Project initiationtizen

First commit for inference-engine-dldt

Change-Id: Iac10d3ba7c358f957a41392eeb32d268ced986d4
Signed-off-by: Kwanghoon Son <k.son@samsung.com>

9 files changed, 739 insertions, 0 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
new file mode 100644
index 0000000..3a41282
--- /dev/null
+++ b/CMakeLists.txt
@@ -0,0 +1,11 @@
+CMAKE_MINIMUM_REQUIRED(VERSION 2.6)
+SET(fw_name "inference-engine-dldt")
+
+PROJECT(${fw_name})
+
+SET(dependents "dlog inference-engine-interface-common openvino")
+
+INCLUDE(FindPkgConfig)
+pkg_check_modules(${fw_name}_dep REQUIRED ${dependents})
+
+add_subdirectory(src)
diff --git a/LICENSE.APLv2 b/LICENSE.APLv2
new file mode 100644
index 0000000..5554685
--- /dev/null
+++ b/LICENSE.APLv2
@@ -0,0 +1,204 @@
+                                 Apache License

+                           Version 2.0, January 2004

+                        http://www.apache.org/licenses/

+

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diff --git a/NOTICE b/NOTICE
new file mode 100644
index 0000000..0e0f016
--- /dev/null
+++ b/NOTICE
@@ -0,0 +1,3 @@
+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.
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..e0c806d
--- /dev/null
+++ b/README.md
@@ -0,0 +1 @@
+# inference-engine-dldt
diff --git a/inference-engine-dldt.manifest b/inference-engine-dldt.manifest
new file mode 100644
index 0000000..a76fdba
--- /dev/null
+++ b/inference-engine-dldt.manifest
@@ -0,0 +1,5 @@
+<manifest>
+	<request>
+		<domain name="_" />
+	</request>
+</manifest>
diff --git a/packaging/inference-engine-dldt.spec b/packaging/inference-engine-dldt.spec
new file mode 100644
index 0000000..961c1f9
--- /dev/null
+++ b/packaging/inference-engine-dldt.spec
@@ -0,0 +1,46 @@
+Name:       inference-engine-dldt
+Summary:    Intel Neural Network Runtime based implementation of inference-engine-interface
+Version:    0.0.1
+Release:    1
+Group:      Multimedia/Libraries
+License:    Apache-2.0
+Source0:    %{name}-%{version}.tar.gz
+Requires(post): /sbin/ldconfig
+Requires(postun): /sbin/ldconfig
+BuildRequires: cmake
+BuildRequires: pkgconfig(dlog)
+BuildRequires: pkgconfig(inference-engine-interface-common)
+BuildRequires: pkgconfig(openvino)
+BuildRequires: pkgconfig(opencv) >= 3.4.1
+
+%description
+Intel Neural Network Runtime based implementation of inference-engine-interface
+
+%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="$FFLAGS -DTIZEN_DEBUG_ENABLE"
+%endif
+
+mkdir build
+pushd build
+cmake ..
+make %{?jobs:-j%jobs}
+popd
+
+%install
+rm -rf %{buildroot}
+mkdir -p %{buildroot}/usr/lib/
+install -m 666 build/src/*.so %{buildroot}/usr/lib
+
+%post -p /sbin/ldconfig
+%postun -p /sbin/ldconfig
+
+%files
+%manifest %{name}.manifest
+%license LICENSE.APLv2
+%{_libdir}/*.so
\ No newline at end of file
diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
new file mode 100644
index 0000000..e7c804d
--- /dev/null
+++ b/src/CMakeLists.txt
@@ -0,0 +1,3 @@
+ADD_LIBRARY(${fw_name} SHARED inference_engine_dldt.cpp)
+target_include_directories(${fw_name} PUBLIC ${${fw_name}_dep_INCLUDE_DIRS})
+target_link_libraries(${fw_name} ${${fw_name}_dep_LIBRARIES})
\ No newline at end of file
diff --git a/src/inference_engine_dldt.cpp b/src/inference_engine_dldt.cpp
new file mode 100644
index 0000000..1660f39
--- /dev/null
+++ b/src/inference_engine_dldt.cpp
@@ -0,0 +1,392 @@
+/**
+ * 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 <fstream>
+#include <iostream>
+#include <unistd.h>
+#include <time.h>
+#include <queue>
+
+#include <inference_engine_error.h>
+#include "inference_engine_dldt_private.h"
+
+/**
+ * Set in/output Layer property is not stable.
+ * Only 1 batch
+ * 1 layer assigned only 1 tensor
+ * If N layer == N tensor exist
+ */
+
+#define BATCH_SIZE (1)
+
+namespace InferenceEngineImpl
+{
+namespace DLDTImpl
+{
+
+int DataTypeToSize(size_t &rv, inference_tensor_data_type_e tType)
+{
+
+    switch (tType)
+    {
+    case TENSOR_DATA_TYPE_FLOAT32:
+    case TENSOR_DATA_TYPE_UINT32:
+        rv = 4;
+        break;
+
+    case TENSOR_DATA_TYPE_FLOAT16:
+    case TENSOR_DATA_TYPE_UINT16:
+        rv = 2;
+        break;
+
+    case TENSOR_DATA_TYPE_UINT8:
+        rv = 1;
+        break;
+
+    default:
+        LOGE("Unsupported data type");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+        break;
+    }
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int PrecisionToDataType(inference_tensor_data_type_e &rv, const InferenceEngine::Precision &prec)
+{
+    switch (InferenceEngine::Precision::ePrecision(prec))
+    {
+    case InferenceEngine::Precision::ePrecision::FP32:
+        rv = TENSOR_DATA_TYPE_FLOAT32;
+        break;
+
+    case InferenceEngine::Precision::ePrecision::FP16:
+        rv = TENSOR_DATA_TYPE_FLOAT16;
+        break;
+
+    case InferenceEngine::Precision::ePrecision::U8:
+        rv = TENSOR_DATA_TYPE_UINT8;
+        break;
+
+    case InferenceEngine::Precision::ePrecision::U16:
+        rv = TENSOR_DATA_TYPE_UINT16;
+        break;
+
+    case InferenceEngine::Precision::ePrecision::I32:
+        rv = TENSOR_DATA_TYPE_UINT32;
+        break;
+
+    default:
+        LOGE("Unsupported data type");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+        break;
+    }
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int LayoutToShapeType(inference_tensor_shape_type_e &rv, InferenceEngine::Layout layout)
+{
+    switch (layout)
+    {
+    case InferenceEngine::NCHW:
+        rv = TENSOR_SHAPE_NCHW;
+        break;
+
+    case InferenceEngine::NHWC:
+        rv = TENSOR_SHAPE_NHWC;
+        break;
+    default:
+        LOGE("Unsupported tensor shape type");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+        break;
+    }
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+InferenceDLDT::InferenceDLDT()
+{
+}
+InferenceDLDT::~InferenceDLDT()
+{
+}
+
+int InferenceDLDT::SetTargetDevices(int types)
+{
+    LOGI("ENTER");
+
+    mTargetDevice = 0;
+    LOGI("Inference targets are, ");
+    if (types & INFERENCE_TARGET_CUSTOM)
+    {
+        mTargetDevice |= INFERENCE_TARGET_CUSTOM;
+        LOGI("MYRIAD ONLY");
+    }
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int DLDTDataToTensorInfo(inference_engine_tensor_info &tensor_info, InferenceEngine::DataPtr data_ptr)
+{
+    PrecisionToDataType(tensor_info.data_type, data_ptr->getPrecision());
+    const InferenceEngine::SizeVector sizev = data_ptr->getTensorDesc().getDims();
+    tensor_info.shape = std::vector<int>(sizev.begin(), sizev.end());
+    LayoutToShapeType(tensor_info.shape_type, data_ptr->getLayout());
+
+    if (tensor_info.shape[0] != BATCH_SIZE)
+    {
+        LOGE("Batch size should be 1");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+    }
+
+    size_t shape_size = 1;
+    for (auto &it : tensor_info.shape)
+    {
+        shape_size *= it;
+    }
+
+    tensor_info.size = shape_size;
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::Load(std::vector<std::string> model_paths, inference_model_format_e model_format)
+{
+    LOGI("ENTER");
+
+    if (!(mTargetDevice == INFERENCE_TARGET_CUSTOM && model_format == INFERENCE_MODEL_DLDT))
+    {
+        LOGE("Only myriad is supported with xml format, set target to custom");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+    }
+
+    std::string input_model = model_paths[0];
+    InferenceEngine::CNNNetReader networkReader;
+    networkReader.ReadNetwork(input_model);
+    networkReader.ReadWeights(input_model.substr(0, input_model.size() - 4) + ".bin");
+    InferenceEngine::CNNNetwork network = networkReader.getNetwork();
+    network.setBatchSize(BATCH_SIZE);
+
+    InferenceEngine::Core DLDTCore;
+    InferenceEngine::ExecutableNetwork exeNetwork;
+    try
+    {
+        exeNetwork = DLDTCore.LoadNetwork(network, "MYRIAD");
+    }
+    catch (const std::exception &e)
+    {
+        LOGE("Fail to load Myriad");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+    }
+
+    mInferRequest = exeNetwork.CreateInferRequest();
+
+    // set input
+    InferenceEngine::InputsDataMap inputInfo = network.getInputsInfo();
+    for (auto ele : inputInfo)
+    {
+        mInputProperty.layer_names.push_back(ele.first);
+        inference_engine_tensor_info tinfo;
+        DLDTDataToTensorInfo(tinfo, ele.second->getInputData());
+        mInputProperty.tensor_infos.push_back(tinfo);
+    }
+
+    // set output
+    InferenceEngine::OutputsDataMap outputInfo = network.getOutputsInfo();
+    for (auto ele : outputInfo)
+    {
+        mOutputProperty.layer_names.push_back(ele.first);
+        inference_engine_tensor_info tinfo;
+        DLDTDataToTensorInfo(tinfo, ele.second);
+        mOutputProperty.tensor_infos.push_back(tinfo);
+    }
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::GetInputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers)
+{
+    LOGI("ENTER");
+
+    // Upper layer will allocate output tensor buffer/buffers.
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::GetOutputTensorBuffers(std::vector<inference_engine_tensor_buffer> &buffers)
+{
+    LOGI("ENTER");
+
+    // Upper layer will allocate output tensor buffer/buffers.
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::GetInputLayerProperty(inference_engine_layer_property &property)
+{
+    LOGI("ENTER");
+
+    property = mInputProperty;
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::GetOutputLayerProperty(inference_engine_layer_property &property)
+{
+    LOGI("ENTER");
+
+    property = mOutputProperty;
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::SetInputLayerProperty(inference_engine_layer_property &property)
+{
+    LOGI("ENTER");
+
+    mInputProperty = property;
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::SetOutputLayerProperty(inference_engine_layer_property &property)
+{
+    LOGI("ENTER");
+
+    mOutputProperty = property;
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int InferenceDLDT::GetBackendCapacity(inference_engine_capacity *capacity)
+{
+    LOGI("ENTER");
+
+    if (capacity == NULL)
+    {
+        LOGE("Bad pointer.");
+        return INFERENCE_ENGINE_ERROR_INVALID_PARAMETER;
+    }
+
+    capacity->supported_accel_devices = mTargetDevice;
+
+    LOGI("LEAVE");
+
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+int TypeToBlob(const InferenceEngine::TensorDesc &tensorDesc, void *ptr, size_t size, InferenceEngine::Blob::Ptr &out)
+{
+    switch (InferenceEngine::Precision::ePrecision(tensorDesc.getPrecision()))
+    {
+    case InferenceEngine::Precision::ePrecision::FP32:
+        out = InferenceEngine::make_shared_blob<float>(tensorDesc, (float *)ptr, size);
+        break;
+
+    case InferenceEngine::Precision::ePrecision::U8:
+        out = InferenceEngine::make_shared_blob<uint8_t>(tensorDesc, (uint8_t *)ptr, size);
+        break;
+
+    case InferenceEngine::Precision::ePrecision::U16:
+    case InferenceEngine::Precision::ePrecision::FP16:
+        out = InferenceEngine::make_shared_blob<uint16_t>(tensorDesc, (uint16_t *)ptr, size);
+        break;
+
+    case InferenceEngine::Precision::ePrecision::I32:
+        out = InferenceEngine::make_shared_blob<int32_t>(tensorDesc, (int32_t *)ptr, size);
+        break;
+
+    default:
+        LOGE("Unsupported data type");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+        break;
+    }
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+int InferenceDLDT::Run(std::vector<inference_engine_tensor_buffer> &input_buffers,
+                       std::vector<inference_engine_tensor_buffer> &output_buffers)
+{
+    LOGI("ENTER");
+
+    if (mTargetDevice != INFERENCE_TARGET_CUSTOM)
+    {
+        LOGE("Only myriad is supported, set target to custom");
+        return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
+    }
+
+    if (mInputProperty.layer_names.size() != input_buffers.size() ||
+        mOutputProperty.layer_names.size() != output_buffers.size())
+    {
+        return INFERENCE_ENGINE_ERROR_INVALID_PARAMETER;
+    }
+
+    for (size_t i = 0; i < input_buffers.size(); i++)
+    {
+        InferenceEngine::Blob::Ptr imgBlob = mInferRequest.GetBlob(mInputProperty.layer_names[i]);
+        const InferenceEngine::TensorDesc tDesc = imgBlob->getTensorDesc();
+        InferenceEngine::Blob::Ptr input;
+        TypeToBlob(tDesc, input_buffers[i].buffer, input_buffers[i].size, input);
+        mInferRequest.SetBlob(mInputProperty.layer_names[i], input);
+    }
+
+    mInferRequest.Infer();
+    for (size_t i = 0; i < output_buffers.size(); i++)
+    {
+        InferenceEngine::Blob::Ptr output = mInferRequest.GetBlob(mOutputProperty.layer_names[i]);
+        std::memcpy(output->cbuffer().as<void *>(), output_buffers[i].buffer, output_buffers[i].size);
+    }
+
+    LOGI("LEAVE");
+    return INFERENCE_ENGINE_ERROR_NONE;
+}
+
+extern "C"
+{
+    class IInferenceEngineCommon *EngineCommonInit(void)
+    {
+        LOGI("ENTER");
+
+        InferenceDLDT *engine = new InferenceDLDT();
+
+        LOGI("LEAVE");
+
+        return engine;
+    }
+
+    void EngineCommonDestroy(class IInferenceEngineCommon *engine)
+    {
+        LOGI("ENTER");
+
+        delete engine;
+
+        LOGI("LEAVE");
+    }
+}
+} // namespace DLDTImpl
+} // namespace InferenceEngineImpl
diff --git a/src/inference_engine_dldt_private.h b/src/inference_engine_dldt_private.h
new file mode 100644
index 0000000..4a7c2a6
--- /dev/null
+++ b/src/inference_engine_dldt_private.h
@@ -0,0 +1,74 @@
+/**
+ * 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_DLDT_PRIVATE_H__
+#define __INFERENCE_ENGINE_DLDT_PRIVATE_H__
+
+#include <inference_engine_common.h>
+#include <inference_engine.hpp> /** DLDT inference engine */
+#include <memory>
+#include <dlog.h>
+
+#ifdef LOG_TAG
+#undef LOG_TAG
+#endif
+
+#define LOG_TAG "INFERENCE_ENGINE_DLDT"
+
+using namespace InferenceEngineInterface::Common;
+
+namespace InferenceEngineImpl
+{
+namespace DLDTImpl
+{
+
+class InferenceDLDT : public IInferenceEngineCommon
+{
+public:
+    InferenceDLDT();
+    ~InferenceDLDT();
+
+    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 mTargetDevice;
+    InferenceEngine::InferRequest mInferRequest;
+    inference_engine_layer_property mInputProperty;
+    inference_engine_layer_property mOutputProperty;
+};
+
+} // namespace DLDTImpl
+} // namespace InferenceEngineImpl
+
+#endif /* __INFERENCE_ENGINE_DLDT_PRIVATE_H__ */