COMPMID-556: Rename CPP folder to reference

Change-Id: I147644349547c4e3804a80b564a9ad95131ad2d0
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/111560
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>

1 files changed, 134 insertions, 0 deletions

diff --git a/tests/validation/reference/SoftmaxLayer.cpp b/tests/validation/reference/SoftmaxLayer.cpp
new file mode 100644
index 0000000000..8e8cc1bd25
--- /dev/null
+++ b/tests/validation/reference/SoftmaxLayer.cpp
@@ -0,0 +1,134 @@
+/*
+ * Copyright (c) 2017 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 "SoftmaxLayer.h"
+
+#include "arm_compute/core/Types.h"
+#include "tests/validation/FixedPoint.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> softmax_layer(const SimpleTensor<T> &src)
+{
+    // Create reference
+    SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+
+    // Compute reference
+    const int cols       = src.shape()[0];
+    const int upper_dims = src.num_elements() / cols;
+
+    for(int r = 0; r < upper_dims; ++r)
+    {
+        const T *src_row_ptr = src.data() + r * cols;
+        T       *dst_row_ptr = dst.data() + r * cols;
+
+        // Find max
+        const T max = *std::max_element(src_row_ptr, src_row_ptr + cols);
+
+        // Regularize
+        T sum(0.f);
+        std::transform(src_row_ptr, src_row_ptr + cols, dst_row_ptr, [&sum, max](T val)
+        {
+            const T res(std::exp(val - max));
+            sum += res;
+            return res;
+        });
+
+        // Normalize
+        std::transform(dst_row_ptr, dst_row_ptr + cols, dst_row_ptr, [sum](T val)
+        {
+            return val / sum;
+        });
+    }
+
+    return dst;
+}
+
+template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
+SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src)
+{
+    using namespace fixed_point_arithmetic;
+
+    // Create reference
+    SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+
+    // Compute reference
+    const int cols       = src.shape()[0];
+    const int upper_dims = src.num_elements() / cols;
+
+    for(int r = 0; r < upper_dims; ++r)
+    {
+        const T *src_row_ptr = src.data() + r * cols;
+        T       *dst_row_ptr = dst.data() + r * cols;
+
+        // Find max
+        const fixed_point<T> max(*std::max_element(src_row_ptr, src_row_ptr + cols), src.fixed_point_position(), true);
+
+        // Regularize
+        using promoted_type = fixed_point_arithmetic::traits::promote_t<T>;
+        fixed_point<promoted_type> sum(0, src.fixed_point_position(), true);
+        std::transform(src_row_ptr, src_row_ptr + cols, dst_row_ptr, [&](T val)
+        {
+            const fixed_point<T> res = exp(fixed_point<T>(val, src.fixed_point_position(), true) - max);
+            sum                      = add(sum, fixed_point<promoted_type>(res.raw(), src.fixed_point_position(), true));
+            return res.raw();
+        });
+
+        // Normalize
+        fixed_point<T> saturated_sum(sum);
+        std::transform(dst_row_ptr, dst_row_ptr + cols, dst_row_ptr, [&](T val)
+        {
+            return div(fixed_point<T>(val, src.fixed_point_position(), true), saturated_sum).raw();
+        });
+    }
+
+    return dst;
+}
+
+template <>
+SimpleTensor<uint8_t> softmax_layer<uint8_t>(const SimpleTensor<uint8_t> &src)
+{
+    // Note: Output quantization info should always have scale = 1/256 and offset = 0
+    const QuantizationInfo output_quantization_info = QuantizationInfo(1.f / 256, 0);
+
+    SimpleTensor<float>   src_tmp = convert_from_asymmetric(src);
+    SimpleTensor<float>   dst_tmp = softmax_layer<float>(src_tmp);
+    SimpleTensor<uint8_t> dst     = convert_to_asymmetric(dst_tmp, output_quantization_info);
+    return dst;
+}
+
+template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src);
+template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src);
+template SimpleTensor<qint8_t> softmax_layer(const SimpleTensor<qint8_t> &src);
+template SimpleTensor<qint16_t> softmax_layer(const SimpleTensor<qint16_t> &src);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute