#ifndef MIGRAPHX_GUARD_OPERATORS_QUANTIZE_LINEAR_HPP #define MIGRAPHX_GUARD_OPERATORS_QUANTIZE_LINEAR_HPP #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace migraphx { inline namespace MIGRAPHX_INLINE_NS { namespace op { struct quantizelinear { std::string name() const { return "quantizelinear"; } shape compute_shape(std::vector inputs) const { if(inputs.size() == 3) { return {inputs[2].type(), inputs[0].lens(), inputs[0].strides()}; } return {shape::uint8_type, inputs[0].lens(), inputs[0].strides()}; } argument compute(const shape& output_shape, std::vector args) const { auto x = args.at(0); auto y_scale = args.at(1); std::vector zeros(output_shape.elements(), 0); argument y_zero_point{output_shape, zeros.data()}; if(args.size() == 3) { y_zero_point = args.at(2); } argument result{output_shape}; visit_all(result, y_zero_point)([&](auto output, auto zero_pts) { x.visit([&](auto input) { y_scale.visit([&](auto scales) { using quant_type = typename decltype(output)::value_type; auto min_value = std::numeric_limits::min(); auto max_value = std::numeric_limits::max(); par_for(output_shape.elements(), [&](auto i) { int64_t quantized = static_cast(std::round(input[i] / scales[i])) + static_cast(zero_pts[i]); output[i] = std::max(static_cast(min_value), std::min(static_cast(max_value), quantized)); }); }); }); }); return result; } }; } // namespace op } // namespace MIGRAPHX_INLINE_NS } // namespace migraphx #endif