148 lines
4.2 KiB
C++
148 lines
4.2 KiB
C++
// Copyright 2019 Google LLC
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//
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// This source code is licensed under the BSD-style license found in the
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// LICENSE file in the root directory of this source tree.
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#pragma once
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#include <gtest/gtest.h>
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#include <algorithm>
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#include <cassert>
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#include <cmath>
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#include <cstddef>
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#include <cstdlib>
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#include <functional>
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#include <random>
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#include <vector>
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#include <xnnpack.h>
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#include <xnnpack/AlignedAllocator.h>
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#include <xnnpack/params-init.h>
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#include <xnnpack/params.h>
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class GAvgPoolCWMicrokernelTester {
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public:
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enum class Variant {
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Native,
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Scalar,
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};
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inline GAvgPoolCWMicrokernelTester& elements(size_t elements) {
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assert(elements != 0);
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this->elements_ = elements;
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return *this;
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}
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inline size_t elements() const {
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return this->elements_;
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}
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inline GAvgPoolCWMicrokernelTester& channels(size_t channels) {
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assert(channels != 0);
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this->channels_ = channels;
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return *this;
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}
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inline size_t channels() const {
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return this->channels_;
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}
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inline GAvgPoolCWMicrokernelTester& qmin(uint8_t qmin) {
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this->qmin_ = qmin;
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return *this;
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}
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inline uint8_t qmin() const {
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return this->qmin_;
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}
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inline GAvgPoolCWMicrokernelTester& qmax(uint8_t qmax) {
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this->qmax_ = qmax;
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return *this;
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}
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inline uint8_t qmax() const {
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return this->qmax_;
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}
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inline GAvgPoolCWMicrokernelTester& iterations(size_t iterations) {
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this->iterations_ = iterations;
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return *this;
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}
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inline size_t iterations() const {
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return this->iterations_;
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}
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void Test(xnn_f32_gavgpool_cw_ukernel_function gavgpool, Variant variant = Variant::Native) const {
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std::random_device random_device;
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auto rng = std::mt19937(random_device());
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auto f32rng = std::bind(std::uniform_real_distribution<float>(), rng);
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std::vector<float> x(elements() * channels() + XNN_EXTRA_BYTES / sizeof(float));
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std::vector<float> y(channels());
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std::vector<float> y_ref(channels());
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for (size_t iteration = 0; iteration < iterations(); iteration++) {
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std::generate(x.begin(), x.end(), std::ref(f32rng));
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std::fill(y.begin(), y.end(), std::nanf(""));
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// Compute reference results, without clamping.
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for (size_t i = 0; i < channels(); i++) {
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float acc = 0.0f;
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for (size_t j = 0; j < elements(); j++) {
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acc += x[i * elements() + j];
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}
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y_ref[i] = acc / float(elements());
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}
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// Compute clamping parameters.
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const float accumulated_min = *std::min_element(y_ref.cbegin(), y_ref.cend());
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const float accumulated_max = *std::max_element(y_ref.cbegin(), y_ref.cend());
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const float accumulated_range = accumulated_max - accumulated_min;
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const float y_min = accumulated_min + float(qmin()) / 255.0f * accumulated_range;
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const float y_max = accumulated_max - float(255 - qmax()) / 255.0f * accumulated_range;
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// Prepare parameters.
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union xnn_f32_gavgpool_params params;
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switch (variant) {
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case Variant::Native:
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xnn_init_f32_gavgpool_params(
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¶ms, 1.0f / float(elements()), y_min, y_max, elements());
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break;
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case Variant::Scalar:
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xnn_init_scalar_f32_gavgpool_params(
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¶ms, 1.0f / float(elements()), y_min, y_max, elements());
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break;
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}
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// Clamp reference results.
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for (float& y_value : y_ref) {
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y_value = std::max(std::min(y_value, y_max), y_min);
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}
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// Call optimized micro-kernel.
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gavgpool(elements() * sizeof(float), channels(), x.data(), y.data(), ¶ms);
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// Verify results.
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for (size_t i = 0; i < channels(); i++) {
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ASSERT_LE(y[i], y_max)
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<< "at position " << i << ", elements = " << elements() << ", channels = " << channels();
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ASSERT_GE(y[i], y_min)
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<< "at position " << i << ", elements = " << elements() << ", channels = " << channels();
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ASSERT_NEAR(y[i], y_ref[i], std::abs(y_ref[i]) * 1.0e-6f)
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<< "at position " << i << ", elements = " << elements() << ", channels = " << channels();
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}
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}
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}
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private:
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size_t elements_{1};
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size_t channels_{1};
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uint8_t qmin_{0};
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uint8_t qmax_{255};
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size_t iterations_{15};
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};
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