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fix api

This commit is contained in:
sunsuodong 2022-06-07 00:16:21 -07:00
parent 911b7b9950
commit cf5a6e324a
9 changed files with 23 additions and 38 deletions
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1
include/api/types.h
View File

@ -364,6 +364,7 @@ constexpr char kDecModeAesGcm[] = "AES-GCM";
struct MSCallBackParam {
std::string node_name; /**< node name argument */
std::string node_type; /**< node type argument */
double execute_time; /**< gpu execute time */
};
/// \brief KernelCallBack defined the function pointer for callBack.

6
mindspore/core/utils/status.cc
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@ -157,7 +157,11 @@ std::vector<char> Status::GetErrDescriptionChar() const {
if (data_ == nullptr) {
return std::vector<char>();
}
return StringToChar(data_->err_description);
if (data_->err_description.empty()) {
return ToCString();
} else {
return StringToChar(data_->err_description);
}
}
std::vector<char> Status::CodeAsCString(enum StatusCode c) {

19
mindspore/lite/include/lite_types.h
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@ -1,5 +1,5 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
* Copyright 2020-2022 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@ -16,10 +16,7 @@
#ifndef MINDSPORE_LITE_INCLUDE_LITE_TYPES_H_
#define MINDSPORE_LITE_INCLUDE_LITE_TYPES_H_
#include <functional>
#include <memory>
#include <string>
#include <vector>
namespace mindspore {
class Allocator;
@ -62,20 +59,6 @@ typedef enum {
MT_TRAIN, /**< Both Train and Inference part of the compiled model are serialized */
MT_INFERENCE /**< Only the Inference part of the compiled model is serialized */
} ModelType;
/// \brief CallBackParam defined input arguments for callBack function.
struct CallBackParam {
std::string node_name; /**< node name argument */
std::string node_type; /**< node type argument */
};
struct GPUCallBackParam : CallBackParam {
double execute_time{-1.f};
};
/// \brief KernelCallBack defined the function pointer for callBack.
using KernelCallBack = std::function<bool(std::vector<lite::Tensor *> inputs, std::vector<lite::Tensor *> outputs,
const CallBackParam &opInfo)>;
} // namespace lite
} // namespace mindspore
#endif // MINDSPORE_LITE_INCLUDE_LITE_TYPES_H_

4
mindspore/lite/src/runtime/c_api/model_c.cc
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@ -193,7 +193,7 @@ Status ModelC::RunGraph(const MSKernelCallBackC &before, const MSKernelCallBackC
if (before != nullptr) {
before_call_back = [&](const std::vector<mindspore::lite::Tensor *> &before_inputs,
const std::vector<mindspore::lite::Tensor *> &before_outputs,
const lite::CallBackParam &call_param) {
const MSCallBackParam &call_param) {
std::vector<LiteTensorImpl> inputs_impl;
std::vector<LiteTensorImpl> outputs_impl;
std::vector<MSTensorHandle> op_inputs;
@ -218,7 +218,7 @@ Status ModelC::RunGraph(const MSKernelCallBackC &before, const MSKernelCallBackC
if (after != nullptr) {
after_call_back = [&](const std::vector<mindspore::lite::Tensor *> &after_inputs,
const std::vector<mindspore::lite::Tensor *> &after_outputs,
const lite::CallBackParam &call_param) {
const MSCallBackParam &call_param) {
std::vector<LiteTensorImpl> inputs_impl;
std::vector<LiteTensorImpl> outputs_impl;
std::vector<MSTensorHandle> op_inputs;

14
mindspore/lite/src/runtime/cxx_api/model/model_impl.cc
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@ -185,26 +185,20 @@ Status ModelImpl::RunGraph(const MSKernelCallBack &before, const MSKernelCallBac
if (before != nullptr) {
before_call_back = [&](const std::vector<mindspore::lite::Tensor *> &before_inputs,
const std::vector<mindspore::lite::Tensor *> &before_outputs,
const lite::CallBackParam &call_param) {
const MSCallBackParam &call_param) {
std::vector<MSTensor> inputs = LiteTensorsToMSTensors(before_inputs);
std::vector<MSTensor> outputs = LiteTensorsToMSTensors(before_outputs);
MSCallBackParam mscall_param;
mscall_param.node_name = call_param.node_name;
mscall_param.node_type = call_param.node_type;
return before(inputs, outputs, mscall_param);
return before(inputs, outputs, call_param);
};
}
if (after != nullptr) {
after_call_back = [&](const std::vector<mindspore::lite::Tensor *> &before_inputs,
const std::vector<mindspore::lite::Tensor *> &before_outputs,
const lite::CallBackParam &call_param) {
const MSCallBackParam &call_param) {
std::vector<MSTensor> inputs = LiteTensorsToMSTensors(before_inputs);
std::vector<MSTensor> outputs = LiteTensorsToMSTensors(before_outputs);
MSCallBackParam mscall_param;
mscall_param.node_name = call_param.node_name;
mscall_param.node_type = call_param.node_type;
return after(inputs, outputs, mscall_param);
return after(inputs, outputs, call_param);
};
}
auto ret = session_->RunGraph(before_call_back, after_call_back);

2
mindspore/lite/src/runtime/kernel/gpu/opencl/opencl_executor.cc
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@ -40,7 +40,7 @@ int OpenCLExecutor::RunOrTune(const std::vector<Tensor *> &inputs, const std::ve
}
for (auto *kernel : kernels) {
MS_ASSERT(kernel);
GPUCallBackParam callbackParam;
MSCallBackParam callbackParam;
callbackParam.node_name = kernel->name();
callbackParam.node_type = kernel->type_str();
if ((before != nullptr) && !before(kernel->in_tensors(), kernel->out_tensors(), callbackParam)) {

7
mindspore/lite/src/runtime/kernel_exec.h
View File

@ -1,5 +1,5 @@
/**
* Copyright 2020-2021 Huawei Technologies Co., Ltd
* Copyright 2020-2022 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@ -39,6 +39,11 @@
#include "extendrt/mindir_loader/abstract_kernel.h"
#include "include/lite_types.h"
namespace mindspore::lite {
using KernelCallBack = std::function<bool(std::vector<lite::Tensor *> inputs, std::vector<lite::Tensor *> outputs,
const MSCallBackParam &opInfo)>;
}
using mindspore::infer::Abstractkernel;
using mindspore::lite::KernelCallBack;

2
mindspore/lite/test/config_level0/cropped_size.cfg
View File

@ -1,2 +1,2 @@
Note: This is the mindspore Lite inference framework size threshold. Offline review is required before modify this value!!!
1022256
1022266

6
mindspore/lite/tools/benchmark/benchmark_unified_api.cc
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@ -1208,8 +1208,7 @@ int BenchmarkUnifiedApi::InitTimeProfilingCallbackParameter() {
std::lock_guard<std::mutex> _l(op_times_mutex_);
float cost = static_cast<float>(opEnd - op_start_times_by_name_[call_param.node_name]) / kFloatMSEC;
if (flags_->device_ == "GPU") {
auto gpu_param = reinterpret_cast<const GPUCallBackParam &>(call_param);
cost = static_cast<float>(gpu_param.execute_time);
cost = static_cast<float>(call_param.execute_time);
}
op_cost_total_ += cost;
op_times_by_type_[call_param.node_type].first++;
@ -1257,8 +1256,7 @@ int BenchmarkUnifiedApi::InitTimeProfilingCallbackParameter() {
float cost = static_cast<float>(opEnd - op_begin_) / kFloatMSEC;
if (flags_->device_ == "GPU") {
auto gpu_param = reinterpret_cast<const GPUCallBackParam &>(call_param);
cost = static_cast<float>(gpu_param.execute_time);
cost = static_cast<float>(call_param.execute_time);
}
op_cost_total_ += cost;
op_times_by_type_[call_param.node_type].first++;