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Diffstat (limited to 'src/armnn/NetworkQuantizerUtils.cpp')
-rw-r--r-- | src/armnn/NetworkQuantizerUtils.cpp | 61 |
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 |