_tensor.Release(), static_cast<uint32_t>(output_size), 1, false);
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}
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} else {
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GELOGW("Output[%zu] is empty. shape = [%s]", i, tensor_desc->GetShape().ToString().c_str());
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output.data = nullptr;
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output_data->blobs.emplace_back(nullptr, 0U, false);
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tensor.SetData(nullptr,0U,nullptr);
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output_data->blobs.emplace_back(nullptr, 0U, 0, false);
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}
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outputs.emplace_back(std::move(output));
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outputs.emplace_back(std::move(tensor));
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GELOGD("Output[%zu] added, type = %s, shape = [%s], size = %ld",
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i,
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TypeUtils::DataTypeToSerialString(tensor_desc->GetDataType()).c_str(),
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@ -508,7 +544,7 @@ Status HybridModelAsyncExecutor::Execute(const vector<GeTensor> &inputs, vector<
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GELOGD("Done copying input data successfully.");
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GE_CHK_STATUS_RET(executor_->Execute(args), "[Invoke][Execute] Failed, model_id = %u.", model_id_);
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std::vector<ge::OutputTensorInfo> output_tensor_info_list;
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std::vector<ge::Tensor> output_tensor_info_list;
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OutputData output_data;
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GE_CHK_STATUS_RET(CopyOutputs(args, &output_data, output_tensor_info_list),
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"[Invoke][CopyOutputs]Failed to copy outputs, model_id = %u.", model_id_);
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@ -518,15 +554,15 @@ Status HybridModelAsyncExecutor::Execute(const vector<GeTensor> &inputs, vector<
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outputs.resize(output_tensor_info_list.size());
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for (auto &out_tensor_info : output_tensor_info_list) {
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auto &ge_tensor = outputs[out_index];
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if (out_tensor_info.length > 0) {
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GE_CHK_GRAPH_STATUS_RET(ge_tensor.SetData(out_tensor_info.data.get(), out_tensor_info.length),
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if (out_tensor_info.GetSize() > 0) {
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GE_CHK_GRAPH_STATUS_RET(ge_tensor.SetData(out_tensor_info.GetData(), out_tensor_info.GetSize()),
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"Failed to set output[%d].", out_index);
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}
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ge_tensor.MutableTensorDesc() = *args.output_desc[out_index];
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GELOGD("Set output[%d], tensor size = %ld, shape = [%s]",
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out_index,
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out_tensor_info.length,
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out_tensor_info.GetSize(),
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ge_tensor.MutableTensorDesc().MutableShape().ToString().c_str());
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++out_index;
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}
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zhou_chao1993
4 years ago