// Copyright 2022 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #pragma once #include #include #include #include #include #include #include #include #include #include #include class WindowMicrokernelTester { public: inline WindowMicrokernelTester& rows(size_t rows) { assert(rows != 0); this->rows_ = rows; return *this; } inline size_t rows() const { return this->rows_; } inline WindowMicrokernelTester& batch(size_t batch) { assert(batch != 0); this->batch_ = batch; return *this; } inline size_t batch() const { return this->batch_; } inline WindowMicrokernelTester& shift(uint32_t shift) { assert(shift < 32); this->shift_ = shift; return *this; } inline uint32_t shift() const { return this->shift_; } inline WindowMicrokernelTester& inplace(bool inplace) { this->inplace_ = inplace; return *this; } inline bool inplace() const { return this->inplace_; } inline WindowMicrokernelTester& iterations(size_t iterations) { this->iterations_ = iterations; return *this; } inline size_t iterations() const { return this->iterations_; } void Test(xnn_s16_window_ukernel_function window) const { std::random_device random_device; auto rng = std::mt19937(random_device()); auto i16rng = std::bind(std::uniform_int_distribution(), std::ref(rng)); std::vector x(batch() * rows() + XNN_EXTRA_BYTES / sizeof(int16_t)); std::vector> w(batch() + XNN_EXTRA_BYTES / sizeof(int16_t)); std::vector y(batch() * rows() + (inplace() ? XNN_EXTRA_BYTES / sizeof(int16_t) : 0)); std::vector y_ref(batch() * rows()); const int16_t* x_data = inplace() ? y.data() : x.data(); for (size_t iteration = 0; iteration < iterations(); iteration++) { std::generate(x.begin(), x.end(), std::ref(i16rng)); std::generate(w.begin(), w.end(), std::ref(i16rng)); std::generate(y.begin(), y.end(), std::ref(i16rng)); std::generate(y_ref.begin(), y_ref.end(), std::ref(i16rng)); // Compute reference results. for (size_t m = 0; m < rows(); m++) { for (size_t n = 0; n < batch(); n++) { const int16_t x_value = x_data[m * batch() + n]; int32_t value = ((int32_t) x_value * (int32_t) w[n]) >> shift(); value = std::min(value, (int32_t) std::numeric_limits::max()); value = std::max(value, (int32_t) std::numeric_limits::min()); y_ref[m * batch() + n] = value; } } // Call optimized micro-kernel. window(rows(), batch(), x_data, w.data(), y.data(), shift()); // Verify results. for (size_t m = 0; m < rows(); m++) { for (size_t n = 0; n < batch(); n++) { ASSERT_EQ(y[m * batch() + n], y_ref[m * batch() + n]) << "at row " << m << " / " << rows() << ", shift " << shift() << ", batch " << n << " / " << batch(); } } } } private: size_t rows_{1}; size_t batch_{1}; uint32_t shift_{12}; bool inplace_{false}; size_t iterations_{15}; };