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// Copyright (c) Facebook, Inc. and its affiliates.
// All rights reserved.
//
// 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 <cstddef>
#include <cstdlib>
#include <functional>
#include <random>
#include <vector>
#include <xnnpack.h>
#include <xnnpack/params-init.h>
#include <xnnpack/params.h>
#include <xnnpack/requantization.h>
class VAddMicrokernelTester {
public:
enum class Variant {
Native,
Scalar,
};
inline VAddMicrokernelTester& n(size_t n) {
assert(n != 0);
this->n_ = n;
return *this;
}
inline size_t n() const {
return this->n_;
}
inline VAddMicrokernelTester& inplace_a(bool inplace_a) {
this->inplace_a_ = inplace_a;
return *this;
}
inline bool inplace_a() const {
return this->inplace_a_;
}
inline VAddMicrokernelTester& inplace_b(bool inplace_b) {
this->inplace_b_ = inplace_b;
return *this;
}
inline bool inplace_b() const {
return this->inplace_b_;
}
inline VAddMicrokernelTester& a_scale(float a_scale) {
assert(a_scale > 0.0f);
assert(std::isnormal(a_scale));
this->a_scale_ = a_scale;
return *this;
}
inline float a_scale() const {
return this->a_scale_;
}
inline VAddMicrokernelTester& a_zero_point(uint8_t a_zero_point) {
this->a_zero_point_ = a_zero_point;
return *this;
}
inline uint8_t a_zero_point() const {
return this->a_zero_point_;
}
inline VAddMicrokernelTester& b_scale(float b_scale) {
assert(b_scale > 0.0f);
assert(std::isnormal(b_scale));
this->b_scale_ = b_scale;
return *this;
}
inline float b_scale() const {
return this->b_scale_;
}
inline VAddMicrokernelTester& b_zero_point(uint8_t b_zero_point) {
this->b_zero_point_ = b_zero_point;
return *this;
}
inline uint8_t b_zero_point() const {
return this->b_zero_point_;
}
inline VAddMicrokernelTester& y_scale(float y_scale) {
assert(y_scale > 0.0f);
assert(std::isnormal(y_scale));
this->y_scale_ = y_scale;
return *this;
}
inline float y_scale() const {
return this->y_scale_;
}
inline VAddMicrokernelTester& y_zero_point(uint8_t y_zero_point) {
this->y_zero_point_ = y_zero_point;
return *this;
}
inline uint8_t y_zero_point() const {
return this->y_zero_point_;
}
inline VAddMicrokernelTester& qmin(uint8_t qmin) {
this->qmin_ = qmin;
return *this;
}
inline uint8_t qmin() const {
return this->qmin_;
}
inline VAddMicrokernelTester& qmax(uint8_t qmax) {
this->qmax_ = qmax;
return *this;
}
inline uint8_t qmax() const {
return this->qmax_;
}
inline VAddMicrokernelTester& iterations(size_t iterations) {
this->iterations_ = iterations;
return *this;
}
inline size_t iterations() const {
return this->iterations_;
}
void Test(xnn_q8_vadd_ukernel_function vadd, Variant variant = Variant::Native) const {
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);
std::vector<uint8_t> a(n() + XNN_EXTRA_BYTES / sizeof(uint8_t));
std::vector<uint8_t> b(n() + XNN_EXTRA_BYTES / sizeof(uint8_t));
std::vector<uint8_t> y(n() + (inplace_a() || inplace_b() ? XNN_EXTRA_BYTES / sizeof(uint8_t) : 0));
std::vector<float> y_fp(n());
std::vector<uint8_t> y_ref(n());
for (size_t iteration = 0; iteration < iterations(); iteration++) {
std::generate(a.begin(), a.end(), std::ref(u8rng));
std::generate(b.begin(), b.end(), std::ref(u8rng));
if (inplace_a() || inplace_b()) {
std::generate(y.begin(), y.end(), std::ref(u8rng));
} else {
std::fill(y.begin(), y.end(), 0xA5);
}
const uint8_t* a_data = inplace_a() ? y.data() : a.data();
const uint8_t* b_data = inplace_b() ? y.data() : b.data();
// Prepare quantization parameters.
xnn_q8_add_params quantization_params = { };
switch (variant) {
case Variant::Native:
quantization_params = xnn_init_q8_add_params(
a_zero_point(), b_zero_point(), y_zero_point(),
a_scale() / y_scale(), b_scale() / y_scale(),
qmin(), qmax());
break;
case Variant::Scalar:
quantization_params = xnn_init_scalar_q8_add_params(
a_zero_point(), b_zero_point(), y_zero_point(),
a_scale() / y_scale(), b_scale() / y_scale(),
qmin(), qmax());
break;
}
const xnn_q8_add_params scalar_quantization_params =
xnn_init_scalar_q8_add_params(
a_zero_point(), b_zero_point(), y_zero_point(),
a_scale() / y_scale(), b_scale() / y_scale(),
qmin(), qmax());
// Compute reference results.
for (size_t i = 0; i < n(); i++) {
y_fp[i] = float(y_zero_point()) +
float(int32_t(a_data[i]) - int32_t(a_zero_point())) * (a_scale() / y_scale()) +
float(int32_t(b_data[i]) - int32_t(b_zero_point())) * (b_scale() / y_scale());
y_fp[i] = std::min<float>(y_fp[i], float(qmax()));
y_fp[i] = std::max<float>(y_fp[i], float(qmin()));
y_ref[i] = xnn_add_quantize(a_data[i], b_data[i], scalar_quantization_params);
}
// Call optimized micro-kernel.
vadd(n(), a_data, b_data, y.data(), &quantization_params);
// Verify results.
for (size_t i = 0; i < n(); i++) {
ASSERT_LE(uint32_t(y[i]), uint32_t(qmax()))
<< "at " << i << ", n = " << n();
ASSERT_GE(uint32_t(y[i]), uint32_t(qmin()))
<< "at " << i << ", n = " << n();
ASSERT_NEAR(float(int32_t(y[i])), y_fp[i], 0.6f)
<< "at " << i << ", n = " << n();
ASSERT_EQ(uint32_t(y_ref[i]), uint32_t(y[i]))
<< "at " << i << ", n = " << n();
}
}
}
private:
size_t n_{1};
bool inplace_a_{false};
bool inplace_b_{false};
float a_scale_{0.75f};
float b_scale_{1.25f};
float y_scale_{0.96875f};
uint8_t a_zero_point_{121};
uint8_t b_zero_point_{127};
uint8_t y_zero_point_{133};
uint8_t qmin_{0};
uint8_t qmax_{255};
size_t iterations_{15};
};