commit 40f51a63c8e7258db15269427ae4fe1ad199c550
author Georgios Pinitas <georgios.pinitas@arm.com> Sat Nov 21 03:04:18 2020 +0000
committer Georgios Pinitas <georgios.pinitas@arm.com> Tue Dec 01 10:41:54 2020 +0000
tree 353253a41863966995a45556731e7181a643c003
parent 327800401c4185d98fcc01b9c9efbc038a4228ed

Update default C++ standard to C++14

(3RDPARTY_UPDATE)

Resolves: COMPMID-3849

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I6369f112337310140e2d6c8e79630cd11138dfa0
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4544
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

tests/RawTensor.cpp

diff --git a/tests/RawTensor.cpp b/tests/RawTensor.cpp
index a32886e..8d610a4 100644
--- a/tests/RawTensor.cpp
+++ b/tests/RawTensor.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 Arm Limited.
+ * Copyright (c) 2017-2020 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -30,20 +30,20 @@
 RawTensor::RawTensor(TensorShape shape, Format format)
     : SimpleTensor(shape, format)
 {
-    _buffer = support::cpp14::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size());
+    _buffer = std::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size());
 }
 
 RawTensor::RawTensor(TensorShape shape, DataType data_type, int num_channels)
     : SimpleTensor(shape, data_type, num_channels)
 {
-    _buffer = support::cpp14::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size());
+    _buffer = std::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size());
 }
 
 RawTensor::RawTensor(const RawTensor &tensor)
     : SimpleTensor(tensor.shape(), tensor.data_type(), tensor.num_channels())
 {
     _format = tensor.format();
-    _buffer = support::cpp14::make_unique<uint8_t[]>(num_elements() * num_channels() * element_size());
+    _buffer = std::make_unique<uint8_t[]>(num_elements() * num_channels() * element_size());
     std::copy_n(tensor.data(), num_elements() * num_channels() * element_size(), _buffer.get());
 }