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https://github.com/saymrwulf/onnxruntime.git
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7b39f5090c
* Add Attention op for multi head self attention in BERT * Add test cases * Move op from kOnnxDomain to kMSDomain. Limit test to run by CUDA provider only. * fix test * Add float16 test * fix cpu build error * handle cuda error * get last cuda error when failed
57 lines
1.7 KiB
C++
57 lines
1.7 KiB
C++
#pragma once
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#include<random>
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#include "core/util/math.h"
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#include "test/providers/provider_test_utils.h"
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namespace onnxruntime {
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namespace test {
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template <class T>
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inline void FillRandom(std::vector<T>& val, T min, T max) {
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static std::default_random_engine generator;
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std::uniform_real_distribution<float> distribution(min, max);
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for (size_t i = 0; i < val.size(); ++i) {
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val[i] = T(distribution(generator));
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}
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}
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inline std::pair<float, float> MeanStdev(std::vector<float>& v) {
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float sum = std::accumulate(v.begin(), v.end(), 0.0f);
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float mean = sum / v.size();
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std::vector<float> diff(v.size());
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std::transform(v.begin(), v.end(), diff.begin(),
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std::bind(std::minus<float>(), std::placeholders::_1, mean));
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float sq_sum = std::inner_product(diff.begin(), diff.end(), diff.begin(), 0.0f);
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float stdev = std::sqrt(sq_sum / v.size());
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return std::make_pair(mean, stdev);
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}
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inline void Normalize(std::vector<float>& v,
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std::pair<float, float>& mean_stdev, bool normalize_variance) {
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float mean = mean_stdev.first;
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float stdev = mean_stdev.second;
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std::transform(v.begin(), v.end(), v.begin(),
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std::bind(std::minus<float>(), std::placeholders::_1, mean));
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if (normalize_variance) {
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std::transform(v.begin(), v.end(), v.begin(),
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std::bind(std::divides<float>(), std::placeholders::_1, stdev));
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}
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}
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inline std::vector<MLFloat16> ToFloat16(const std::vector<float>& data) {
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std::vector<MLFloat16> result;
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result.reserve(data.size());
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for (size_t i = 0; i < data.size(); i++) {
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result.push_back(MLFloat16(math::floatToHalf(data[i])));
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}
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return result;
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}
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} // namespace test
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} // namespace onnxruntime
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