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context.h 17.91 KB
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zhengyuanhua 提交于 2022-05-30 09:48 . replace ascend710 to ascend310P
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_INCLUDE_API_CONTEXT_H
#define MINDSPORE_INCLUDE_API_CONTEXT_H
#include <string>
#include <memory>
#include <vector>
#include <map>
#include "include/api/types.h"
#include "include/api/dual_abi_helper.h"
namespace mindspore {
enum DeviceType {
kCPU = 0,
kGPU,
kKirinNPU,
kAscend,
kAscend910,
kAscend310,
// add new type here
kInvalidDeviceType = 100,
};
class Allocator;
class Delegate;
class DeviceInfoContext;
/// \brief Context is used to store environment variables during execution.
class MS_API Context {
public:
struct Data;
Context();
~Context() = default;
/// \brief Set the number of threads at runtime. Only valid for Lite.
///
/// \param[in] thread_num the number of threads at runtime.
void SetThreadNum(int32_t thread_num);
/// \brief Get the current thread number setting. Only valid for Lite.
///
/// \return The current thread number setting.
int32_t GetThreadNum() const;
/// \brief Set the parallel number of operators at runtime. Only valid for Lite.
///
/// \param[in] parallel_num the parallel number of operators at runtime.
void SetInterOpParallelNum(int32_t parallel_num);
/// \brief Get the current operators parallel number setting. Only valid for Lite.
///
/// \return The current operators parallel number setting.
int32_t GetInterOpParallelNum() const;
/// \brief Set the thread affinity to CPU cores. Only valid for Lite.
///
/// \param[in] mode: 0: no affinities, 1: big cores first, 2: little cores first
void SetThreadAffinity(int mode);
/// \brief Get the thread affinity of CPU cores. Only valid for Lite.
///
/// \return Thread affinity to CPU cores. 0: no affinities, 1: big cores first, 2: little cores first
int GetThreadAffinityMode() const;
/// \brief Set the thread lists to CPU cores. Only valid for Lite.
///
/// \note If core_list and mode are set by SetThreadAffinity at the same time, the core_list is effective, but the
/// mode is not effective.
///
/// \param[in] core_list: a vector of thread core lists.
void SetThreadAffinity(const std::vector<int> &core_list);
/// \brief Get the thread lists of CPU cores. Only valid for Lite.
///
/// \return core_list: a vector of thread core lists.
std::vector<int32_t> GetThreadAffinityCoreList() const;
/// \brief Set the status whether to perform model inference or training in parallel. Only valid for Lite.
///
/// \param[in] is_parallel: true, parallel; false, not in parallel.
void SetEnableParallel(bool is_parallel);
/// \brief Get the status whether to perform model inference or training in parallel. Only valid for Lite.
///
/// \return Bool value that indicates whether in parallel.
bool GetEnableParallel() const;
/// \brief Set Delegate to access third-party AI framework. Only valid for Lite.
///
/// \param[in] delegate the custom delegate.
void SetDelegate(const std::shared_ptr<Delegate> &delegate);
/// \brief Get the delegate of the third-party AI framework. Only valid for Lite.
///
/// \return Pointer to the custom delegate.
std::shared_ptr<Delegate> GetDelegate() const;
/// \brief Set quant model to run as float model in multi device.
///
/// \param[in] float_mode: true, run as float model; false, not run as float model.
void SetMultiModalHW(bool float_mode);
/// \brief Get the mode of the model run.
///
/// \return Bool value that indicates whether run as float model
bool GetMultiModalHW() const;
/// \brief Get a mutable reference of DeviceInfoContext vector in this context. Only MindSpore Lite supports
/// heterogeneous scenarios with multiple members in the vector.
///
/// \return Mutable reference of DeviceInfoContext vector in this context.
std::vector<std::shared_ptr<DeviceInfoContext>> &MutableDeviceInfo();
private:
std::shared_ptr<Data> data_;
};
/// \brief DeviceInfoContext defines different device contexts.
class MS_API DeviceInfoContext : public std::enable_shared_from_this<DeviceInfoContext> {
public:
struct Data;
DeviceInfoContext();
virtual ~DeviceInfoContext() = default;
/// \brief Get the type of this DeviceInfoContext.
///
/// \return Type of this DeviceInfoContext.
virtual enum DeviceType GetDeviceType() const = 0;
/// \brief A similar function to RTTI is provided when the -fno-rtti compilation option is turned on, which converts
/// DeviceInfoContext to a shared pointer of type T, and returns nullptr if the conversion fails.
///
/// \return A pointer of type T after conversion. If the conversion fails, it will be nullptr.
template <class T>
std::shared_ptr<T> Cast() {
static_assert(std::is_base_of<DeviceInfoContext, T>::value, "Wrong cast type.");
if (GetDeviceType() != T().GetDeviceType()) {
return nullptr;
}
return std::static_pointer_cast<T>(shared_from_this());
}
/// \brief obtain provider's name
///
/// \return provider's name.
inline std::string GetProvider() const;
/// \brief set provider's name.
///
/// \param[in] provider define the provider's name.
inline void SetProvider(const std::string &provider);
/// \brief obtain provider's device type.
///
/// \return provider's device type.
inline std::string GetProviderDevice() const;
/// \brief set provider's device type.
///
/// \param[in] device define the provider's device type.EG: CPU.
inline void SetProviderDevice(const std::string &device);
/// \brief set memory allocator.
///
/// \param[in] allocator define the memory allocator which can be defined by user.
void SetAllocator(const std::shared_ptr<Allocator> &allocator);
/// \brief obtain memory allocator.
///
/// \return memory allocator.
std::shared_ptr<Allocator> GetAllocator() const;
protected:
std::vector<char> GetProviderChar() const;
void SetProvider(const std::vector<char> &provider);
std::vector<char> GetProviderDeviceChar() const;
void SetProviderDevice(const std::vector<char> &device);
std::shared_ptr<Data> data_;
};
std::string DeviceInfoContext::GetProvider() const { return CharToString(GetProviderChar()); }
void DeviceInfoContext::SetProvider(const std::string &provider) { SetProvider(StringToChar(provider)); }
std::string DeviceInfoContext::GetProviderDevice() const { return CharToString(GetProviderDeviceChar()); }
void DeviceInfoContext::SetProviderDevice(const std::string &device) { SetProviderDevice(StringToChar(device)); }
/// \brief Derived from DeviceInfoContext, The configuration of the model running on the CPU. This option is only valid
/// for MindSpore Lite.
class MS_API CPUDeviceInfo : public DeviceInfoContext {
public:
/// \brief Get the type of this DeviceInfoContext.
///
/// \return Type of this DeviceInfoContext.
enum DeviceType GetDeviceType() const override { return DeviceType::kCPU; };
/// \brief Set enables to perform the float16 inference
///
/// \param[in] is_fp16 Enable float16 inference or not.
void SetEnableFP16(bool is_fp16);
/// \brief Get enables to perform the float16 inference
///
/// \return Whether enable float16 inference.
bool GetEnableFP16() const;
};
/// \brief Derived from DeviceInfoContext, The configuration of the model running on the NPU. This option is only valid
/// for MindSpore Lite.
class MS_API KirinNPUDeviceInfo : public DeviceInfoContext {
public:
/// \brief Get the type of this DeviceInfoContext.
///
/// \return Type of this DeviceInfoContext.
enum DeviceType GetDeviceType() const override { return DeviceType::kKirinNPU; };
/// \brief Set the NPU frequency.
///
/// \param[in] frequency Can be set to 1 (low power consumption), 2 (balanced), 3 (high performance), 4 (extreme
/// performance), default as 3.
void SetFrequency(int frequency);
/// \brief Get the NPU frequency.
///
/// \return NPU frequency
int GetFrequency() const;
};
/// \brief Derived from DeviceInfoContext, The configuration of the model running on the GPU.
class MS_API GPUDeviceInfo : public DeviceInfoContext {
public:
/// \brief Get the type of this DeviceInfoContext.
///
/// \return Type of this DeviceInfoContext.
enum DeviceType GetDeviceType() const override { return DeviceType::kGPU; };
/// \brief Set device id.
///
/// \param[in] device_id The device id.
void SetDeviceID(uint32_t device_id);
/// \brief Get the device id.
///
/// \return The device id.
uint32_t GetDeviceID() const;
/// \brief Get the distribution rank id.
///
/// \return The device id.
int GetRankID() const;
/// \brief Get the distribution group size.
///
/// \return The device id.
int GetGroupSize() const;
/// \brief Set the precision mode.
///
/// \param[in] precision_mode Optional "origin", "fp16". "origin" is set as default.
inline void SetPrecisionMode(const std::string &precision_mode);
/// \brief Get the precision mode.
///
/// \return The precision mode.
inline std::string GetPrecisionMode() const;
/// \brief Set enables to perform the float16 inference
///
/// \param[in] is_fp16 Enable float16 inference or not.
void SetEnableFP16(bool is_fp16);
/// \brief Get enables to perform the float16 inference
///
/// \return Whether enable float16 inference.
bool GetEnableFP16() const;
/// \brief Set enables to sharing mem with OpenGL
///
/// \param[in] is_enable_gl_texture Enable sharing OpenCL Memory with OpenGL or not.
void SetEnableGLTexture(bool is_enable_gl_texture);
/// \brief Get enables to sharing mem with OpenGL
///
/// \return Whether enable sharing mem with OpenGL.
bool GetEnableGLTexture() const;
/// \brief Set current OpenGL context
///
/// \param[in] gl_context Current OpenGL context.
void SetGLContext(void *gl_context);
/// \brief Get current OpenGL context
///
/// \return the OpenCL context by OpenGL used.
void *GetGLContext() const;
/// \brief Set current OpenGL display
///
/// \param[in] gl_display Current OpenGL display.
void SetGLDisplay(void *gl_display);
/// \brief Get current OpenGL display
///
/// \return the OpenCL display by OpenGL used.
void *GetGLDisplay() const;
private:
void SetPrecisionMode(const std::vector<char> &precision_mode);
std::vector<char> GetPrecisionModeChar() const;
};
void GPUDeviceInfo::SetPrecisionMode(const std::string &precision_mode) {
SetPrecisionMode(StringToChar(precision_mode));
}
std::string GPUDeviceInfo::GetPrecisionMode() const { return CharToString(GetPrecisionModeChar()); }
/// \brief Derived from DeviceInfoContext, The configuration of the model running on the Ascend. This option is
/// invalid for MindSpore Lite.
class MS_API AscendDeviceInfo : public DeviceInfoContext {
public:
/// \brief Get the type of this DeviceInfoContext.
///
/// \return Type of this DeviceInfoContext.
enum DeviceType GetDeviceType() const override { return DeviceType::kAscend; };
/// \brief Set device id.
///
/// \param[in] device_id The device id.
void SetDeviceID(uint32_t device_id);
/// \brief Get the device id.
///
/// \return The device id.
uint32_t GetDeviceID() const;
/// \brief Set AIPP configuration file path.
///
/// \param[in] cfg_path AIPP configuration file path.
inline void SetInsertOpConfigPath(const std::string &cfg_path);
/// \brief Get AIPP configuration file path.
///
/// \return AIPP configuration file path.
inline std::string GetInsertOpConfigPath() const;
/// \brief Set format of model inputs.
///
/// \param[in] format Optional "NCHW", "NHWC", etc.
inline void SetInputFormat(const std::string &format);
/// \brief Get format of model inputs.
///
/// \return The format of model inputs.
inline std::string GetInputFormat() const;
/// \brief Set shape of model inputs.
///
/// \param[in] shape e.g. "input_op_name1: 1,2,3,4;input_op_name2: 4,3,2,1".
inline void SetInputShape(const std::string &shape);
/// \brief Get shape of model inputs.
///
/// \return The shape of model inputs.
inline std::string GetInputShape() const;
/// \brief Set shape of model inputs.
///
/// \param[in] shape e.g. {{1, {1,2,3,4}}, {2, {4,3,2,1}}} means the first input shape 1,2,3,4 and the second input
/// shape 4,3,2,1.
void SetInputShapeMap(const std::map<int, std::vector<int>> &shape);
/// \brief Get shape of model inputs.
///
/// \return The shape of model inputs.
std::map<int, std::vector<int>> GetInputShapeMap() const;
void SetDynamicBatchSize(const std::vector<size_t> &dynamic_batch_size);
inline std::string GetDynamicBatchSize() const;
/// \brief Set the dynamic image size of model inputs.
///
/// \param[in] dynamic_image_size size hw e.g. "66,88;32,64" means h1:66,w1:88; h2:32,w2:64.
inline void SetDynamicImageSize(const std::string &dynamic_image_size);
/// \brief Get dynamic image size of model inputs.
///
/// \return The image size of model inputs.
inline std::string GetDynamicImageSize() const;
/// \brief Set type of model outputs.
///
/// \param[in] output_type FP32, UINT8 or FP16, default as FP32.
void SetOutputType(enum DataType output_type);
/// \brief Get type of model outputs.
///
/// \return The set type of model outputs.
enum DataType GetOutputType() const;
/// \brief Set precision mode of model.
///
/// \param[in] precision_mode Optional "force_fp16", "allow_fp32_to_fp16", "must_keep_origin_dtype" and
/// "allow_mix_precision", "force_fp16" is set as default
inline void SetPrecisionMode(const std::string &precision_mode);
/// \brief Get precision mode of model.
///
/// \return The set type of model outputs
inline std::string GetPrecisionMode() const;
/// \brief Set op select implementation mode.
///
/// \param[in] op_select_impl_mode Optional "high_performance" and "high_precision", "high_performance" is set as
/// default.
inline void SetOpSelectImplMode(const std::string &op_select_impl_mode);
/// \brief Get op select implementation mode.
///
/// \return The set op select implementation mode.
inline std::string GetOpSelectImplMode() const;
inline void SetFusionSwitchConfigPath(const std::string &cfg_path);
inline std::string GetFusionSwitchConfigPath() const;
// Optional "l1_optimize", "l2_optimize", "off_optimize" or "l1_and_l2_optimize", default as "l2_optimize"
inline void SetBufferOptimizeMode(const std::string &buffer_optimize_mode);
inline std::string GetBufferOptimizeMode() const;
private:
void SetInsertOpConfigPath(const std::vector<char> &cfg_path);
std::vector<char> GetInsertOpConfigPathChar() const;
void SetInputFormat(const std::vector<char> &format);
std::vector<char> GetInputFormatChar() const;
void SetInputShape(const std::vector<char> &shape);
std::vector<char> GetInputShapeChar() const;
std::vector<char> GetDynamicBatchSizeChar() const;
void SetDynamicImageSize(const std::vector<char> &dynamic_image_size);
std::vector<char> GetDynamicImageSizeChar() const;
void SetPrecisionMode(const std::vector<char> &precision_mode);
std::vector<char> GetPrecisionModeChar() const;
void SetOpSelectImplMode(const std::vector<char> &op_select_impl_mode);
std::vector<char> GetOpSelectImplModeChar() const;
void SetFusionSwitchConfigPath(const std::vector<char> &cfg_path);
std::vector<char> GetFusionSwitchConfigPathChar() const;
void SetBufferOptimizeMode(const std::vector<char> &buffer_optimize_mode);
std::vector<char> GetBufferOptimizeModeChar() const;
};
using Ascend310DeviceInfo = AscendDeviceInfo;
using Ascend910DeviceInfo = AscendDeviceInfo;
void AscendDeviceInfo::SetInsertOpConfigPath(const std::string &cfg_path) {
SetInsertOpConfigPath(StringToChar(cfg_path));
}
std::string AscendDeviceInfo::GetInsertOpConfigPath() const { return CharToString(GetInsertOpConfigPathChar()); }
void AscendDeviceInfo::SetInputFormat(const std::string &format) { SetInputFormat(StringToChar(format)); }
std::string AscendDeviceInfo::GetInputFormat() const { return CharToString(GetInputFormatChar()); }
void AscendDeviceInfo::SetInputShape(const std::string &shape) { SetInputShape(StringToChar(shape)); }
std::string AscendDeviceInfo::GetInputShape() const { return CharToString(GetInputShapeChar()); }
std::string AscendDeviceInfo::GetDynamicBatchSize() const { return CharToString(GetDynamicBatchSizeChar()); }
void AscendDeviceInfo::SetDynamicImageSize(const std::string &dynamic_image_size) {
SetDynamicImageSize(StringToChar(dynamic_image_size));
}
std::string AscendDeviceInfo::GetDynamicImageSize() const { return CharToString(GetDynamicImageSizeChar()); }
void AscendDeviceInfo::SetPrecisionMode(const std::string &precision_mode) {
SetPrecisionMode(StringToChar(precision_mode));
}
std::string AscendDeviceInfo::GetPrecisionMode() const { return CharToString(GetPrecisionModeChar()); }
void AscendDeviceInfo::SetOpSelectImplMode(const std::string &op_select_impl_mode) {
SetOpSelectImplMode(StringToChar(op_select_impl_mode));
}
std::string AscendDeviceInfo::GetOpSelectImplMode() const { return CharToString(GetOpSelectImplModeChar()); }
void AscendDeviceInfo::SetFusionSwitchConfigPath(const std::string &cfg_path) {
SetFusionSwitchConfigPath(StringToChar(cfg_path));
}
std::string AscendDeviceInfo::GetFusionSwitchConfigPath() const {
return CharToString(GetFusionSwitchConfigPathChar());
}
void AscendDeviceInfo::SetBufferOptimizeMode(const std::string &buffer_optimize_mode) {
SetBufferOptimizeMode(StringToChar(buffer_optimize_mode));
}
std::string AscendDeviceInfo::GetBufferOptimizeMode() const { return CharToString(GetBufferOptimizeModeChar()); }
} // namespace mindspore
#endif // MINDSPORE_INCLUDE_API_CONTEXT_H
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