From: Inki Dae <inki.dae@samsung.com>
Date: Wed, 14 Oct 2020 06:38:48 +0000 (+0900)
Subject: Update various tensor filters support
X-Git-Tag: submit/tizen/20201104.021236~2
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=d7871b14f803a8d44e1ac835e49ce17131b05275;p=platform%2Fcore%2Fmultimedia%2Finference-engine-mlapi.git

Update various tensor filters support

Change-Id: I2ea104cae60ba5a9049fcc8eaa1b0ec78a220112
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---

diff --git a/src/inference_engine_mlapi.cpp b/src/inference_engine_mlapi.cpp
index d683b0e..7f10204 100644
--- a/src/inference_engine_mlapi.cpp
+++ b/src/inference_engine_mlapi.cpp
@@ -15,6 +15,7 @@
  */
 
 #include <inference_engine_error.h>
+#include "inference_engine_private_type.h"
 #include "inference_engine_mlapi_private.h"
 
 #include <fstream>
@@ -70,7 +71,8 @@ namespace MLAPIImpl
 		inference_backend_type_e type =
 				*(static_cast<inference_backend_type_e *>(data));
 
-		if (INFERENCE_BACKEND_NONE >= type || INFERENCE_BACKEND_MAX <= type) {
+		if (INFERENCE_BACKEND_NONE >= type || INFERENCE_BACKEND_MAX <= type ||
+				INFERENCE_BACKEND_OPENCV == type) {
 			LOGE("Invalid backend type.");
 			return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
 		}
@@ -120,19 +122,10 @@ namespace MLAPIImpl
 		ml_nnfw_hw_e nnfw_hw;
 
 		switch (mPluginType) {
-		case INFERENCE_BACKEND_MLAPI:
-			// For now, backend type is MLAPI and target device type is CUSTOM then
-			// we will use Vivante NPU.
-			// TODO. other NPU should be considered later. I.e., SRNPU.
-			if ((mTargetDevice & INFERENCE_TARGET_CUSTOM) ==
-				INFERENCE_TARGET_CUSTOM) {
-				nnfw_type = ML_NNFW_TYPE_VIVANTE;
-				nnfw_hw = ML_NNFW_HW_ANY;
-				LOGI("Vivante tensor filter will be used.");
-			} else {
-				LOGE("Invalid target device type.");
-				return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED;
-			}
+		case INFERENCE_BACKEND_NPU_VIVANTE:
+			nnfw_type = ML_NNFW_TYPE_VIVANTE;
+			nnfw_hw = ML_NNFW_HW_ANY;
+			LOGI("Vivante tensor filter will be used.");
 
 			if (access(model_str.c_str(), R_OK) ||
 					access(model_paths[1].c_str(), R_OK)) {
@@ -148,30 +141,38 @@ namespace MLAPIImpl
 		case INFERENCE_BACKEND_ONE:
 		case INFERENCE_BACKEND_ARMNN:
 		case INFERENCE_BACKEND_TFLITE:
-			if (mPluginType == INFERENCE_BACKEND_ONE)
+			if (mPluginType == INFERENCE_BACKEND_ONE) {
 				nnfw_type = ML_NNFW_TYPE_NNFW;
-			if (mPluginType == INFERENCE_BACKEND_ARMNN)
+
+				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.");
+			}
+
+			if (mPluginType == INFERENCE_BACKEND_ARMNN) {
 				nnfw_type = ML_NNFW_TYPE_ARMNN;
-			if (mPluginType == INFERENCE_BACKEND_TFLITE)
+				LOGI("ARMNN tensor filter will be used.");
+			}
+
+			if (mPluginType == INFERENCE_BACKEND_TFLITE) {
 				nnfw_type = ML_NNFW_TYPE_TENSORFLOW_LITE;
+				LOGI("TFLITE tensor filter will be used.");
+			}
 
 			if (access(model_str.c_str(), R_OK)) {
 				LOGE("model file path in [%s]", model_str.c_str());
 				return INFERENCE_ENGINE_ERROR_INVALID_PATH;
 			}
 
-			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:
@@ -591,7 +592,7 @@ namespace MLAPIImpl
 		}
 
 		// TODO. flag supported accel device types according to a given ML Single API of nnstreamer backend.
-		if (mPluginType == INFERENCE_BACKEND_MLAPI) {
+		if (mPluginType == INFERENCE_BACKEND_NPU_VIVANTE) {
 			capacity->supported_accel_devices = INFERENCE_TARGET_CUSTOM;
 		} else {
 			capacity->supported_accel_devices = INFERENCE_TARGET_GPU |