Basic support for UINT4 in loader

runtime/libs/circle-schema/include/circle_schema_generated.h

@@ -1,19 +1,3 @@
-/*
- * Copyright (c) 2019-2024 Samsung Electronics Co., Ltd. All Rights Reserved
- * Copyright 2018 The TensorFlow Authors. 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.
- */
 // automatically generated by the FlatBuffers compiler, do not modify
 
 #ifndef FLATBUFFERS_GENERATED_CIRCLESCHEMA_CIRCLE_H_
@@ -530,6 +514,7 @@ struct ModelBuilder;
 
 enum TensorType : int8_t
 {
+  TensorType_UINT4 = -1,
   TensorType_FLOAT32 = 0,
   TensorType_FLOAT16 = 1,
   TensorType_INT32 = 2,
@@ -548,35 +533,35 @@ enum TensorType : int8_t
   TensorType_UINT32 = 15,
   TensorType_UINT16 = 16,
   TensorType_INT4 = 17,
-  TensorType_MIN = TensorType_FLOAT32,
+  TensorType_MIN = TensorType_UINT4,
   TensorType_MAX = TensorType_INT4
 };
 
-inline const TensorType (&EnumValuesTensorType())[18]
+inline const TensorType (&EnumValuesTensorType())[19]
 {
   static const TensorType values[] = {
-    TensorType_FLOAT32,   TensorType_FLOAT16,  TensorType_INT32,   TensorType_UINT8,
-    TensorType_INT64,     TensorType_STRING,   TensorType_BOOL,    TensorType_INT16,
-    TensorType_COMPLEX64, TensorType_INT8,     TensorType_FLOAT64, TensorType_COMPLEX128,
-    TensorType_UINT64,    TensorType_RESOURCE, TensorType_VARIANT, TensorType_UINT32,
-    TensorType_UINT16,    TensorType_INT4};
+    TensorType_UINT4,      TensorType_FLOAT32,   TensorType_FLOAT16,  TensorType_INT32,
+    TensorType_UINT8,      TensorType_INT64,     TensorType_STRING,   TensorType_BOOL,
+    TensorType_INT16,      TensorType_COMPLEX64, TensorType_INT8,     TensorType_FLOAT64,
+    TensorType_COMPLEX128, TensorType_UINT64,    TensorType_RESOURCE, TensorType_VARIANT,
+    TensorType_UINT32,     TensorType_UINT16,    TensorType_INT4};
   return values;
 }
 
 inline const char *const *EnumNamesTensorType()
 {
-  static const char *const names[19] = {"FLOAT32", "FLOAT16",    "INT32",  "UINT8",     "INT64",
-                                        "STRING",  "BOOL",       "INT16",  "COMPLEX64", "INT8",
-                                        "FLOAT64", "COMPLEX128", "UINT64", "RESOURCE",  "VARIANT",
-                                        "UINT32",  "UINT16",     "INT4",   nullptr};
+  static const char *const names[20] = {"UINT4",   "FLOAT32", "FLOAT16",    "INT32",  "UINT8",
+                                        "INT64",   "STRING",  "BOOL",       "INT16",  "COMPLEX64",
+                                        "INT8",    "FLOAT64", "COMPLEX128", "UINT64", "RESOURCE",
+                                        "VARIANT", "UINT32",  "UINT16",     "INT4",   nullptr};
   return names;
 }
 
 inline const char *EnumNameTensorType(TensorType e)
 {
-  if (::flatbuffers::IsOutRange(e, TensorType_FLOAT32, TensorType_INT4))
+  if (::flatbuffers::IsOutRange(e, TensorType_UINT4, TensorType_INT4))
     return "";
-  const size_t index = static_cast<size_t>(e);
+  const size_t index = static_cast<size_t>(e) - static_cast<size_t>(TensorType_UINT4);
   return EnumNamesTensorType()[index];
 }
 

runtime/onert/core/include/ir/DataType.h

@@ -39,7 +39,8 @@ enum class DataType
   QUANT_INT16_ASYMM = 10,
   QUANT_INT8_SYMM_PER_CHANNEL = 11,
   QUANT_INT16_SYMM = 12,
-  QUANT_INT4_SYMM = 13
+  QUANT_INT4_SYMM = 13,
+  QUANT_UINT4_ASYMM = 14
 };
 
 size_t sizeOfDataType(DataType data_type);

runtime/onert/core/src/ir/DataType.cc

@@ -54,6 +54,8 @@ size_t sizeOfDataType(DataType data_type)
       return sizeof(int16_t);
     case DataType::QUANT_INT4_SYMM:
       return sizeof(uint8_t); // Q: what is type size for int4?
+    case DataType::QUANT_UINT4_ASYMM:
+      return sizeof(uint8_t); // Q: what is type size for uint4?
     default:
       throw std::runtime_error{"Unsupported type size"};
   }

runtime/onert/core/src/loader/BaseLoader.h

@@ -94,7 +94,7 @@ template <typename LoaderDomain> class BaseLoader
 
   // Helper functions
   ir::Activation convertActivation(ActivationFunctionType type);
-  ir::DataType tensorTypeToDataType(TensorType type);
+  virtual ir::DataType tensorTypeToDataType(TensorType type);
   ir::OperandIndex tensorIdxToOperandIdx(int32_t tensorIdx);
   flexbuffers::Map getCustomOpAttrMap(const Operator *op);
 
@@ -321,8 +321,6 @@ ir::DataType BaseLoader<LoaderDomain>::BaseLoader::tensorTypeToDataType(const Te
     // case TensorType::TensorType_FLOAT64
     case TensorType::TensorType_UINT32:
       return ir::DataType::UINT32;
-    case TensorType::TensorType_INT4:
-      return ir::DataType::QUANT_INT4_SYMM;
     default:
       throw std::runtime_error(
         std::string("Unsupported tensor type: ").append(EnumNameTensorType(type)));

runtime/onert/core/src/loader/CircleLoader.cc

@@ -70,6 +70,7 @@ class CircleLoader final : public loader::BaseLoader<LoaderDomain>
   void loadInstanceNorm(const Operator *op, ir::Graph &subg);
   void loadBCQFullyConnected(const Operator *op, ir::Graph &subg);
   void loadBCQGather(const Operator *op, ir::Graph &subg);
+  virtual ir::DataType tensorTypeToDataType(TensorType type) override;
 
 public:
   using BaseLoader::BaseLoader;
@@ -149,6 +150,21 @@ class CircleLoader final : public loader::BaseLoader<LoaderDomain>
   }
 };
 
+
+ir::DataType CircleLoader::tensorTypeToDataType(const TensorType type)
+{
+  switch (type)
+  {
+    case TensorType::TensorType_INT4:
+      return ir::DataType::QUANT_INT4_SYMM;
+    case TensorType::TensorType_UINT4:
+      return ir::DataType::QUANT_UINT4_ASYMM;
+    default:
+      return BaseLoader::tensorTypeToDataType(type);
+  }
+}
+
+
 void CircleLoader::loadBatchMatMul(const Operator *op, ir::Graph &subg)
 {
   ir::OperandIndexSequence inputs;