COMPMID-1539 Implement YOLOLayer on CL
Change-Id: I332c0703e1399fca0c5b724529b54a28f49c88da
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/146842
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/tests/validation/reference/YOLOLayer.cpp b/tests/validation/reference/YOLOLayer.cpp
new file mode 100644
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+++ b/tests/validation/reference/YOLOLayer.cpp
@@ -0,0 +1,80 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "YOLOLayer.h"
+
+#include "ActivationLayer.h"
+
+#include "arm_compute/core/Types.h"
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
+SimpleTensor<T> yolo_layer(const SimpleTensor<T> &src, const ActivationLayerInfo &info, int32_t num_classes)
+{
+ // Create reference
+ SimpleTensor<T> dst{ src.shape(), src.data_type() };
+
+ // Compute reference
+ const T a(info.a());
+ const T b(info.b());
+
+ for(int i = 0; i < src.num_elements(); ++i)
+ {
+ const size_t z = index2coord(dst.shape(), i).z() % (num_classes + 5);
+
+ if(z != 2 && z != 3)
+ {
+ dst[i] = activate_float<T>(src[i], a, b, info.activation());
+ }
+ else
+ {
+ dst[i] = src[i];
+ }
+ }
+
+ return dst;
+}
+
+template <>
+SimpleTensor<uint8_t> yolo_layer<uint8_t>(const SimpleTensor<uint8_t> &src, const ActivationLayerInfo &info, int32_t num_classes)
+{
+ SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
+ SimpleTensor<float> dst_tmp = yolo_layer<float>(src_tmp, info, num_classes);
+ SimpleTensor<uint8_t> dst = convert_to_asymmetric(dst_tmp, src.quantization_info());
+ return dst;
+}
+
+template SimpleTensor<float> yolo_layer(const SimpleTensor<float> &src, const ActivationLayerInfo &info, int32_t num_classes);
+template SimpleTensor<half> yolo_layer(const SimpleTensor<half> &src, const ActivationLayerInfo &info, int32_t num_classes);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute