AffineQuant.h

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#pragma once
#include "common/Export.h"
 
 
#include "common/Result.h"
 
#include <cstdint>
#include <span>
#include <vector>
 
namespace eve::tensor {
class OnnxCompute;
}
namespace eve::tensor::affine {
 
struct QuantizedActivation {
    std::vector<uint8_t> values;
    float                scale     = 1;
    uint8_t              zeroPoint = 0;
};
 
struct ByteView {
    std::span<const uint8_t> bytes;
    bool                     signedValues = false;
};
 
[[nodiscard]] EVENGINE_API_DOMAINS Result<QuantizedActivation> dynamicQuantize(std::span<const float> input);
 
[[nodiscard]] EVENGINE_API_DOMAINS Result<std::vector<uint8_t>> quantize(std::span<const float> input, float scale,
                                                                         int zeroPoint, bool signedValues);
 
[[nodiscard]] Result<std::vector<float>> dequantize(ByteView input, std::span<const float> scales,
                                                    std::span<const int32_t> zeros, size_t inner = 1);
 
[[nodiscard]] EVENGINE_API_DOMAINS Result<std::vector<int32_t>> matmul(ByteView a, ByteView b, size_t m, size_t k,
                                                                       size_t n, int aZero = 0, int bZero = 0,
                                                                       OnnxCompute* compute = nullptr);
 
struct ConvShape {
    int batch = 1, channels = 1, height = 1, width = 1;
    int outputs = 1, kernelH = 1, kernelW = 1;
    int strideH = 1, strideW = 1, dilationH = 1, dilationW = 1;
    int padTop = 0, padLeft = 0, padBottom = 0, padRight = 0, groups = 1;
};
 
[[nodiscard]] EVENGINE_API_DOMAINS Result<std::vector<int32_t>> conv(ByteView x, ByteView w, const ConvShape& shape,
                                                                     int xZero, std::span<const int32_t> wZeros,
                                                                     OnnxCompute* compute = nullptr);
}  // namespace eve::tensor::affine