1 files changed, 61 insertions, 0 deletions
diff --git a/src/armnn/NetworkQuantizerUtils.cpp b/src/armnn/NetworkQuantizerUtils.cpp
new file mode 100644
index 0000000000..1bec63b58c
--- /dev/null
+++ b/src/armnn/NetworkQuantizerUtils.cpp
@@ -0,0 +1,61 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NetworkQuantizerUtils.hpp"
+
+#include <algorithm>
+#include <cmath>
+#include <stdint.h>
+
+namespace armnn
+{
+
+std::pair<int, float> ComputeQAsymmParams(int numBits, double min, double max)
+{
+    BOOST_ASSERT_MSG(min < max, "min >= max will result in invalid quantization.");
+    double highest = (1 << numBits) - 1;
+
+    min = std::min(0.0, min); // min <= 0.0
+    max = std::max(0.0, max); // max >= 0.0
+
+    // Assumes quantization range [0-highest]
+    double scale = (max-min) / highest;
+    double offset = -min / scale;
+
+    // Clamp offset [0-highest]
+    offset = std::max(0.0, std::min(highest, offset));
+
+    return std::make_pair(static_cast<int>(std::round(offset)), static_cast<float>(scale));
+}
+
+ConstTensor CreateQuantizedConst(const ConstTensor& tensor, std::vector<uint8_t>& backing)
+{
+    float scale = 0.0f;
+    int offset = 0;
+
+    // Reserve the backing memory
+    backing.resize(tensor.GetInfo().GetNumElements());
+
+    DataType type = tensor.GetInfo().GetDataType();
+    switch(type)
+    {
+        case DataType::Float32:
+        {
+            Quantize(static_cast<const float*>(tensor.GetMemoryArea()),
+                     backing.data(),
+                     backing.size(),
+                     scale,
+                     offset);
+        }
+            break;
+        default:
+            BOOST_ASSERT_MSG(false, "Can't quantize unsupported data type");
+    }
+
+    TensorInfo qInfo(tensor.GetInfo().GetShape(), DataType::QuantisedAsymm8, scale, offset);
+    return ConstTensor(qInfo, backing);
+}
+
+} // namespace armnn