From: Сергей Баранников/AI Tools Lab /SRR/Engineer/삼성전자 <s.barannikov@samsung.com>
Date: Mon, 5 Aug 2019 17:38:27 +0000 (+0300)
Subject: [mir_caffe] Rename DTYPE to DataType (#6244)
X-Git-Tag: submit/tizen/20190809.050447~149
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=8c3b8918296f774a1167f98a3d506b228822553e;p=platform%2Fcore%2Fml%2Fnnfw.git

[mir_caffe] Rename DTYPE to DataType (#6244)

Replace deprecated `DTYPE` with `DataType`.

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

diff --git a/compiler/mir-caffe-importer/caffe_op_creator.cpp b/compiler/mir-caffe-importer/caffe_op_creator.cpp
index 4e13681..3b801ab 100644
--- a/compiler/mir-caffe-importer/caffe_op_creator.cpp
+++ b/compiler/mir-caffe-importer/caffe_op_creator.cpp
@@ -90,7 +90,7 @@ static TensorVariant fixGroupedKernel(int groups, const TensorVariant &folded_ke
     else
     {
       // fill element of output kernel with zero element
-      assert(folded_kernel.getDataType() == mir::DTYPE::FLOAT32 &&
+      assert(folded_kernel.getDataType() == mir::DataType::FLOAT32 &&
              "unsupported data type, add appropriate zero element creation");
       auto elem = reinterpret_cast<float *>(unfold_kernel.at(idx));
       *elem = 0.0f;
@@ -202,16 +202,16 @@ TensorVariant CaffeOpCreator::convertBlob(const BlobProto &blob)
 {
   const void *src_data;
 
-  DTYPE dtype;
+  mir::DataType dtype;
   if (blob.data_size() != 0)
   {
     assert(blob.double_data_size() == 0);
-    dtype = DTYPE::FLOAT32;
+    dtype = mir::DataType::FLOAT32;
     src_data = blob.data().data();
   }
   else if (blob.double_data_size() != 0)
   {
-    dtype = DTYPE::FLOAT64;
+    dtype = mir::DataType::FLOAT64;
     src_data = blob.double_data().data();
   }
   else
@@ -754,7 +754,7 @@ CaffeOpCreator::convertEltwise(const caffe::LayerParameter &layer,
         {
           if (opts.coeff().Get(i) != 1.0f)
           {
-            TensorVariant coeff_tensor(DTYPE::FLOAT32, Shape{1}, &opts.coeff().Get(i));
+            TensorVariant coeff_tensor(mir::DataType::FLOAT32, Shape{1}, &opts.coeff().Get(i));
             auto coeff_const = createOp<ops::ConstantOp>(layer.name() + "_const", coeff_tensor);
             std::vector<mir::Operation::Output *> mul_inputs;
             mul_inputs.push_back(coeff_const->getOutput(0));
@@ -805,7 +805,7 @@ void CaffeOpCreator::checkLSTM(const caffe::LayerParameter &layer,
 static TensorVariant createZeroedTensor(const mir::Shape &shape)
 {
   // TODO For now it is hardcoded float32.
-  auto elem_type = mir::DTYPE::FLOAT32;
+  auto elem_type = mir::DataType::FLOAT32;
   std::vector<float> zeros(static_cast<std::size_t>(shape.numElements()), 0.0f);
   return TensorVariant(elem_type, shape, zeros.data());
 }