arm_compute v17.09
Change-Id: I4bf8f4e6e5f84ce0d5b6f5ba570d276879f42a81
diff --git a/tests/validation/CPP/QuantizationLayer.cpp b/tests/validation/CPP/QuantizationLayer.cpp
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+/*
+ * 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 "QuantizationLayer.h"
+
+#include <cmath>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
+SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<T> &src)
+{
+ // Create reference
+ SimpleTensor<uint8_t> dst{ src.shape(), DataType::U8 };
+
+ const int width = src.shape().x();
+ const int height = src.shape().y();
+ const int depth = src.shape().z();
+ const int stride_w = width * height * depth;
+ const int num_batches = src.shape().total_size_upper(3);
+
+ for(int k = 0; k < num_batches; ++k)
+ {
+ // Compute min and max of the 3D tensor
+ float min = src[k * stride_w];
+ float max = src[k * stride_w];
+
+ // Look for min and max values
+ for(int i = 1; i < stride_w; ++i)
+ {
+ float val = src[i + k * stride_w];
+ min = std::min(min, val);
+ max = std::max(max, val);
+ }
+
+ // Saturate the result in case min = max
+ if(min == max)
+ {
+ min = 0.0f;
+ max = 1.0f;
+ }
+
+ const float range = max - min;
+
+ for(int i = 0; i < stride_w; ++i)
+ {
+ // map values to range [0.0, 1.0]
+ float val = src[i + k * stride_w];
+ const float normalized = (val - min) / range;
+ dst[i + k * stride_w] = static_cast<uint8_t>(std::min(255.0f, normalized * 256.0f));
+ }
+ }
+
+ return dst;
+}
+
+template SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<float> &src);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute