--- /dev/null
+Inki Dae <inki.dae@samsung.com>
--- /dev/null
+
+CMAKE_MINIMUM_REQUIRED(VERSION 2.6)
+SET(fw_name "inference-engine-nnstreamer")
+
+PROJECT(${fw_name})
+
+SET(CMAKE_INSTALL_PREFIX /usr)
+SET(PREFIX ${CMAKE_INSTALL_PREFIX})
+
+set(CMAKE_CXX_STANDARD 14)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+set(CMAKE_CXX_EXTENSIONS OFF)
+
+SET(INC_DIR "${PROJECT_SOURCE_DIR}/include")
+SET(dependents "dlog inference-engine-interface-common capi-nnstreamer")
+
+INCLUDE(FindPkgConfig)
+pkg_check_modules(${fw_name} REQUIRED ${dependents})
+FOREACH(flag ${${fw_name}_CFLAGS})
+ SET(EXTRA_CFLAGS "${EXTRA_CFLAGS} ${flag}")
+ SET(EXTRA_CXXFLAGS "${EXTRA_CXXFLAGS} ${flag}")
+ENDFOREACH(flag)
+
+FOREACH(flag ${${fw_name}_LDFLAGS})
+ SET(EXTRA_LDFLAGS "${EXTRA_LDFLAGS} ${flag}")
+ENDFOREACH(flag)
+#Remove leading whitespace POLICY CMP0004
+STRING(REGEX REPLACE "^ " "" EXTRA_LDFLAGS ${EXTRA_LDFLAGS})
+
+SET(CMAKE_C_FLAGS "-I./include -I./include/headers ${CMAKE_C_FLAGS} ${EXTRA_CFLAGS} -fPIC -Wall -w")
+SET(CMAKE_C_FLAGS_DEBUG "-O0 -g")
+
+SET(CMAKE_CXX_FLAGS "-I./include -I./include/headers ${CMAKE_CXX_FLAGS} ${EXTRA_CXXFLAGS} -fPIC")
+SET(CMAKE_CXX_FLAGS_DEBUG "-O0 -g --w")
+
+ADD_DEFINITIONS("-DPREFIX=\"${CMAKE_INSTALL_PREFIX}\"")
+ADD_DEFINITIONS("-DTIZEN_DEBUG")
+
+SET(CMAKE_EXE_LINKER_FLAGS "-Wl,--as-needed -Wl,--rpath=${LIB_INSTALL_DIR}")
+
+aux_source_directory(src SOURCES)
+ADD_LIBRARY(${fw_name} SHARED ${SOURCES})
+
+TARGET_LINK_LIBRARIES(${fw_name} ${EXTRA_LDFLAGS})
+
+
+SET_TARGET_PROPERTIES(${fw_name}
+ PROPERTIES
+ CLEAN_DIRECT_OUTPUT 1
+)
+
+INSTALL(TARGETS ${fw_name} DESTINATION ${LIB_INSTALL_DIR})
+INSTALL(
+ DIRECTORY ${INC_DIR}/ DESTINATION include/media
+ FILES_MATCHING
+ PATTERN "*_private.h" EXCLUDE
+ PATTERN "*.h"
+ )
+
+SET(PC_NAME ${fw_name})
+SET(PC_REQUIRED ${pc_dependents})
+SET(PC_LDFLAGS -l${fw_name})
+SET(PC_CFLAGS -I\${includedir}/media)
+
+IF(UNIX)
+
+ADD_CUSTOM_TARGET (distclean @echo cleaning for source distribution)
+ADD_CUSTOM_COMMAND(
+ DEPENDS clean
+ COMMENT "distribution clean"
+ COMMAND find
+ ARGS .
+ -not -name config.cmake -and \(
+ -name tester.c -or
+ -name Testing -or
+ -name CMakeFiles -or
+ -name cmake.depends -or
+ -name cmake.check_depends -or
+ -name CMakeCache.txt -or
+ -name cmake.check_cache -or
+ -name *.cmake -or
+ -name Makefile -or
+ -name core -or
+ -name core.* -or
+ -name gmon.out -or
+ -name install_manifest.txt -or
+ -name *.pc -or
+ -name *~ \)
+ | grep -v TC | xargs rm -rf
+ TARGET distclean
+ VERBATIM
+)
+
+ENDIF(UNIX)
--- /dev/null
+Copyright (c) 2000 - 2011 Samsung Electronics Co., Ltd. All rights reserved.\r
+\r
+ Apache License\r
+ Version 2.0, January 2004\r
+ http://www.apache.org/licenses/\r
+\r
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\r
+\r
+ 1. Definitions.\r
+\r
+ "License" shall mean the terms and conditions for use, reproduction,\r
+ and distribution as defined by Sections 1 through 9 of this document.\r
+\r
+ "Licensor" shall mean the copyright owner or entity authorized by\r
+ the copyright owner that is granting the License.\r
+\r
+ "Legal Entity" shall mean the union of the acting entity and all\r
+ other entities that control, are controlled by, or are under common\r
+ control with that entity. For the purposes of this definition,\r
+ "control" means (i) the power, direct or indirect, to cause the\r
+ direction or management of such entity, whether by contract or\r
+ otherwise, or (ii) ownership of fifty percent (50%) or more of the\r
+ outstanding shares, or (iii) beneficial ownership of such entity.\r
+\r
+ "You" (or "Your") shall mean an individual or Legal Entity\r
+ exercising permissions granted by this License.\r
+\r
+ "Source" form shall mean the preferred form for making modifications,\r
+ including but not limited to software source code, documentation\r
+ source, and configuration files.\r
+\r
+ "Object" form shall mean any form resulting from mechanical\r
+ transformation or translation of a Source form, including but\r
+ not limited to compiled object code, generated documentation,\r
+ and conversions to other media types.\r
+\r
+ "Work" shall mean the work of authorship, whether in Source or\r
+ Object form, made available under the License, as indicated by a\r
+ copyright notice that is included in or attached to the work\r
+ (an example is provided in the Appendix below).\r
+\r
+ "Derivative Works" shall mean any work, whether in Source or Object\r
+ form, that is based on (or derived from) the Work and for which the\r
+ editorial revisions, annotations, elaborations, or other modifications\r
+ represent, as a whole, an original work of authorship. For the purposes\r
+ of this License, Derivative Works shall not include works that remain\r
+ separable from, or merely link (or bind by name) to the interfaces of,\r
+ the Work and Derivative Works thereof.\r
+\r
+ "Contribution" shall mean any work of authorship, including\r
+ the original version of the Work and any modifications or additions\r
+ to that Work or Derivative Works thereof, that is intentionally\r
+ submitted to Licensor for inclusion in the Work by the copyright owner\r
+ or by an individual or Legal Entity authorized to submit on behalf of\r
+ the copyright owner. For the purposes of this definition, "submitted"\r
+ means any form of electronic, verbal, or written communication sent\r
+ to the Licensor or its representatives, including but not limited to\r
+ communication on electronic mailing lists, source code control systems,\r
+ and issue tracking systems that are managed by, or on behalf of, the\r
+ Licensor for the purpose of discussing and improving the Work, but\r
+ excluding communication that is conspicuously marked or otherwise\r
+ designated in writing by the copyright owner as "Not a Contribution."\r
+\r
+ "Contributor" shall mean Licensor and any individual or Legal Entity\r
+ on behalf of whom a Contribution has been received by Licensor and\r
+ subsequently incorporated within the Work.\r
+\r
+ 2. Grant of Copyright License. Subject to the terms and conditions of\r
+ this License, each Contributor hereby grants to You a perpetual,\r
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable\r
+ copyright license to reproduce, prepare Derivative Works of,\r
+ publicly display, publicly perform, sublicense, and distribute the\r
+ Work and such Derivative Works in Source or Object form.\r
+\r
+ 3. Grant of Patent License. Subject to the terms and conditions of\r
+ this License, each Contributor hereby grants to You a perpetual,\r
+ worldwide, non-exclusive, no-charge, royalty-free, irrevocable\r
+ (except as stated in this section) patent license to make, have made,\r
+ use, offer to sell, sell, import, and otherwise transfer the Work,\r
+ where such license applies only to those patent claims licensable\r
+ by such Contributor that are necessarily infringed by their\r
+ Contribution(s) alone or by combination of their Contribution(s)\r
+ with the Work to which such Contribution(s) was submitted. If You\r
+ institute patent litigation against any entity (including a\r
+ cross-claim or counterclaim in a lawsuit) alleging that the Work\r
+ or a Contribution incorporated within the Work constitutes direct\r
+ or contributory patent infringement, then any patent licenses\r
+ granted to You under this License for that Work shall terminate\r
+ as of the date such litigation is filed.\r
+\r
+ 4. Redistribution. You may reproduce and distribute copies of the\r
+ Work or Derivative Works thereof in any medium, with or without\r
+ modifications, and in Source or Object form, provided that You\r
+ meet the following conditions:\r
+\r
+ (a) You must give any other recipients of the Work or\r
+ Derivative Works a copy of this License; and\r
+\r
+ (b) You must cause any modified files to carry prominent notices\r
+ stating that You changed the files; and\r
+\r
+ (c) You must retain, in the Source form of any Derivative Works\r
+ that You distribute, all copyright, patent, trademark, and\r
+ attribution notices from the Source form of the Work,\r
+ excluding those notices that do not pertain to any part of\r
+ the Derivative Works; and\r
+\r
+ (d) If the Work includes a "NOTICE" text file as part of its\r
+ distribution, then any Derivative Works that You distribute must\r
+ include a readable copy of the attribution notices contained\r
+ within such NOTICE file, excluding those notices that do not\r
+ pertain to any part of the Derivative Works, in at least one\r
+ of the following places: within a NOTICE text file distributed\r
+ as part of the Derivative Works; within the Source form or\r
+ documentation, if provided along with the Derivative Works; or,\r
+ within a display generated by the Derivative Works, if and\r
+ wherever such third-party notices normally appear. The contents\r
+ of the NOTICE file are for informational purposes only and\r
+ do not modify the License. You may add Your own attribution\r
+ notices within Derivative Works that You distribute, alongside\r
+ or as an addendum to the NOTICE text from the Work, provided\r
+ that such additional attribution notices cannot be construed\r
+ as modifying the License.\r
+\r
+ You may add Your own copyright statement to Your modifications and\r
+ may provide additional or different license terms and conditions\r
+ for use, reproduction, or distribution of Your modifications, or\r
+ for any such Derivative Works as a whole, provided Your use,\r
+ reproduction, and distribution of the Work otherwise complies with\r
+ the conditions stated in this License.\r
+\r
+ 5. Submission of Contributions. Unless You explicitly state otherwise,\r
+ any Contribution intentionally submitted for inclusion in the Work\r
+ by You to the Licensor shall be under the terms and conditions of\r
+ this License, without any additional terms or conditions.\r
+ Notwithstanding the above, nothing herein shall supersede or modify\r
+ the terms of any separate license agreement you may have executed\r
+ with Licensor regarding such Contributions.\r
+\r
+ 6. Trademarks. This License does not grant permission to use the trade\r
+ names, trademarks, service marks, or product names of the Licensor,\r
+ except as required for reasonable and customary use in describing the\r
+ origin of the Work and reproducing the content of the NOTICE file.\r
+\r
+ 7. Disclaimer of Warranty. Unless required by applicable law or\r
+ agreed to in writing, Licensor provides the Work (and each\r
+ Contributor provides its Contributions) on an "AS IS" BASIS,\r
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or\r
+ implied, including, without limitation, any warranties or conditions\r
+ of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A\r
+ PARTICULAR PURPOSE. You are solely responsible for determining the\r
+ appropriateness of using or redistributing the Work and assume any\r
+ risks associated with Your exercise of permissions under this License.\r
+\r
+ 8. Limitation of Liability. In no event and under no legal theory,\r
+ whether in tort (including negligence), contract, or otherwise,\r
+ unless required by applicable law (such as deliberate and grossly\r
+ negligent acts) or agreed to in writing, shall any Contributor be\r
+ liable to You for damages, including any direct, indirect, special,\r
+ incidental, or consequential damages of any character arising as a\r
+ result of this License or out of the use or inability to use the\r
+ Work (including but not limited to damages for loss of goodwill,\r
+ work stoppage, computer failure or malfunction, or any and all\r
+ other commercial damages or losses), even if such Contributor\r
+ has been advised of the possibility of such damages.\r
+\r
+ 9. Accepting Warranty or Additional Liability. While redistributing\r
+ the Work or Derivative Works thereof, You may choose to offer,\r
+ and charge a fee for, acceptance of support, warranty, indemnity,\r
+ or other liability obligations and/or rights consistent with this\r
+ License. However, in accepting such obligations, You may act only\r
+ on Your own behalf and on Your sole responsibility, not on behalf\r
+ of any other Contributor, and only if You agree to indemnify,\r
+ defend, and hold each Contributor harmless for any liability\r
+ incurred by, or claims asserted against, such Contributor by reason\r
+ of your accepting any such warranty or additional liability.\r
+\r
+ END OF TERMS AND CONDITIONS\r
+\r
+ APPENDIX: How to apply the Apache License to your work.\r
+\r
+ To apply the Apache License to your work, attach the following\r
+ boilerplate notice, with the fields enclosed by brackets "[]"\r
+ replaced with your own identifying information. (Don't include\r
+ the brackets!) The text should be enclosed in the appropriate\r
+ comment syntax for the file format. We also recommend that a\r
+ file or class name and description of purpose be included on the\r
+ same "printed page" as the copyright notice for easier\r
+ identification within third-party archives.\r
+\r
+ Copyright [yyyy] [name of copyright owner]\r
+\r
+ Licensed under the Apache License, Version 2.0 (the "License");\r
+ you may not use this file except in compliance with the License.\r
+ You may obtain a copy of the License at\r
+\r
+ http://www.apache.org/licenses/LICENSE-2.0\r
+\r
+ Unless required by applicable law or agreed to in writing, software\r
+ distributed under the License is distributed on an "AS IS" BASIS,\r
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\r
+ See the License for the specific language governing permissions and\r
+ limitations under the License.\r
+\r
+\r
+\r
--- /dev/null
+Copyright (c) Samsung Electronics Co., Ltd. All rights reserved.
+Except as noted, this software is licensed under Apache License, Version 2.
+Please, see the LICENSE.APLv2 file for Apache License terms and conditions.
--- /dev/null
+# inference-engine-mlapi
+This is Tizen MediaVision inference engine ML Single API backend of NNStreamer
+for the use of NNFW, Vivante and TRIV2 NPU.
--- /dev/null
+<manifest>
+ <request>
+ <domain name="_" />
+ </request>
+</manifest>
--- /dev/null
+Name: inference-engine-mlapi
+Summary: ML Single API backend of NNStreamer for MediaVision
+Version: 0.0.1
+Release: 1
+Group: Multimedia/Libraries
+License: Apache-2.0
+ExclusiveArch: %{arm} aarch64
+Source0: %{name}-%{version}.tar.gz
+Requires(post): /sbin/ldconfig
+Requires(postun): /sbin/ldconfig
+BuildRequires: cmake
+BuildRequires: python
+BuildRequires: pkgconfig(dlog)
+BuildRequires: pkgconfig(inference-engine-interface-common)
+BuildRequires: capi-nnstreamer-devel
+
+%description
+ML Single API backend of NNStreamer for MediaVision
+
+%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
+
+%cmake .
+
+make %{?jobs:-j%jobs}
+
+%install
+rm -rf %{buildroot}
+
+%make_install
+
+%post -p /sbin/ldconfig
+%postun -p /sbin/ldconfig
+
+%files
+%manifest %{name}.manifest
+%license LICENSE.APLv2
+%defattr(-,root,root,-)
+%{_libdir}/*.so
--- /dev/null
+/**
+ * Copyright (c) 2020 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 <inference_engine_error.h>
+#include "inference_engine_nnstreamer_private.h"
+
+#include <fstream>
+#include <iostream>
+#include <unistd.h>
+#include <time.h>
+#include <queue>
+
+namespace InferenceEngineImpl {
+namespace MLAPIImpl {
+
+InferenceMLAPI::InferenceMLAPI(void) :
+ mPluginType(),
+ mTargetDevice(),
+ mSingle(),
+ mDesignated_inputs(),
+ mDesignated_outputs(),
+ mInputProperty(),
+ mOutputProperty(),
+ mInputTensorBuffer(),
+ mOutputTensorBuffer(),
+ mInputTensorInfo(),
+ mOutputTensorInfo()
+{
+ LOGI("ENTER");
+
+ LOGI("LEAVE");
+}
+
+InferenceMLAPI::~InferenceMLAPI()
+{
+ mDesignated_inputs.clear();
+ std::vector<std::string>().swap(mDesignated_inputs);
+
+ mDesignated_outputs.clear();
+ std::vector<std::string>().swap(mDesignated_outputs);
+}
+
+int InferenceMLAPI::SetPluginType(int type)
+{
+ LOGI("ENTER");
+
+ if (INFERENCE_BACKEND_NNFW != type && INFERENCE_BACKEND_VIVANTE != type) {
+ LOGE("Invalid backend type.");
+ return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+ }
+
+ mPluginType = type;
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::SetTargetDevices(int types)
+{
+ LOGI("ENTER");
+
+
+ LOGI("Inference targets are, ");
+ if (types & INFERENCE_TARGET_CPU) {
+ mTargetDevice |= INFERENCE_TARGET_CPU;
+ LOGI("CPU");
+ }
+
+ if (types & INFERENCE_TARGET_GPU) {
+ mTargetDevice |= INFERENCE_TARGET_GPU;
+ LOGI("GPU");
+ }
+
+ if (types & INFERENCE_TARGET_CUSTOM) {
+ mTargetDevice |= INFERENCE_TARGET_CUSTOM;
+ LOGI("NPU");
+ }
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::Load(std::vector<std::string> model_paths, inference_model_format_e model_format)
+{
+ LOGI("ENTER");
+
+ // ML Single API of MLAPI requires model_paths rule like below,
+ // "so library file path,nb model file path" or vise versa.
+ std::string model_str(model_paths[0] + "," + model_paths[1]);
+
+ LOGI("Model name = %s", model_str.c_str());
+
+ // TODO. Set NNFW backend type and HW type properly.
+
+ ml_nnfw_type_e nnfw_type;
+ ml_nnfw_hw_e nnfw_hw;
+
+ switch (mPluginType) {
+ case INFERENCE_BACKEND_VIVANTE:
+ nnfw_type = ML_NNFW_TYPE_VIVANTE;
+ nnfw_hw = ML_NNFW_HW_ANY;
+ LOGI("Vivante tensor filter will be used.");
+ break;
+ case INFERENCE_BACKEND_NNFW:
+ nnfw_type = ML_NNFW_TYPE_NNFW;
+ if (mTargetDevice == INFERENCE_TARGET_CPU) {
+ nnfw_hw = ML_NNFW_HW_CPU_NEON;
+ LOGI("Target device is NEON.");
+ } else if (mTargetDevice == INFERENCE_TARGET_GPU) {
+ nnfw_hw = ML_NNFW_HW_GPU;
+ LOGI("Target device is GPU");
+ } else {
+ LOGE("Invalid inference target device type.");
+ return INFERENCE_ENGINE_ERROR_INVALID_PARAMETER;
+ }
+ LOGI("NNFW tensor filter will be used.");
+ break;
+ // TODO.
+ default:
+ LOGE("Invalid plugin type.");
+ return INFERENCE_ENGINE_ERROR_INVALID_PARAMETER;
+ }
+
+ int ret = ml_single_open(&mSingle, model_str.c_str(), NULL, NULL, nnfw_type, nnfw_hw);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_single_open(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::GetInputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers)
+{
+ LOGI("ENTER");
+
+ // TODO. Implement this function according to a given nnstreamer backend properly.
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::GetOutputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers)
+{
+ LOGI("ENTER");
+
+ // Output tensor buffers will be allocated by a backend plugin of nnstreamer
+ // So add a null tensor buffer object. This buffer will be updated at Run callback.
+
+ // Caution. this tensor buffer will be checked by upper framework to verity if
+ // the tensor buffer object is valid or not so fill dummy data to the tensor buffer.
+
+ // TODO. Consider multiple output tensors.
+
+ inference_engine_tensor_buffer tensor_buf = { 0, };
+ tensor_buf.data_type = INFERENCE_TENSOR_DATA_TYPE_FLOAT16;
+ tensor_buf.buffer = (void *)1;
+ tensor_buf.size = 1;
+ tensor_buf.owner_is_backend = 1;
+ buffers.push_back(tensor_buf);
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+
+int InferenceMLAPI::GetInputLayerProperty(inference_engine_layer_property &property)
+{
+ LOGI("ENTER");
+
+ ml_tensors_info_h in_info = NULL;
+
+ // TODO. Need to check if model file loading is done.
+
+ int ret = ml_single_get_input_info(mSingle, &in_info);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_single_get_input_info(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ unsigned int cnt;
+ ret = ml_tensors_info_get_count(in_info, &cnt);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_count(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("input tensor count = %u", cnt);
+
+ for (unsigned int i = 0; i < cnt; ++i) {
+ ml_tensor_type_e in_type;
+ unsigned int in_dim;
+ char *in_name = NULL;
+ size_t in_size;
+
+ ret = ml_tensors_info_get_tensor_type(in_info, i, &in_type);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_tensor_type(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("input tensor type = %d", in_type);
+
+ ret = ml_tensors_info_get_tensor_dimension(in_info, i, &in_dim);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_tensor_dimension(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("input tensor dimension = %u", in_dim);
+
+ ret = ml_tensors_info_get_tensor_name(in_info, i, &in_name);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_tensor_name(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("input tensor name = %s", in_name);
+
+ ret = ml_tensors_info_get_tensor_size(in_info, i, &in_size);
+ if (ret != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_tensor_size(%d).", ret);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("input tensor size = %u", in_size);
+
+ // TODO. Compare tensor info from engine to one from a given property.
+ }
+
+ property.layer_names = mInputProperty.layer_names;
+
+ std::vector<inference_engine_tensor_info>::iterator iter;
+ for (iter = mInputProperty.tensor_infos.begin(); iter != mInputProperty.tensor_infos.end(); iter++) {
+ inference_engine_tensor_info tensor_info = *iter;
+ property.tensor_infos.push_back(tensor_info);
+ }
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::GetOutputLayerProperty(inference_engine_layer_property &property)
+{
+ LOGI("ENTER");
+
+ property.layer_names = mOutputProperty.layer_names;
+
+ inference_engine_tensor_info tensor_info;
+
+ // TODO. Set tensor info from a given nnstreamer backend instead of fixed one.
+
+ tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_FLOAT16;
+ tensor_info.shape = { 1, 1001 };
+ tensor_info.size = 1001;
+ property.tensor_infos.push_back(tensor_info);
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::SetInputLayerProperty(inference_engine_layer_property &property)
+{
+ LOGI("ENTER");
+
+ std::vector<std::string>::iterator iter;
+ for (iter = property.layer_names.begin(); iter != property.layer_names.end(); iter++) {
+ std::string name = *iter;
+ LOGI("input layer name = %s", name.c_str());
+ }
+
+ mDesignated_inputs.clear();
+ std::vector<std::string>().swap(mDesignated_inputs);
+
+ // TODO. Request input property information to a given nnstreamer backend,
+ // and set it instead of user-given one,
+
+ mDesignated_inputs = property.layer_names;
+ mInputProperty = property;
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::SetOutputLayerProperty(inference_engine_layer_property &property)
+{
+ LOGI("ENTER");
+
+ std::vector<std::string>::iterator iter;
+ for (iter = property.layer_names.begin(); iter != property.layer_names.end(); iter++) {
+ std::string name = *iter;
+ LOGI("output layer name = %s", name.c_str());
+ }
+
+ mDesignated_outputs.clear();
+ std::vector<std::string>().swap(mDesignated_outputs);
+
+ // TODO. Request output property information to a given nnstreamer backend,
+ // and set it instead of user-given one,
+
+ mDesignated_outputs = property.layer_names;
+ mOutputProperty = property;
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::GetBackendCapacity(inference_engine_capacity *capacity)
+{
+ LOGI("ENTER");
+
+ if (capacity == NULL) {
+ LOGE("Bad pointer.");
+ return INFERENCE_ENGINE_ERROR_INVALID_PARAMETER;
+ }
+
+ // TODO. flag supported accel device types according to a given nnstreamer backend.
+ capacity->supported_accel_devices = INFERENCE_TARGET_CUSTOM;
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::CheckTensorBuffers(std::vector<inference_engine_tensor_buffer> &input_buffers,
+ std::vector<inference_engine_tensor_buffer> &output_buffers)
+{
+ LOGI("ENTER");
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceMLAPI::Run(std::vector<inference_engine_tensor_buffer> &input_buffers,
+ std::vector<inference_engine_tensor_buffer> &output_buffers)
+{
+ LOGI("ENTER");
+
+ // Make sure to check if tensor buffer count and binding info one are same.
+ int err = CheckTensorBuffers(input_buffers, output_buffers);
+ if (err != INFERENCE_ENGINE_ERROR_NONE) {
+ return err;
+ }
+
+ ml_tensors_info_h in_info = NULL;
+
+ err = ml_single_get_input_info(mSingle, &in_info);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_single_get_input_info(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ ml_tensors_data_h input_data = NULL;
+ err = ml_tensors_data_create(in_info, &input_data);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_data_create(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ unsigned int cnt;
+ err = ml_tensors_info_get_count(in_info, &cnt);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_info_get_count(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ for (unsigned int i = 0; i < cnt; ++i) {
+ LOGI("index(%d) : buffer = %p, size = %u\n", i, input_buffers[i].buffer, input_buffers[i].size);
+ err = ml_tensors_data_set_tensor_data(input_data, i, input_buffers[i].buffer, input_buffers[i].size);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_data_set_tensor_data(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+ }
+
+ ml_tensors_data_h output_data = NULL;
+ err = ml_single_invoke(mSingle, input_data, &output_data);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_single_invoke(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ // TODO. Consider mutiple output tensors.
+
+ err = ml_tensors_data_get_tensor_data(output_data, 0, (void **)&output_buffers[0].buffer, &output_buffers[0].size);
+ if (err != ML_ERROR_NONE) {
+ LOGE("Failed to request ml_tensors_data_get_tensor_data(%d).", err);
+ return INFERENCE_ENGINE_ERROR_INVALID_OPERATION;
+ }
+
+ LOGI("Output tensor = %u", output_buffers[0].size);
+
+ LOGI("LEAVE");
+
+ return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+extern "C"
+{
+class IInferenceEngineCommon* EngineCommonInit(void)
+{
+ LOGI("ENTER");
+
+ InferenceMLAPI *engine = new InferenceMLAPI();
+
+ LOGI("LEAVE");
+
+ return engine;
+}
+
+void EngineCommonDestroy(class IInferenceEngineCommon *engine)
+{
+ LOGI("ENTER");
+
+ delete engine;
+
+ LOGI("LEAVE");
+}
+}
+} /* MLAPIImpl */
+} /* InferenceEngineImpl */
--- /dev/null
+/**
+ * Copyright (c) 2020 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 __INFERENCE_ENGINE_NNSTREAMER_PRIVATE_H__
+#define __INFERENCE_ENGINE_NNSTREAMER_PRIVATE_H__
+
+#include <inference_engine_common.h>
+#include <nnstreamer-single.h>
+
+#include <memory>
+#include <dlog.h>
+
+#ifdef LOG_TAG
+#undef LOG_TAG
+#endif
+
+#define LOG_TAG "INFERENCE_ENGINE_MLAPI"
+
+using namespace InferenceEngineInterface::Common;
+
+namespace InferenceEngineImpl {
+namespace MLAPIImpl {
+
+class InferenceMLAPI : public IInferenceEngineCommon {
+public:
+ InferenceMLAPI();
+ ~InferenceMLAPI();
+
+ int SetPluginType(int type) override;
+
+ int SetTargetDevices(int types) override;
+
+ int Load(std::vector<std::string> model_paths, inference_model_format_e model_format) override;
+
+ int GetInputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers) override;
+
+ int GetOutputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers) override;
+
+ int GetInputLayerProperty(inference_engine_layer_property &property) override;
+
+ int GetOutputLayerProperty(inference_engine_layer_property &property) override;
+
+ int SetInputLayerProperty(inference_engine_layer_property &property) override;
+
+ int SetOutputLayerProperty(inference_engine_layer_property &property) override;
+
+ int GetBackendCapacity(inference_engine_capacity *capacity) override;
+
+ int Run(std::vector<inference_engine_tensor_buffer> &input_buffers,
+ std::vector<inference_engine_tensor_buffer> &output_buffers) override;
+
+private:
+ int CheckTensorBuffers(std::vector<inference_engine_tensor_buffer> &input_buffers,
+ std::vector<inference_engine_tensor_buffer> &output_buffers);
+
+ int mPluginType;
+ int mTargetDevice;
+ ml_single_h mSingle;
+ std::vector<std::string> mDesignated_inputs;
+ std::vector<std::string> mDesignated_outputs;
+ inference_engine_layer_property mInputProperty;
+ inference_engine_layer_property mOutputProperty;
+ std::vector<inference_engine_tensor_buffer> mInputTensorBuffer;
+ std::vector<inference_engine_tensor_buffer> mOutputTensorBuffer;
+ std::vector<inference_engine_tensor_info> mInputTensorInfo;
+ std::vector<inference_engine_tensor_info> mOutputTensorInfo;
+};
+
+} /* InferenceEngineImpl */
+} /* MLAPIImpl */
+
+#endif /* __INFERENCE_ENGINE_NNSTREAMER_PRIVATE_H__ */