[mir_tflite] Rename DTYPE to DataType (#6246)

Replace deprecated `DTYPE` with `DataType`.

Signed-off-by: Sergei Barannikov <s.barannikov@samsung.com>

diff --git a/compiler/mir-tflite-importer/tflite_importer.cpp b/compiler/mir-tflite-importer/tflite_importer.cpp
index 83adf47..9920e3f 100644 (file)
--- a/compiler/mir-tflite-importer/tflite_importer.cpp
+++ b/compiler/mir-tflite-importer/tflite_importer.cpp
@@ -352,17 +352,17 @@ mir::TensorVariant TfliteImporter::createTensor(const Tensor *t, const Buffer *b
 {
   assert(b->data() != nullptr);
 
-  mir::DTYPE type;
+  mir::DataType type;
   switch (t->type())
   {
     case TensorType_INT32:
-      type = mir::DTYPE::INT32;
+      type = mir::DataType::INT32;
       break;
     case TensorType_FLOAT32:
-      type = mir::DTYPE::FLOAT32;
+      type = mir::DataType::FLOAT32;
       break;
     case TensorType_INT64:
-      type = mir::DTYPE::INT64;
+      type = mir::DataType::INT64;
       break;
     default:
       throw std::runtime_error(std::string("Unsupported tensor type: ") +

diff --git a/compiler/mir-tflite-importer/tflite_op_creator.cpp b/compiler/mir-tflite-importer/tflite_op_creator.cpp
index 1738128..1755f2c 100644 (file)
--- a/compiler/mir-tflite-importer/tflite_op_creator.cpp
+++ b/compiler/mir-tflite-importer/tflite_op_creator.cpp
@@ -343,11 +343,11 @@ TFLiteOpCreator::convertMul(const ::tflite::MulOptions *opts,
     {
       const auto &input1_tensor = constant1_op->getValue();
       const auto &input2_tensor = constant2_op->getValue();
-      if (input1_tensor.getDataType() == mir::DTYPE::INT32 &&
-          input2_tensor.getDataType() == mir::DTYPE::INT32)
+      if (input1_tensor.getDataType() == mir::DataType::INT32 &&
+          input2_tensor.getDataType() == mir::DataType::INT32)
       {
         const auto &output_shape = inputs[0]->getShape();
-        mir::TensorVariant res_tensor(mir::DTYPE::INT32, output_shape);
+        mir::TensorVariant res_tensor(mir::DataType::INT32, output_shape);
 
         mir::Tensor<int32_t> input1_accessor(input1_tensor);
         mir::Tensor<int32_t> input2_accessor(input2_tensor);
@@ -494,7 +494,7 @@ TFLiteOpCreator::convertPad(const ::tflite::PadOptions * /*opts*/,
   }
 
   float filler_value = 0.0;
-  mir::Scalar filler(reinterpret_cast<char *>(&filler_value), mir::DTYPE::FLOAT32,
+  mir::Scalar filler(reinterpret_cast<char *>(&filler_value), mir::DataType::FLOAT32,
                      sizeof(filler_value));
 
   // FIXME Do we really need num_dims as an argument? It looks redundant.
@@ -621,7 +621,7 @@ TFLiteOpCreator::convertStridedSlice(const ::tflite::StridedSliceOptions *opts,
     if (constant_op != nullptr)
     {
       const auto &input_tensor = constant_op->getValue();
-      if (input_tensor.getDataType() == mir::DTYPE::INT32)
+      if (input_tensor.getDataType() == mir::DataType::INT32)
       {
         mir::Shape output_shape(num_dims);
         for (int32_t i = 0; i < num_dims; ++i)
@@ -636,7 +636,7 @@ TFLiteOpCreator::convertStridedSlice(const ::tflite::StridedSliceOptions *opts,
           }
         }
 
-        mir::TensorVariant res_tensor(mir::DTYPE::INT32, output_shape);
+        mir::TensorVariant res_tensor(mir::DataType::INT32, output_shape);
         mir::Tensor<int32_t> input_accessor(input_tensor);
         mir::Tensor<int32_t> res_accessor(res_tensor);
 
@@ -691,7 +691,7 @@ TFLiteOpCreator::convertShape(const ::tflite::ShapeOptions * /*opts*/,
   data.reserve(static_cast<uint64_t>(rank));
   for (int32_t i = 0; i < rank; i++)
     data.emplace_back(input_shape.dim(i));
-  mir::TensorVariant tensor(mir::DTYPE::INT32, output_shape, data.data());
+  mir::TensorVariant tensor(mir::DataType::INT32, output_shape, data.data());
   auto result = createOp<ops::ConstantOp>(tensor);
   return {result->getOutput(0)};
 }