From: Inki Dae <inki.dae@samsung.com>
Date: Fri, 18 Oct 2024 08:28:19 +0000 (+0900)
Subject: add INT8 data type support
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=refs%2Fheads%2Ftizen_devel;p=platform%2Fcore%2Fmultimedia%2Finference-engine-tflite.git

add INT8 data type support

Change-Id: If85622bc22988dcf0226df8f08d9c21543e46a3e
Signed-off-by: Inki Dae <inki.dae@samsung.com>
---

diff --git a/src/inference_engine_tflite.cpp b/src/inference_engine_tflite.cpp
index ee52348..3697e71 100644
--- a/src/inference_engine_tflite.cpp
+++ b/src/inference_engine_tflite.cpp
@@ -176,6 +176,12 @@ namespace TFLiteImpl
 			case INFERENCE_TENSOR_DATA_TYPE_UINT8:
 				pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mInputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_UINT8, size, 1 };
+				LOGD("buffer type is UINT8");
+				break;
+			case INFERENCE_TENSOR_DATA_TYPE_INT8:
+				pBuff = static_cast<void *>(mInterpreter->typed_tensor<int8_t>(mInputLayerId[layer.first]));
+				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_INT8, size, 1 };
+				LOGD("buffer type is INT8");
 				break;
 			case INFERENCE_TENSOR_DATA_TYPE_FLOAT32:
 				pBuff = static_cast<void *>(mInterpreter->typed_tensor<float>(mInputLayerId[layer.first]));
@@ -185,6 +191,7 @@ namespace TFLiteImpl
 				LOGE("Not supported");
 				return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT;
 			}
+
 			buffers.insert(std::make_pair(layer.first, buffer));
 		}
 
@@ -216,6 +223,11 @@ namespace TFLiteImpl
 				pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mOutputLayerId[layer.first]));
 				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_UINT8, size, 1 };
 				break;
+			case kTfLiteInt8:
+				LOGI("type is kTfLiteInt8");
+				pBuff = static_cast<void *>(mInterpreter->typed_tensor<int8_t>(mOutputLayerId[layer.first]));
+				buffer = { pBuff, INFERENCE_TENSOR_DATA_TYPE_INT8, size, 1 };
+				break;
 			case kTfLiteInt64:
 				LOGI("type is kTfLiteInt64");
 				pBuff = static_cast<void *>(mInterpreter->typed_tensor<int64_t>(mOutputLayerId[layer.first]));
@@ -281,6 +293,9 @@ namespace TFLiteImpl
 			if (mInterpreter->tensor(layer.second)->type == kTfLiteUInt8) {
 				LOGI("type is kTfLiteUInt8");
 				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_UINT8;
+			} else if (mInterpreter->tensor(layer.second)->type == kTfLiteInt8) {
+				LOGI("type is kTfLiteInt8");
+				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_INT8;
 			} else if (mInterpreter->tensor(layer.second)->type == kTfLiteInt64) {
 				LOGI("type is kTfLiteInt64");
 				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_INT64;
@@ -362,11 +377,16 @@ namespace TFLiteImpl
 		if (mIsDynamicTensorMode)
 			for (auto &input_buffer : input_buffers) {
 				void *pBuff;
+
 				switch (mInterpreter->tensor(mInputLayerId[input_buffer.first])->type) {
 				case kTfLiteUInt8:
 					LOGI("type is kTfLiteUInt8");
 					pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mInputLayerId[input_buffer.first]));
 					break;
+				case kTfLiteInt8:
+					LOGI("type is kTfLiteInt8");
+					pBuff = static_cast<void *>(mInterpreter->typed_tensor<int8_t>(mInputLayerId[input_buffer.first]));
+					break;
 				case kTfLiteInt64:
 					LOGI("type is kTfLiteInt64");
 					pBuff = static_cast<void *>(mInterpreter->typed_tensor<int64_t>(mInputLayerId[input_buffer.first]));
@@ -379,6 +399,7 @@ namespace TFLiteImpl
 					LOGE("Not supported");
 					return INFERENCE_ENGINE_ERROR_NOT_SUPPORTED_FORMAT;
 				}
+
 				memcpy(pBuff, input_buffer.second.buffer, input_buffer.second.size);
 			}
 
@@ -397,6 +418,10 @@ namespace TFLiteImpl
 					LOGI("type is kTfLiteUInt8");
 					pBuff = static_cast<void *>(mInterpreter->typed_tensor<uint8_t>(mOutputLayerId[output_buffer.first]));
 					break;
+				case kTfLiteInt8:
+					LOGI("type is kTfLiteInt8");
+					pBuff = static_cast<void *>(mInterpreter->typed_tensor<int8_t>(mOutputLayerId[output_buffer.first]));
+					break;
 				case kTfLiteInt64:
 					LOGI("type is kTfLiteInt64");
 					pBuff = static_cast<void *>(mInterpreter->typed_tensor<int64_t>(mOutputLayerId[output_buffer.first]));
@@ -487,6 +512,10 @@ namespace TFLiteImpl
 				LOGI("type is kTfLiteUInt8");
 				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_UINT8;
 				break;
+			case kTfLiteInt8:
+				LOGI("type is kTfLiteInt8");
+				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_INT8;
+				break;
 			case kTfLiteFloat32:
 				LOGI("type is kTfLiteFloat32");
 				tensor_info.data_type = INFERENCE_TENSOR_DATA_TYPE_FLOAT32;