1 files changed, 0 insertions, 134 deletions
diff --git a/tests/validation/CPP/SoftmaxLayer.cpp b/tests/validation/CPP/SoftmaxLayer.cpp
deleted file mode 100644
index 8e8cc1bd25..0000000000
--- a/tests/validation/CPP/SoftmaxLayer.cpp
+++ /dev/null
@@ -1,134 +0,0 @@
-/*
- * 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