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