263 lines
7.6 KiB
C++
263 lines
7.6 KiB
C++
// 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 <cmath>
|
|
#include <cstddef>
|
|
#include <cstdlib>
|
|
#include <functional>
|
|
#include <random>
|
|
#include <vector>
|
|
|
|
#include <xnnpack.h>
|
|
#include <xnnpack/AlignedAllocator.h>
|
|
#include <xnnpack/math.h>
|
|
#include <xnnpack/pack.h>
|
|
#include <xnnpack/params-init.h>
|
|
#include <xnnpack/params.h>
|
|
|
|
|
|
class DWConv2DMicrokernelTester {
|
|
public:
|
|
enum class Variant {
|
|
Native,
|
|
Scalar,
|
|
};
|
|
|
|
inline DWConv2DMicrokernelTester& padding_left(uint32_t padding_left) {
|
|
this->padding_left_ = padding_left;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_left() const {
|
|
return this->padding_left_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& padding_right(uint32_t padding_right) {
|
|
this->padding_right_ = padding_right;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_right() const {
|
|
return this->padding_right_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& padding_top(uint32_t padding_top) {
|
|
this->padding_top_ = padding_top;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_top() const {
|
|
return this->padding_top_;
|
|
}
|
|
|
|
|
|
inline DWConv2DMicrokernelTester& padding_bottom(uint32_t padding_bottom) {
|
|
this->padding_bottom_ = padding_bottom;
|
|
return *this;
|
|
}
|
|
inline uint32_t padding_bottom() const {
|
|
return this->padding_bottom_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& input_height(uint32_t input_height) {
|
|
assert(input_height >= 1);
|
|
this->input_height_ = input_height;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t input_height() const {
|
|
return this->input_height_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& input_width(uint32_t input_width) {
|
|
assert(input_width >= 1);
|
|
this->input_width_ = input_width;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t input_width() const {
|
|
return this->input_width_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& subsampling(uint32_t subsampling) {
|
|
assert(subsampling >= 1);
|
|
this->subsampling_ = subsampling;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t subsampling() const {
|
|
return this->subsampling_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& kernel_height(uint32_t kernel_height) {
|
|
assert(kernel_height != 0);
|
|
this->kernel_height_ = kernel_height;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t kernel_height() const {
|
|
return this->kernel_height_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& kernel_width(uint32_t kernel_width) {
|
|
assert(kernel_width != 0);
|
|
this->kernel_width_ = kernel_width;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t kernel_width() const {
|
|
return this->kernel_width_;
|
|
}
|
|
|
|
inline uint32_t kernel_size() const {
|
|
return kernel_height() * kernel_width();
|
|
}
|
|
|
|
inline uint32_t output_height() const {
|
|
const uint32_t padded_input_height = padding_top() + input_height() + padding_bottom();
|
|
if (padded_input_height <= kernel_height()) {
|
|
return 1;
|
|
} else {
|
|
return (padded_input_height - kernel_height()) / subsampling() + 1;
|
|
}
|
|
}
|
|
|
|
inline uint32_t output_width() const {
|
|
const uint32_t padded_input_width = padding_left() + input_width() + padding_right();
|
|
if (padded_input_width <= kernel_width()) {
|
|
return 1;
|
|
} else {
|
|
return (padded_input_width - kernel_width()) / subsampling() + 1;
|
|
}
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& qmin(uint8_t qmin) {
|
|
this->qmin_ = qmin;
|
|
return *this;
|
|
}
|
|
|
|
inline uint8_t qmin() const {
|
|
return this->qmin_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& qmax(uint8_t qmax) {
|
|
this->qmax_ = qmax;
|
|
return *this;
|
|
}
|
|
|
|
inline uint8_t qmax() const {
|
|
return this->qmax_;
|
|
}
|
|
|
|
inline DWConv2DMicrokernelTester& iterations(size_t iterations) {
|
|
this->iterations_ = iterations;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t iterations() const {
|
|
return this->iterations_;
|
|
}
|
|
|
|
void Test(xnn_f32_dwconv2d_chw_ukernel_function dwconv, 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>(0.0f, 1.0f), rng);
|
|
|
|
std::vector<float, AlignedAllocator<float, 64>> input(input_height() * input_width() + 2 * XNN_EXTRA_BYTES);
|
|
std::vector<float> zero(input_width() + 2 * XNN_EXTRA_BYTES);
|
|
std::vector<float> packed_weights(kernel_size() + 1);
|
|
std::vector<float, AlignedAllocator<float, 64>> output(output_height() * output_width());
|
|
std::vector<float> output_ref(output_height() * output_width());
|
|
|
|
for (size_t iteration = 0; iteration < iterations(); iteration++) {
|
|
std::generate(input.begin(), input.end(), std::ref(f32rng));
|
|
std::generate(packed_weights.begin(), packed_weights.end(), std::ref(f32rng));
|
|
std::fill(output.begin(), output.end(), nanf(""));
|
|
|
|
for (size_t oy = 0; oy < output_height(); oy++) {
|
|
for (size_t ox = 0; ox < output_width(); ox++) {
|
|
float acc = packed_weights[0];
|
|
for (size_t ky = 0; ky < kernel_height(); ky++) {
|
|
const size_t iy = oy * subsampling() + ky - padding_top();
|
|
for (size_t kx = 0; kx < kernel_width(); kx++) {
|
|
const size_t ix = ox * subsampling() + kx - padding_left();
|
|
if (ix < input_width() && iy < input_height()) {
|
|
const float input_val = input[iy * input_width() + ix];
|
|
const float kernel_val = packed_weights[1 + ky * kernel_width() + kx];
|
|
acc += input_val * kernel_val;
|
|
}
|
|
}
|
|
}
|
|
output_ref[oy * output_width() + ox] = acc;
|
|
}
|
|
}
|
|
|
|
// Compute clamping parameters.
|
|
const float accumulated_min = *std::min_element(output_ref.cbegin(), output_ref.cend());
|
|
const float accumulated_max = *std::max_element(output_ref.cbegin(), output_ref.cend());
|
|
const float accumulated_range = accumulated_max - accumulated_min;
|
|
const float output_min = accumulated_min + accumulated_range / 255.0f * float(qmin());
|
|
const float output_max = accumulated_max - accumulated_range / 255.0f * float(255 - qmax());
|
|
|
|
// Prepare parameters.
|
|
xnn_f32_chw_params chw_params;
|
|
switch (variant) {
|
|
case Variant::Native:
|
|
xnn_init_f32_chw_params(&chw_params, input_width(), output_min, output_max);
|
|
break;
|
|
case Variant::Scalar:
|
|
xnn_init_scalar_f32_chw_params(&chw_params, input_width(), output_min, output_max);
|
|
break;
|
|
}
|
|
|
|
// Clamp reference results.
|
|
for (float& output_val : output_ref) {
|
|
output_val = std::max(std::min(output_val, output_max), output_min);
|
|
}
|
|
|
|
// Call optimized micro-kernel.
|
|
dwconv(
|
|
input_height(), input_width() * sizeof(float),
|
|
input.data(), packed_weights.data(), zero.data(), output.data(),
|
|
padding_top(),
|
|
&chw_params);
|
|
|
|
// Verify results.
|
|
for (size_t y = 0; y < output_height(); y++) {
|
|
for (size_t x = 0; x < output_width(); x++) {
|
|
ASSERT_NEAR(
|
|
output_ref[y * output_width() + x],
|
|
output[y * output_width() + x],
|
|
std::abs(output_ref[y * output_width() + x]) * 1.0e-5)
|
|
<< "x = " << x << ", y = " << y;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
private:
|
|
uint32_t padding_left_{0};
|
|
uint32_t padding_right_{0};
|
|
uint32_t padding_top_{0};
|
|
uint32_t padding_bottom_{0};
|
|
uint32_t input_height_{1};
|
|
uint32_t input_width_{1};
|
|
uint32_t subsampling_{1};
|
|
uint32_t kernel_height_{1};
|
|
uint32_t kernel_width_{1};
|
|
uint8_t qmin_{0};
|
|
uint8_t qmax_{255};
|
|
size_t iterations_{1};
|
|
};
|