InferenceTFLite: drop mInputData member

[Issue type] code cleanup

Change-Id: Ifaff8ab6b1f1b16037b6249bd7918f8984282c35
Signed-off-by: Vibhav Aggarwal <v.aggarwal@samsung.com>

2 files changed, 20 insertions, 23 deletions

diff --git a/src/inference_engine_tflite.cpp b/src/inference_engine_tflite.cpp
index a1c8517..f37454b 100644
--- a/src/inference_engine_tflite.cpp
+++ b/src/inference_engine_tflite.cpp
@@ -154,27 +154,22 @@ namespace TFLiteImpl
 			SetInterpreterInfo();
 		}
 
-		mInputData.clear();
-
-		void *pBuff = NULL;
-
 		for (auto& layer : mInputLayers) {
 			size_t size = 1;
 			inference_engine_tensor_buffer buffer;
 			for (auto& dim : layer.second.shape)
 				size *= dim;
 
-			if ((layer.second).data_type == INFERENCE_TENSOR_DATA_TYPE_UINT8) {
-				mInputData.push_back(
-						mInterpreter->typed_tensor<uint8_t>(mInputLayerId[layer.first]));
-				pBuff = mInputData.back();
+			switch (layer.second.data_type) {
+			case INFERENCE_TENSOR_DATA_TYPE_UINT8:
+				auto pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mInputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_UINT8, size, 1 };
-			} else if ((layer.second).data_type == INFERENCE_TENSOR_DATA_TYPE_FLOAT32) {
-				mInputData.push_back(
-						mInterpreter->typed_tensor<float>(mInputLayerId[layer.first]));
-				pBuff = mInputData.back();
+				break;
+			case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
+				auto pBuff = static_cast<void *>(mInterpreter->typed_tensor<float>(mInputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_FLOAT32, size * 4, 1 };
-			} else {
+				break;
+			default:
 				LOGE("Not supported");
 				return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT;
 			}
@@ -193,31 +188,34 @@ namespace TFLiteImpl
 			SetInterpreterInfo();
 		}
 
-		void *pBuff = NULL;
 		for (auto& layer : mOutputLayers) {
 			inference_engine_tensor_buffer buffer;
 			size_t size = 1;
 			for (int idx2 = 0; idx2 < mInterpreter->tensor(mOutputLayerId[layer.first])->dims->size; ++idx2)
 				size *= mInterpreter->tensor(mOutputLayerId[layer.first])->dims->data[idx2];
 
-			if (mInterpreter->tensor(mOutputLayerId[layer.first])->type == kTfLiteUInt8) {
+			switch (mInterpreter->tensor(mOutputLayerId[layer.first])->type) {
+			case kTfLiteUInt8:
 				LOGI("type is kTfLiteUInt8");
-				pBuff = (void *) mInterpreter->typed_tensor<uint8_t>(mOutputLayerId[layer.first]);
+				auto pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mOutputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_UINT8, size, 1 };
-			} else if (mInterpreter->tensor(mOutputLayerId[layer.first])->type == kTfLiteInt64) {
+				break;
+			case kTfLiteInt64:
 				LOGI("type is kTfLiteInt64");
-				pBuff = (void*)mInterpreter->typed_tensor<int64_t>(mOutputLayerId[layer.first]);
+				auto pBuff = static_cast<void *>(mInterpreter->typed_tensor<int64_t>(mOutputLayerId[layer.first]));
 				buffer = {pBuff, INFERENCE_TENSOR_DATA_TYPE_INT64, size * 8, 1};
-			} else if (mInterpreter->tensor(mOutputLayerId[layer.first])->type == kTfLiteFloat32) {
+				break;
+			case kTfLiteFloat32:
 				LOGI("type is kTfLiteFloat32");
-				pBuff = (void *) mInterpreter->typed_tensor<float>(mOutputLayerId[layer.first]);
+				auto pBuff = static_cast<void *>(mInterpreter->typed_tensor<float>(mOutputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_FLOAT32, size * 4, 1 };
-			} else {
+				break;
+			default:
 				LOGE("Not supported");
 				return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT;
 			}
 
-			buffers.insert(std::make_pair(mInterpreter->tensor(mOutputLayerId[layer.first])->name, buffer));
+			buffers.insert(std::make_pair(layer.first, buffer));
 		}
 		LOGI("LEAVE");
 		return INFERENCE_ENGINE_ERROR_NONE;
diff --git a/src/inference_engine_tflite_private.h b/src/inference_engine_tflite_private.h
index d491500..82605f6 100644
--- a/src/inference_engine_tflite_private.h
+++ b/src/inference_engine_tflite_private.h
@@ -93,7 +93,6 @@ namespace TFLiteImpl
 
 		std::unique_ptr<tflite::Interpreter> mInterpreter;
 		std::unique_ptr<tflite::FlatBufferModel> mFlatBuffModel;
-		std::vector<void *> mInputData;
 
 		std::map<std::string, inference_engine_tensor_info> mInputLayers;
 		std::map<std::string, inference_engine_tensor_info> mOutputLayers;