--- /dev/null
+PROJECT("training-engine-interface-common")
+CMAKE_MINIMUM_REQUIRED(VERSION 2.6)
+
+# Find all source files and add the file list to a given variable, SOURCES
+AUX_SOURCE_DIRECTORY(src SOURCES)
+
+ADD_LIBRARY(${PROJECT_NAME} SHARED ${SOURCES})
+
+FIND_PACKAGE(PkgConfig REQUIRED)
+PKG_CHECK_MODULES(${PROJECT_NAME}_DEP REQUIRED dlog)
+
+TARGET_INCLUDE_DIRECTORIES(${PROJECT_NAME}
+ PUBLIC
+ ${PROJECT_SOURCE_DIR}/include
+ ${${PROJECT_NAME}_DEP_INCLUDE_DIRS}
+)
+
+TARGET_LINK_LIBRARIES(${PROJECT_NAME} ${${PROJECT_NAME}_DEP_LIBRARIES})
+
+SET_TARGET_PROPERTIES(${PROJECT_NAME}
+ PROPERTIES
+ VERSION ${FULLVER}
+ SOVERSION ${MAJORVER}
+ CLEAN_DIRECT_OUTPUT 1
+)
+
+#Install header and library files to given places
+INSTALL(TARGETS ${PROJECT_NAME} DESTINATION ${LIB_INSTALL_DIR})
+INSTALL(DIRECTORY ${PROJECT_SOURCE_DIR}/include/ DESTINATION include/media
+ FILES_MATCHING
+ PATTERN "*_private.h" EXCLUDE
+ PATTERN "*.h"
+)
+
+CONFIGURE_FILE(${PROJECT_NAME}.pc.in
+ ${CMAKE_CURRENT_SOURCE_DIR}/${PROJECT_NAME}.pc
+ @ONLY
+)
+
+INSTALL(FILES ${CMAKE_CURRENT_SOURCE_DIR}/${PROJECT_NAME}.pc
+ DESTINATION
+ ${LIB_INSTALL_DIR}/pkgconfig
+)
+
+ADD_SUBDIRECTORY(${PROJECT_SOURCE_DIR}/test)
--- /dev/null
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--- /dev/null
+# training_engine_interface
+An adaptation framework for deploying various training engines - NNTriner, TFLITE, Caffe2 and so on - to Mediavision.
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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 __TRAINING_ENGINE_COMMON_H__
+#define __TRAINING_ENGINE_COMMON_H__
+
+#include <map>
+#include <vector>
+#include <string>
+#include "training_engine_type.h"
+
+#define TE_CHECK_OBJ_NO_RETURN_VAL(obj) if (obj == NULL) { \
+ LOGE("Invalid object (%s)", #obj); \
+ return; \
+ }
+
+#define TE_CHECK_OBJ(obj, err) if (obj == NULL) { \
+ LOGE("Invalid object (%s)", #obj); \
+ return err; \
+ }
+
+namespace TrainingEngineInterface
+{
+namespace Common
+{
+ class ITrainingEngineCommon
+ {
+ public:
+ virtual ~ITrainingEngineCommon() {};
+
+ /**
+ * @brief Get capacity from a given backend engine.
+ * @details This callback requests what supported features and constraints the backend engine has.
+ * Upper layer should call this callback just after the backend engine library is loaded.
+ *
+ * @since_tizen 6.5
+ * @param[out] capacity A backend engine should add the features and constraints it has.
+ */
+ virtual int GetBackendCapacity(training_engine_capacity &capacity) = 0;
+
+ /**
+ * @brief Create a model object.
+ * @details This API creates a model object corresponding to specific training engine.
+ *
+ * @since_tizen 6.5
+ * @param[in] backbone_model_path A full path of backbone model which is a pre-trained model.
+ * @param[in] model_config_path A full path of model configuration file.
+ */
+ virtual training_engine_model *CreateModel(std::string backbone_model_path = "", std::string model_config_path = "") = 0;
+
+ /**
+ * @brief Destroy a given model object.
+ * @details This API releases all resources used for training model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object to release.
+ */
+ virtual void DestroyModel(training_engine_model *model) = 0;
+
+ /**
+ * @brief Create a layer object.
+ * @details This API creates a layer object corresponding to specific training engine model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a layer type to be created.
+ */
+ virtual training_engine_layer *CreateLayer(training_engine_layer_type_e type) = 0;
+
+ /**
+ * @brief Destroy a given layer object.
+ * @details This API releases a created layer object.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A layer object to release.
+ */
+ virtual void DestroyLayer(training_engine_layer *layer) = 0;
+
+ /**
+ * @brief Set an additional information for a given layer.
+ * @details This API adds several options for a given layer.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A object points to a created layer.
+ * @param[in] property A property structure which contains several options for a given layer.
+ */
+ virtual int SetLayerProperty(training_engine_layer *layer, training_engine_layer_property &property) = 0;
+
+ /**
+ * @brief Add a created layer to a given model.
+ * @details This API adds a created layer to a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object for a given layer to be added to.
+ * @param[in] layer A object points to a created layer.
+ */
+ virtual int AddLayer(training_engine_model *model, training_engine_layer *layer) = 0;
+
+ /**
+ * @brief Create a optimizer object.
+ * @details This API creates a model optimizer corresponding to specific training engine model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a optimizer type to be created.
+ */
+ virtual training_engine_optimizer *CreateOptimizer(training_engine_optimizer_type_e type) = 0;
+
+ /**
+ * @brief Set an additional information for a given optimizer.
+ * @details This API adds several options for a given optimizer.
+ *
+ * @since_tizen 6.5
+ * @param[in] optimizer A object points to a created optimizer.
+ * @param[in] property A property structure which contains several options for a given optimizer.
+ */
+ virtual int SetOptimizerProperty(training_engine_optimizer *optimizer, training_engine_optimizer_property &property) = 0;
+
+ /**
+ * @brief Add a created optimizer to a given model.
+ * @details This API adds a created optimizer to a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object for a given optimizer to be added to.
+ * @param[in] optimizer A object points to a created optimizer.
+ */
+ virtual int AddOptimizer(training_engine_model *model, training_engine_optimizer *optimizer) = 0;
+
+ /**
+ * @brief Create a dataset object.
+ * @details This API creates a dataset to train a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a dataset type to be created.
+ */
+ virtual training_engine_dataset *CreateDataset(training_engine_dataset_type_e type) = 0;
+
+ /**
+ * @brief Destroy a given dataset object.
+ * @details This API releases a created dataset object.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A dataset object to release.
+ */
+ virtual void DestroyDataset(training_engine_dataset *dataset) = 0;
+
+ /**
+ * @brief Set an additional information for a given dataset.
+ * @details This API adds several options for a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A object points to a created dataset.
+ * @param[in] property A dataset structure which contains several options for a given dataset.
+ */
+ virtual int SetDatasetProperty(training_engine_dataset *dataset, training_engine_dataset_property &property) = 0;
+
+ /**
+ * @brief Add a new input data to a given dataset.
+ * @details This API adds a new input data to a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A data set object for a new input data to be added to.
+ * @param[in] data An array which contains input tensor values.
+ * @param[in] data_len a length of data.
+ * @param[in] label An array which contains label values to a input data.
+ * @param[in] label_len a length of label.
+ * @param[in] type An type which indicates what data and label set given data and label should be added to.
+ */
+ virtual int AddDataToDataset(training_engine_dataset *dataset, float *data, size_t data_len, float *label, size_t label_len, training_engine_dataset_type_e type) = 0;
+
+ /**
+ * @brief Add a new input data to a given dataset.
+ * @details This API adds a new input data to a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A data set object for a new input data to be added to.
+ * @param[in] data An array which contains input tensor values.
+ * @param[in] data_len a length of data.
+ * @param[in] label An array which contains label values to a input data.
+ * @param[in] label_len a length of label.
+ * @param[in] type An type which indicates what data and label set given data and label should be added to.
+ */
+ virtual int AddDataToDataset(training_engine_dataset *dataset, unsigned int *data, size_t data_len, unsigned int *label, size_t label_len, training_engine_dataset_type_e type) = 0;
+
+ /**
+ * @brief Set an additional information for a given dataset.
+ * @details This API adds several options for a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A object points to a created dataset.
+ * @param[in] property A dataset structure which contains several options for a given dataset.
+ */
+ virtual int SetDataset(training_engine_model *model, training_engine_dataset *dataset) = 0;
+
+ /**
+ * @brief Compile a given model with a given property.
+ * @details This API compiles a given model referring to a given property information.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object points the model to be compiled.
+ * @param[in] property A structure which contains several compiler options.
+ */
+ virtual int CompileModel(training_engine_model *model, training_engine_compile_property &property) = 0;
+
+ /**
+ * @brief Train a given model with a given property.
+ * @details This API trains a given model with already-ready dataset.
+ *
+ * @since_tizen 6.5
+ * @parm[in] model A model object points the model to be trained.
+ * @parm[in] property A structure which contains several training options.
+ */
+ virtual int TrainModel(training_engine_model *model, training_engine_model_property &property) = 0;
+ };
+
+ typedef void destroy_t(ITrainingEngineCommon *);
+ typedef ITrainingEngineCommon *init_t(void);
+} /* Common */
+} /* TrainingEngineInterface */
+
+#endif /* __TRAINING_ENGINE_COMMON_H__ */
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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 __TRAINING_ENGINE_COMMON_IMPL_H__
+#define __TRAINING_ENGINE_COMMON_IMPL_H__
+
+#include <map>
+#include <vector>
+#include <string>
+
+#include "training_engine_common.h"
+
+namespace TrainingEngineInterface
+{
+namespace Common
+{
+ class TrainingEngineCommon
+ {
+ private:
+ void *mBackendModule;
+ ITrainingEngineCommon *mTraining;
+
+ public:
+ TrainingEngineCommon();
+
+ ~TrainingEngineCommon();
+
+ /**
+ * @brief Load a backend engine library with a given backend name.
+ * @details This callback loads a backend engine library with a given backend name.
+ * In order to find a backend engine library corresponding to the given backend name,
+ * this function makes a full name of the library file with given backend name.
+ * After that, it opens the library file by calling dlopen function to find a entry point
+ * function - EngineInit - of a actual backend library.
+ *
+ * @since_tizen 6.5
+ * @param[in] config A configuraion data needed to load a backend library.
+ */
+ int BindBackend(training_engine_config &config);
+
+ /**
+ * @brief Unload a backend engine library.
+ * @details This callback unload a backend engine library.
+ *
+ * @since_tizen 6.5
+ */
+ void UnbindBackend(void);
+
+ /**
+ * @brief Get capacity from a given backend engine.
+ * @details This callback requests what supported features and constraints the backend engine has.
+ * Upper layer should call this callback just after the backend engine library is loaded.
+ *
+ * @since_tizen 6.5
+ * @param[out] capacity A backend engine should add the features and constraints it has.
+ */
+ int GetBackendCapacity(training_engine_capacity &capacity);
+
+ /**
+ * @brief Create a model object.
+ * @details This API creates a model object corresponding to specific training engine.
+ *
+ * @since_tizen 6.5
+ * @param[in] backbone_model_path A full path of backbone model which is a pre-trained model.
+ * @param[in] model_config_path A full path of model configuration file.
+ */
+ training_engine_model *CreateModel(std::string backbone_model_path = "", std::string model_config_path = "");
+
+ /**
+ * @brief Destroy a given model object.
+ * @details This API releases all resources used for training model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object to release.
+ */
+ void DestroyModel(training_engine_model *model);
+
+ /**
+ * @brief Create a layer object.
+ * @details This API creates a layer object corresponding to specific training engine model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a layer type to be created.
+ */
+ training_engine_layer *CreateLayer(training_engine_layer_type_e type);
+
+ /**
+ * @brief Destroy a given layer object.
+ * @details This API releases a created layer object.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A layer object to release.
+ */
+ void DestroyLayer(training_engine_layer *layer);
+
+ /**
+ * @brief Set an additional information for a given layer.
+ * @details This API adds several options for a given layer.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A object points to a created layer.
+ * @param[in] property A property structure which contains several options for a given layer.
+ */
+ int SetLayerProperty(training_engine_layer *layer, training_engine_layer_property &property);
+
+ /**
+ * @brief Add a created layer to a given model.
+ * @details This API adds a created layer to a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object for a given layer to be added to.
+ * @param[in] layer A object points to a created layer.
+ */
+ int AddLayer(training_engine_model *model, training_engine_layer *layer);
+
+ /**
+ * @brief Create a optimizer object.
+ * @details This API creates a model optimizer corresponding to specific training engine model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a optimizer type to be created.
+ */
+ training_engine_optimizer *CreateOptimizer(training_engine_optimizer_type_e type);
+
+ /**
+ * @brief Set an additional information for a given optimizer.
+ * @details This API adds several options for a given optimizer.
+ *
+ * @since_tizen 6.5
+ * @param[in] optimizer A object points to a created optimizer.
+ * @param[in] property A property structure which contains several options for a given optimizer.
+ */
+ int SetOptimizerProperty(training_engine_optimizer *optimizer, training_engine_optimizer_property &property);
+
+ /**
+ * @brief Add a created optimizer to a given model.
+ * @details This API adds a created optimizer to a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object for a given optimizer to be added to.
+ * @param[in] optimizer A object points to a created optimizer.
+ */
+ int AddOptimizer(training_engine_model *model, training_engine_optimizer *optimizer);
+
+ /**
+ * @brief Create a dataset object.
+ * @details This API creates a dataset to train a given model.
+ *
+ * @since_tizen 6.5
+ * @param[in] type A enumeration value which indicates a dataset type to be created.
+ */
+ training_engine_dataset *CreateDataset(training_engine_dataset_type_e type);
+
+ /**
+ * @brief Destroy a given dataset object.
+ * @details This API releases a created dataset object.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A dataset object to release.
+ */
+ void DestroyDataset(training_engine_dataset *dataset);
+
+ /**
+ * @brief Set an additional information for a given dataset.
+ * @details This API adds several options for a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A object points to a created dataset.
+ * @param[in] property A dataset structure which contains several options for a given dataset.
+ */
+ int SetDatasetProperty(training_engine_dataset *dataset, training_engine_dataset_property &property);
+
+ /**
+ * @brief Add a new input data to a given dataset.
+ * @details This API adds a new input data to a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] dataset A data set object for a new input data to be added to.
+ * @param[in] data An array which contains input tensor values.
+ * @param[in] data_len A length of data.
+ * @param[in] label An array which contains label values to a input data.
+ * @param[in] label_len A length of label.
+ * @param[in] type An type which indicates what data and label set given data and label should be added to.
+ */
+ template <typename D, typename L>
+ int AddDataToDataset(training_engine_dataset *dataset, D *data, size_t data_len, L *label, size_t label_len, training_engine_dataset_type_e type);
+
+ /**
+ * @brief Set an additional information for a given dataset.
+ * @details This API adds several options for a given dataset.
+ *
+ * @since_tizen 6.5
+ * @param[in] layer A object points to a created dataset.
+ * @param[in] property A dataset structure which contains several options for a given dataset.
+ */
+ int SetDataset(training_engine_model *model, training_engine_dataset *dataset);
+
+ /**
+ * @brief Compile a given model with a given property.
+ * @details This API compiles a given model referring to a given property information.
+ *
+ * @since_tizen 6.5
+ * @param[in] model A model object points the model to be compiled.
+ * @param[in] property A structure which contains several compiler options.
+ */
+ int CompileModel(training_engine_model *model, training_engine_compile_property &property);
+
+ /**
+ * @brief Train a given model with a given property.
+ * @details This API trains a given model with already-ready dataset.
+ *
+ * @since_tizen 6.5
+ * @parm[in] model A model object points the model to be trained.
+ * @parm[in] property A structure which contains several training options.
+ */
+ int TrainModel(training_engine_model *model, training_engine_model_property &property);
+ };
+
+} /* Common */
+} /* TrainingEngineInterface */
+
+#endif /* __TRAINING_ENGINE_COMMON_IMPL_H__ */
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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 __TRAINING_ENGINE_ERROR_H__
+#define __TRAINING_ENGINE_ERROR_H__
+
+#include <tizen.h>
+
+#ifdef __cplusplus
+extern "C"
+{
+#endif /* __cplusplus */
+
+ /**
+ * @file training_engine_error.h
+ * @brief This file contains error type required by
+ * training engine
+ */
+ typedef enum {
+ TRAINING_ENGINE_ERROR_NONE = TIZEN_ERROR_NONE, /**< Successful */
+ TRAINING_ENGINE_ERROR_NOT_SUPPORTED =
+ TIZEN_ERROR_NOT_SUPPORTED, /**< Not supported */
+ TRAINING_ENGINE_ERROR_NO_DATA = TIZEN_ERROR_NO_DATA, /**< No data */
+ TRAINING_ENGINE_ERROR_KEY_NOT_AVAILABLE =
+ TIZEN_ERROR_KEY_NOT_AVAILABLE, /**< Key not available */
+ TRAINING_ENGINE_ERROR_OUT_OF_MEMORY =
+ TIZEN_ERROR_OUT_OF_MEMORY, /**< Out of memory */
+ TRAINING_ENGINE_ERROR_INVALID_PARAMETER =
+ TIZEN_ERROR_INVALID_PARAMETER, /**< Invalid parameter */
+ TRAINING_ENGINE_ERROR_INVALID_OPERATION =
+ TIZEN_ERROR_INVALID_OPERATION, /**< Invalid operation */
+ TRAINING_ENGINE_ERROR_PERMISSION_DENIED =
+ TIZEN_ERROR_NOT_PERMITTED, /**< Not permitted */
+ TRAINING_ENGINE_ERROR_BAD_ADDRESS =
+ TIZEN_ERROR_BAD_ADDRESS, /**< Bad address */
+ TRAINING_ENGINE_ERROR_INVALID_ADDRESS =
+ TIZEN_ERROR_MEDIA_VISION | 0x10 /**< Invalid address */
+ } training_engine_error_e;
+
+#ifdef __cplusplus
+}
+#endif /* __cplusplus */
+
+#endif /* __TRAINING_ENGINE_ERROR_H__ */
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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 __TRAINING_ENGINE_TYPE_H__
+#define __TRAINING_ENGINE_TYPE_H__
+
+#include <map>
+#include <vector>
+
+#ifdef __cplusplus
+extern "C"
+{
+#endif /* __cplusplus */
+
+ typedef enum {
+ TRAINING_LAYER_TYPE_MIN = 0,
+ TRAINING_LAYER_TYPE_INPUT, /**< Input Layer */
+ TRAINING_LAYER_TYPE_FC, /**< Fully Connected Layer */
+ TRAINING_LAYER_TYPE_BN, /**< Batch Normalization Layer */
+ TRAINING_LAYER_TYPE_CONV2D, /**< Convolution 2D Layer */
+ TRAINING_LAYER_TYPE_POOLING2D, /**< Pooling 2D Layer */
+ TRAINING_LAYER_TYPE_FLATTEN, /**< Flatten Layer */
+ TRAINING_LAYER_TYPE_ACTIVATION, /**< Activation Layer */
+ TRAINING_LAYER_TYPE_ADDITION, /**< Addition Layer */
+ TRAINING_LAYER_TYPE_CONCAT, /**< Concat Layer */
+ TRAINING_LAYER_TYPE_MULTIOUT, /**< MultiOut Layer */
+ TRAINING_LAYER_TYPE_L2NORM, /**< L2 Norm Layer */
+ TRAINING_LAYER_TYPE_CENTROID_KNN, /**< Centroid k-Nearest Neighbor Layer */
+ TRAINING_LAYER_TYPE_MAX
+ } training_engine_layer_type_e;
+
+ typedef enum {
+ TRAINING_TENSOR_SHAPE_MIN = 0,
+ TRAINING_TENSOR_SHAPE_NHWC,
+ TRAINING_TENSOR_SHAPE_NCHW,
+ TRAINING_TENSOR_SHAPE_MAX
+ } training_engine_tensor_shape_type_e;
+
+ typedef enum {
+ TRAINING_OPTIMIZER_TYPE_MIN = 0,
+ TRAINING_OPTIMIZER_TYPE_ADAM, /**< Adam optimizer */
+ TRAINING_OPTIMIZER_TYPE_SGD, /**< Stochastic Gradient Descent optomizer */
+ TRAINING_OPTIMIZER_TYPE_MAX
+ } training_engine_optimizer_type_e;
+
+ typedef enum {
+ TRAINING_DATASET_TYPE_MIN = 0,
+ TRAINING_DATASET_TYPE_TRAIN, /**< dataset for training a model */
+ TRAINING_DATASET_TYPE_TEST, /**< dataset for testing a model */
+ TRAINING_DATASET_TYPE_VERIFY, /**< dataset for verifying a model */
+ TRAINING_DATASET_TYPE_MAX
+ } training_engine_dataset_type_e;
+
+ /**
+ * @brief A structure to training model.
+ *
+ * @details This structure points to training engine specific model object.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_model {
+ void *model_handle;
+ // TODO. add a queue for keeping input data.
+ } training_engine_model;
+
+ /**
+ * @brief A structure to model layer.
+ *
+ * @details This structure points to training engine specific layer object.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_layer {
+ void *layer_handle;
+ // TODO.
+ } training_engine_layer;
+
+ /**
+ * @brief A structure to model optimizer.
+ *
+ * @details This structure points to training engine specific model optimizer object.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_optimizer {
+ void *optimizer_handle;
+ // TODO.
+ } training_engine_optimizer;
+
+ /**
+ * @brief A structure to model dataset.
+ *
+ * @details This structure points to training engine specific model dataset object.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_dataset {
+ void *dataset_handle;
+ training_engine_dataset_type_e type;
+ // TODO.
+ } training_engine_dataset;
+
+ /**
+ * @brief A layer property structure
+ *
+ * @details This structure is used to provide layer option to backend engine.
+ * - String which contains option strings corresponding to a given layer.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_layer_property {
+ std::string option;
+ // TODO.
+ } training_engine_layer_property;
+
+ /**
+ * @brief A optimizer property structure
+ *
+ * @details This structure is used to provide optimizer option to backend engine.
+ * - String which contains option strings corresponding to a given optimizer.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_optimizer_property {
+ std::string option;
+ // TODO.
+ } training_engine_optimizer_property;
+
+ /**
+ * @brief A dataset property structure
+ *
+ * @details This structure is used to provide dataset option to backend engine.
+ * - String which contains option strings corresponding to a given dataset.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_dataset_property {
+ std::string option;
+ // TODO.
+ } training_engine_dataset_property;
+
+ /**
+ * @brief A compile property structure
+ *
+ * @details This structure is used to provide compile option to backend engine.
+ * - String which contains option strings for compiling a given model.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_compile_property {
+ std::vector<std::string> options;
+ // TODO.
+ } training_engine_compile_property;
+
+ /**
+ * @brief A model property structure
+ *
+ * @details This structure is used to provide model option to backend engine.
+ * - String which contains option strings corresponding to a given model.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_model_property {
+ std::vector<std::string> options;
+ // TODO.
+ } training_engine_model_property;
+
+ /**
+ * @brief A capacity structure to a backend engine.
+ *
+ * @details This structure is used to get information such as what features and
+ * constraints a given backend engine has, and it contains below information,
+ * - tensor shape type a given backend engine supports for such as NCHW or NHWC.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_capacity {
+ training_engine_tensor_shape_type_e supported_tensor_shape_type;
+ // TODO.
+ } training_engine_capacity;
+
+ /**
+ * @brief A training engine commcon config structure.
+ *
+ * @details This structure contains training engine common configuration.
+ * - A backend name which indicates the training engine backend library
+ * to be linked.
+ *
+ * @since_tizen 6.5
+ */
+ typedef struct _training_engine_config {
+ std::string backend_name;
+ // TODO.
+ } training_engine_config;
+
+#ifdef __cplusplus
+}
+#endif /* __cplusplus */
+
+#endif /* __TRAINING_ENGINE_TYPE_H__ */
--- /dev/null
+Name: training-engine-interface
+Summary: Common interface for training engines
+Version: 0.0.1
+Release: 1
+Group: Multimedia/Framework
+License: Apache-2.0
+Source0: %{name}-%{version}.tar.gz
+BuildRequires: cmake
+BuildRequires: pkgconfig(dlog)
+BuildRequires: pkgconfig(iniparser)
+BuildRequires: pkgconfig(glib-2.0)
+BuildRequires: gtest-devel
+
+%description
+Common interface for training engines
+
+%package common
+Summary: Provide common interface library files for training engine excution
+Group: Multimedia/Framework
+
+%description common
+Common interface library files for training engine excution
+
+%package common-devel
+Summary: Provide header and library files for backend development of training engine
+Group: Multimedia/Framework
+Requires: training-engine-interface-common
+
+%description common-devel
+Header and library files for backend development of training engine
+
+%package tools
+Summary: Provide test binaries for testing training engine backends
+Group: Multimedia/Framework
+Requires: training-engine-interface-common
+
+%description tools
+Summary: Test binaries for testing training engine backends
+
+%prep
+%setup -q
+
+%build
+%if 0%{?sec_build_binary_debug_enable}
+export CFLAGS="$CFLAGS -DTIZEN_DEBUG_ENABLE"
+export CXXFLAGS="$CXXFLAGS -DTIZEN_DEBUG_ENABLE"
+export FFLAGS="$FFLAGS -DTIZEN_DEBUG_ENABLE"
+%endif
+
+export CFLAGS+=" -DPATH_LIBDIR=\\\"%{_libdir}\\\" -DSYSCONFDIR=\\\"%{_hal_sysconfdir}\\\""
+export CXXFLAGS+=" -DPATH_LIBDIR=\\\"%{_libdir}\\\" -DSYSCONFDIR=\\\"%{_hal_sysconfdir}\\\""
+
+MAJORVER=`echo %{version} | awk 'BEGIN {FS="."}{print $1}'`
+%cmake . -DFULLVER=%{version} -DMAJORVER=${MAJORVER} -DTZ_SYS_BIN=%TZ_SYS_BIN \
+
+make %{?jobs:-j%jobs}
+
+%install
+rm -rf %{buildroot}
+
+mkdir -p %{buildroot}%{_bindir}
+%make_install
+
+install -m 755 test/bin/training_engine_tc %{buildroot}%{_bindir}
+
+%post -p /sbin/ldconfig
+%postun -p /sbin/ldconfig
+
+%files common
+%manifest training-engine-interface-common.manifest
+%license LICENSE.APLv2
+%{_libdir}/libtraining-engine-interface-common.so.*
+
+%files common-devel
+%{_includedir}/media/*.h
+%{_libdir}/pkgconfig/*common.pc
+%{_libdir}/lib*-common.so
+
+%files tools
+%{_bindir}/training_engine_tc
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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.
+ */
+
+#include <iostream>
+#include <unistd.h>
+#include <dlfcn.h>
+
+#include "training_engine_error.h"
+#include "training_engine_common_impl.h"
+
+extern "C"
+{
+#include <dlog.h>
+
+#ifdef LOG_TAG
+#undef LOG_TAG
+#endif
+
+#define LOG_TAG "TRAINING_ENGINE_COMMON"
+}
+
+namespace TrainingEngineInterface
+{
+namespace Common
+{
+ TrainingEngineCommon::TrainingEngineCommon() :
+ mBackendModule(),
+ mTraining()
+ {
+ LOGI("ENTER");
+
+ LOGI("LEAVE");
+ }
+
+ TrainingEngineCommon::~TrainingEngineCommon()
+ {
+ LOGI("ENTER");
+
+ LOGI("LEAVE");
+ }
+
+ int TrainingEngineCommon::BindBackend(training_engine_config &config)
+ {
+ LOGI("ENTER");
+
+ const std::string lib_path("libtraining-engine-" + config.backend_name + ".so");
+
+ // Load training engine backend library with config->backend_name.
+ LOGI("lib: %s", lib_path.c_str());
+ mBackendModule = dlopen(lib_path.c_str(), RTLD_NOW);
+ LOGI("Handle : [%p]", mBackendModule);
+
+ if (!mBackendModule) {
+ LOGE("Failed to dlopen %s", lib_path.c_str());
+ LOGE("%s", dlerror());
+ return TRAINING_ENGINE_ERROR_INVALID_ADDRESS;
+ }
+
+ init_t *EngineInit= (init_t *)dlsym(mBackendModule, "EngineCommonInit");
+ if (EngineInit == NULL) {
+ LOGE("Failed to dlsym(%s).", dlerror());
+ mBackendModule = NULL;
+ return TRAINING_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ mTraining = EngineInit();
+ if (mTraining == NULL) {
+ LOGE("Failed to EngineInit call.");
+ dlclose(mBackendModule);
+ mBackendModule = NULL;
+ return TRAINING_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("LEAVE");
+
+ return TRAINING_ENGINE_ERROR_NONE;
+ }
+
+ void TrainingEngineCommon::UnbindBackend(void)
+ {
+ LOGI("ENTER");
+
+ if (mBackendModule) {
+ destroy_t *engineDestroy = (destroy_t *) dlsym(mBackendModule, "EngineCommonDestroy");
+ engineDestroy(mTraining);
+ dlclose(mBackendModule);
+ mTraining = nullptr;
+ mBackendModule = nullptr;
+ }
+
+ LOGI("LEAVE");
+ }
+
+ int TrainingEngineCommon::GetBackendCapacity(training_engine_capacity &capacity)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+
+ int ret = mTraining->GetBackendCapacity(capacity);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to get backend capacity.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ training_engine_model *TrainingEngineCommon::CreateModel(std::string backbone_model_path,
+ std::string model_config_path)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, NULL);
+
+ training_engine_model *model = mTraining->CreateModel(backbone_model_path,
+ model_config_path);
+ if (model == NULL)
+ LOGE("Failed to create a model.");
+
+ LOGI("LEAVE");
+
+ return model;
+ }
+
+ void TrainingEngineCommon::DestroyModel(training_engine_model *model)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ_NO_RETURN_VAL(mTraining);
+ TE_CHECK_OBJ_NO_RETURN_VAL(model);
+
+ mTraining->DestroyModel(model);
+
+ LOGI("LEAVE");
+ }
+
+ training_engine_layer *TrainingEngineCommon::CreateLayer(training_engine_layer_type_e type)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, NULL);
+
+ if (TRAINING_LAYER_TYPE_MIN >= type || TRAINING_LAYER_TYPE_MAX <= type) {
+ LOGE("Invalid layer parameter.");
+ return NULL;
+ }
+
+ training_engine_layer *layer = mTraining->CreateLayer(type);
+ if (layer == NULL)
+ LOGE("Failed to create a layer.");
+
+ LOGI("LEAVE");
+
+ return layer;
+ }
+
+ void TrainingEngineCommon::DestroyLayer(training_engine_layer *layer)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ_NO_RETURN_VAL(mTraining);
+ TE_CHECK_OBJ_NO_RETURN_VAL(layer);
+
+ mTraining->DestroyLayer(layer);
+
+ LOGI("LEAVE");
+ }
+
+ int TrainingEngineCommon::SetLayerProperty(training_engine_layer *layer,
+ training_engine_layer_property &property)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(layer, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->SetLayerProperty(layer, property);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to set layer property.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ int TrainingEngineCommon::AddLayer(training_engine_model *model, training_engine_layer *layer)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(model, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+ TE_CHECK_OBJ(layer, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->AddLayer(model, layer);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to add a layer to a given model.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ training_engine_optimizer *TrainingEngineCommon::CreateOptimizer(training_engine_optimizer_type_e type)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, NULL);
+
+ if (TRAINING_OPTIMIZER_TYPE_MIN >= type || TRAINING_OPTIMIZER_TYPE_MAX <= type) {
+ LOGE("Invalid optimizer parameter.");
+ return NULL;
+ }
+
+ training_engine_optimizer *optimizer = mTraining->CreateOptimizer(type);
+ if (optimizer == NULL)
+ LOGE("Failed to create a optimizer.");
+
+ LOGI("LEAVE");
+
+ return optimizer;
+ }
+
+ int TrainingEngineCommon::SetOptimizerProperty(training_engine_optimizer *optimizer,
+ training_engine_optimizer_property &property)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(optimizer, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->SetOptimizerProperty(optimizer, property);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to set optimizer property.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ int TrainingEngineCommon::AddOptimizer(training_engine_model *model,
+ training_engine_optimizer *optimizer)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(model, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+ TE_CHECK_OBJ(optimizer, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->AddOptimizer(model, optimizer);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to add a optimizer to a given model.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ training_engine_dataset *TrainingEngineCommon::CreateDataset(training_engine_dataset_type_e type)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, NULL);
+
+ if (TRAINING_DATASET_TYPE_MIN >= type || TRAINING_DATASET_TYPE_MAX <= type) {
+ LOGE("Invalid dataset parameter.");
+ return NULL;
+ }
+
+ // In case of nntrainer backend, the backend has to register callbacks
+ // for adding user-given data by calling ml_train_dataset_create_with_generator() API.
+ training_engine_dataset *dataset = mTraining->CreateDataset(type);
+ if (dataset == NULL)
+ LOGE("Failed to create a dataset.");
+
+ LOGI("LEAVE");
+
+ return dataset;
+ }
+
+ void TrainingEngineCommon::DestroyDataset(training_engine_dataset *dataset)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ_NO_RETURN_VAL(mTraining);
+ TE_CHECK_OBJ_NO_RETURN_VAL(dataset);
+
+ mTraining->DestroyDataset(dataset);
+
+ LOGI("LEAVE");
+ }
+
+ int TrainingEngineCommon::SetDatasetProperty(training_engine_dataset *dataset,
+ training_engine_dataset_property &property)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(dataset, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->SetDatasetProperty(dataset, property);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to set dataset property.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ template <typename D, typename L>
+ int TrainingEngineCommon::AddDataToDataset(training_engine_dataset *dataset,
+ D *data, size_t data_len, L *label, size_t label_len,
+ training_engine_dataset_type_e type)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(dataset, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+ TE_CHECK_OBJ(data, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+ TE_CHECK_OBJ(label, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ if (type <= TRAINING_DATASET_TYPE_MIN || type >= TRAINING_DATASET_TYPE_MAX) {
+ LOGE("Invalid dataset type.");
+ return TRAINING_ENGINE_ERROR_INVALID_PARAMETER;
+ }
+
+ // In case of nntrainer backend,
+ // Data and label will be added a queue of nntrainer backend.
+ // And then, all data in the queue will be updated into
+ // nntrainer internal in the callback registered by CreateDataset()
+ // The callback will be called in ml_train_model_run() API.
+ int ret = mTraining->AddDataToDataset(dataset, data, data_len, label, label_len, type);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to add data to dataset.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ int TrainingEngineCommon::SetDataset(training_engine_model *model,
+ training_engine_dataset *dataset)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(model, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+ TE_CHECK_OBJ(dataset, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->SetDataset(model, dataset);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to set dataset.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ int TrainingEngineCommon::CompileModel(training_engine_model *model,
+ training_engine_compile_property &property)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(model, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->CompileModel(model, property);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to compile a given model.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+ int TrainingEngineCommon::TrainModel(training_engine_model *model,
+ training_engine_model_property &property)
+ {
+ LOGI("ENTER");
+
+ TE_CHECK_OBJ(mTraining, TRAINING_ENGINE_ERROR_INVALID_OPERATION);
+ TE_CHECK_OBJ(model, TRAINING_ENGINE_ERROR_INVALID_PARAMETER);
+
+ int ret = mTraining->TrainModel(model, property);
+ if (ret != TRAINING_ENGINE_ERROR_NONE)
+ LOGE("Failed to train a given model.");
+
+ LOGI("LEAVE");
+
+ return ret;
+ }
+
+} /* Common */
+} /* TrainingEngineInterface */
--- /dev/null
+cmake_minimum_required(VERSION 2.6)
+
+enable_testing()
+
+SET(TRAINING_ENGINE_INTERFACE_LIB_NAME "training-engine-interface-common")
+
+add_subdirectory(src)
--- /dev/null
+project(training_engine_test)
+
+set(TRAINING_ENGINE_TEST_CASE training_engine_tc)
+
+find_package(GTest REQUIRED)
+set(GTEST_LIBRARY gtest)
+
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/test/bin)
+
+add_executable(${TRAINING_ENGINE_TEST_CASE}
+ ${PROJECT_SOURCE_DIR}/training_engine_tc.cpp
+ )
+
+target_link_libraries(${TRAINING_ENGINE_TEST_CASE} ${GTEST_LIBRARY}
+ ${GTEST_MAIN_LIBRARY}
+ ${TRAINING_ENGINE_INTERFACE_LIB_NAME}
+ dl
+ )
--- /dev/null
+/*
+ * test_gtest.cpp
+ *
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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.
+ */
+
+#include "gtest/gtest.h"
+
+int main(int argc, char **argv)
+{
+ ::testing::InitGoogleTest(&argc, argv);
+ int ret = RUN_ALL_TESTS();
+ return ret;
+}
--- /dev/null
+/**
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd All Rights Reserved
+ *
+ * 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.
+ */
+
+#include <string.h>
+#include <tuple>
+#include <map>
+
+#include "gtest/gtest.h"
+
+#include "training_engine_error.h"
+#include "training_engine_common_impl.h"
+
+using namespace TrainingEngineInterface::Common;
+
+static const char *LayerNames[TRAINING_LAYER_TYPE_MAX + 1] = {
+ "",
+ "Input",
+ "Fully Connected",
+ "Batch Normalization",
+ "Convolution 2D",
+ "Pooling 2D",
+ "Flatten",
+ "Activation",
+ "Addition",
+ "Concat",
+ "MultiOut",
+ "L2NORM",
+ "Centroid K-Nearest Neighbor",
+ ""
+};
+
+typedef std::tuple<std::string> ParamType_One;
+typedef std::tuple<std::string, training_engine_layer_type_e, std::vector<std::string>> ParamType_Three;
+
+class TrainingEngineTestCase_G1 : public testing::TestWithParam<ParamType_One> {};
+class TrainingEngineTestCase_G3 : public testing::TestWithParam<ParamType_Three> {};
+
+TEST_P(TrainingEngineTestCase_G1, InitBackendP)
+{
+ std::string backend_name;
+
+ std::tie(backend_name) = GetParam();
+
+ std::cout << "backend = " << backend_name << std::endl;
+
+ auto engine = std::make_unique<TrainingEngineCommon>();
+ ASSERT_TRUE(engine);
+
+ training_engine_config config = { "nntrainer" };
+ int ret = engine->BindBackend(config);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+
+ training_engine_capacity capacity = { TRAINING_TENSOR_SHAPE_MIN };
+ ret = engine->GetBackendCapacity(capacity);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+
+ engine->UnbindBackend();
+}
+
+TEST_P(TrainingEngineTestCase_G3, LayerTestP)
+{
+ std::string backend_name;
+ training_engine_layer_type_e type;
+ std::vector<std::string> options;
+
+ std::tie(backend_name, type, options) = GetParam();
+
+ std::cout << "backend = " << backend_name << "layer = " << LayerNames[static_cast<int>(type)] << std::endl;
+
+ auto engine = std::make_unique<TrainingEngineCommon>();
+ ASSERT_TRUE(engine);
+
+ training_engine_config config = { "nntrainer" };
+ int ret = engine->BindBackend(config);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+
+ training_engine_capacity capacity = { TRAINING_TENSOR_SHAPE_MIN };
+ ret = engine->GetBackendCapacity(capacity);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+
+ training_engine_model *model = engine->CreateModel();
+ ASSERT_TRUE(model);
+
+ training_engine_layer *layer = engine->CreateLayer(type);
+ ASSERT_TRUE(layer);
+
+ for (size_t i = 0; i < options.size(); ++i) {
+ training_engine_layer_property property = { .option = options[i] };
+ ret = engine->SetLayerProperty(layer, property);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+ }
+
+ ret = engine->AddLayer(model, layer);
+ ASSERT_EQ(ret, TRAINING_ENGINE_ERROR_NONE);
+
+ engine->DestroyLayer(layer);
+ engine->DestroyModel(model);
+
+ engine->UnbindBackend();
+}
+
+INSTANTIATE_TEST_CASE_P(Prefix, TrainingEngineTestCase_G1,
+ testing::Values(
+ // parameter order : backend name
+ // NNTRAINER.
+ ParamType_One("nntrainer")
+ /* TODO */
+ ));
+
+INSTANTIATE_TEST_CASE_P(Prefix, TrainingEngineTestCase_G3,
+ testing::Values(
+ // parameter order : backend name, layer type, property string
+ // NNTRAINER.
+ ParamType_Three("nntrainer", TRAINING_LAYER_TYPE_FC, { "unit=10", "activation=softmax", "bias_initializer=zeros" })
+ /* TODO */
+ ));
--- /dev/null
+<manifest>
+ <request>
+ <domain name="_" />
+ </request>
+</manifest>
--- /dev/null
+
+# Package Information for pkg-config
+
+prefix=@PREFIX@
+exec_prefix=/usr
+libdir=@LIB_INSTALL_DIR@
+includedir=/usr/include/media
+
+Name: @PC_NAME@
+Description: @PACKAGE_DESCRIPTION@
+Version: @VERSION@
+Requires: @PC_REQUIRED@
+Libs: -L${libdir} @PC_LDFLAGS@
+Cflags: -I${includedir} -I/usr/include
projects / platform / upstream / training-engine-interface.git / commitdiff