602 lines
23 KiB
C++
602 lines
23 KiB
C++
// 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 <limits>
|
|
#include <random>
|
|
#include <vector>
|
|
|
|
#include <xnnpack.h>
|
|
|
|
|
|
class ArgmaxPoolingOperatorTester {
|
|
public:
|
|
inline ArgmaxPoolingOperatorTester& padding_tf_same(bool padding_same) {
|
|
if (padding_same) {
|
|
assert(padding_top() == 0);
|
|
assert(padding_left() == 0);
|
|
assert(padding_bottom() == 0);
|
|
assert(padding_right() == 0);
|
|
}
|
|
this->padding_tf_same_ = padding_same;
|
|
return *this;
|
|
}
|
|
|
|
inline bool padding_tf_same() const {
|
|
return this->padding_tf_same_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding(uint32_t padding) {
|
|
assert(!padding_tf_same());
|
|
this->padding_top_ = padding;
|
|
this->padding_right_ = padding;
|
|
this->padding_bottom_ = padding;
|
|
this->padding_left_ = padding;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding(uint32_t padding_height, uint32_t padding_width) {
|
|
assert(!padding_tf_same());
|
|
this->padding_top_ = padding_height;
|
|
this->padding_right_ = padding_width;
|
|
this->padding_bottom_ = padding_height;
|
|
this->padding_left_ = padding_width;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_height(uint32_t padding_height) {
|
|
assert(!padding_tf_same());
|
|
this->padding_top_ = padding_height;
|
|
this->padding_bottom_ = padding_height;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_width(uint32_t padding_width) {
|
|
assert(!padding_tf_same());
|
|
this->padding_right_ = padding_width;
|
|
this->padding_left_ = padding_width;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_top(uint32_t padding_top) {
|
|
assert(!padding_tf_same());
|
|
this->padding_top_ = padding_top;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_top() const {
|
|
if (padding_tf_same()) {
|
|
const uint32_t total_padding_height = output_height() * pooling_height() - input_height();
|
|
return total_padding_height / 2;
|
|
} else {
|
|
return this->padding_top_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_left(uint32_t padding_left) {
|
|
assert(!padding_tf_same());
|
|
this->padding_left_ = padding_left;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_left() const {
|
|
if (padding_tf_same()) {
|
|
const uint32_t total_padding_width = output_width() * pooling_width() - input_width();
|
|
return total_padding_width / 2;
|
|
} else {
|
|
return this->padding_left_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_bottom(uint32_t padding_bottom) {
|
|
assert(!padding_tf_same());
|
|
this->padding_bottom_ = padding_bottom;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_bottom() const {
|
|
if (padding_tf_same()) {
|
|
const uint32_t total_padding_height = output_height() * pooling_height() - input_height();
|
|
return total_padding_height - total_padding_height / 2;
|
|
} else {
|
|
return this->padding_bottom_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& padding_right(uint32_t padding_right) {
|
|
assert(!padding_tf_same());
|
|
this->padding_right_ = padding_right;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t padding_right() const {
|
|
if (padding_tf_same()) {
|
|
const uint32_t total_padding_width = output_width() * pooling_width() - input_width();
|
|
return total_padding_width - total_padding_width / 2;
|
|
} else {
|
|
return this->padding_right_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& input_size(size_t input_height, size_t input_width) {
|
|
assert(input_height >= 1);
|
|
assert(input_width >= 1);
|
|
this->input_height_ = input_height;
|
|
this->input_width_ = input_width;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& input_height(size_t input_height) {
|
|
assert(input_height >= 1);
|
|
this->input_height_ = input_height;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t input_height() const {
|
|
return this->input_height_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& input_width(size_t input_width) {
|
|
assert(input_width >= 1);
|
|
this->input_width_ = input_width;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t input_width() const {
|
|
return this->input_width_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& channels(size_t channels) {
|
|
assert(channels != 0);
|
|
this->channels_ = channels;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t channels() const {
|
|
return this->channels_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& batch_size(size_t batch_size) {
|
|
assert(batch_size != 0);
|
|
this->batch_size_ = batch_size;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t batch_size() const {
|
|
return this->batch_size_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& pooling_size(uint32_t pooling_size) {
|
|
assert(pooling_size >= 1);
|
|
this->pooling_height_ = pooling_size;
|
|
this->pooling_width_ = pooling_size;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& pooling_size(uint32_t pooling_height, uint32_t pooling_width) {
|
|
assert(pooling_height >= 1);
|
|
assert(pooling_width >= 1);
|
|
this->pooling_height_ = pooling_height;
|
|
this->pooling_width_ = pooling_width;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& pooling_height(uint32_t pooling_height) {
|
|
assert(pooling_height >= 1);
|
|
this->pooling_height_ = pooling_height;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t pooling_height() const {
|
|
return this->pooling_height_;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& pooling_width(uint32_t pooling_width) {
|
|
assert(pooling_width >= 1);
|
|
this->pooling_width_ = pooling_width;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t pooling_width() const {
|
|
return this->pooling_width_;
|
|
}
|
|
|
|
inline size_t output_height() const {
|
|
if (padding_tf_same()) {
|
|
return (input_height() + pooling_height() - 1) / pooling_height();
|
|
} else {
|
|
const size_t padded_input_height = padding_top() + input_height() + padding_bottom();
|
|
return padded_input_height / pooling_height();
|
|
}
|
|
}
|
|
|
|
inline size_t output_width() const {
|
|
if (padding_tf_same()) {
|
|
return (input_width() + pooling_width() - 1) / pooling_width();
|
|
} else {
|
|
const size_t padded_input_width = padding_left() + input_width() + padding_right();
|
|
return padded_input_width / pooling_width();
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& input_pixel_stride(size_t input_pixel_stride) {
|
|
assert(input_pixel_stride != 0);
|
|
this->input_pixel_stride_ = input_pixel_stride;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t input_pixel_stride() const {
|
|
if (this->input_pixel_stride_ == 0) {
|
|
return channels();
|
|
} else {
|
|
assert(this->input_pixel_stride_ >= channels());
|
|
return this->input_pixel_stride_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& output_pixel_stride(size_t output_pixel_stride) {
|
|
assert(output_pixel_stride != 0);
|
|
this->output_pixel_stride_ = output_pixel_stride;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t output_pixel_stride() const {
|
|
if (this->output_pixel_stride_ == 0) {
|
|
return channels();
|
|
} else {
|
|
assert(this->output_pixel_stride_ >= channels());
|
|
return this->output_pixel_stride_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& next_input_size(uint32_t next_input_height, uint32_t next_input_width) {
|
|
assert(next_input_height >= 1);
|
|
assert(next_input_width >= 1);
|
|
this->next_input_height_ = next_input_height;
|
|
this->next_input_width_ = next_input_width;
|
|
return *this;
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& next_input_height(uint32_t next_input_height) {
|
|
assert(next_input_height >= 1);
|
|
this->next_input_height_ = next_input_height;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t next_input_height() const {
|
|
if (this->next_input_height_ == 0) {
|
|
return input_height();
|
|
} else {
|
|
return this->next_input_height_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& next_input_width(uint32_t next_input_width) {
|
|
assert(next_input_width >= 1);
|
|
this->next_input_width_ = next_input_width;
|
|
return *this;
|
|
}
|
|
|
|
inline uint32_t next_input_width() const {
|
|
if (this->next_input_width_ == 0) {
|
|
return input_width();
|
|
} else {
|
|
return this->next_input_width_;
|
|
}
|
|
}
|
|
|
|
inline size_t next_output_height() const {
|
|
const size_t padded_next_input_height = padding_top() + next_input_height() + padding_bottom();
|
|
return padded_next_input_height / pooling_height();
|
|
}
|
|
|
|
inline size_t next_output_width() const {
|
|
const size_t padded_next_input_width = padding_left() + next_input_width() + padding_right();
|
|
return padded_next_input_width / pooling_width();
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& next_batch_size(size_t next_batch_size) {
|
|
assert(next_batch_size >= 1);
|
|
this->next_batch_size_ = next_batch_size;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t next_batch_size() const {
|
|
if (this->next_batch_size_ == 0) {
|
|
return batch_size();
|
|
} else {
|
|
return this->next_batch_size_;
|
|
}
|
|
}
|
|
|
|
inline ArgmaxPoolingOperatorTester& iterations(size_t iterations) {
|
|
this->iterations_ = iterations;
|
|
return *this;
|
|
}
|
|
|
|
inline size_t iterations() const {
|
|
return this->iterations_;
|
|
}
|
|
|
|
void TestF32() 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> input((batch_size() * input_height() * input_width() - 1) * input_pixel_stride() + channels() + XNN_EXTRA_BYTES / sizeof(float));
|
|
std::vector<float> output((batch_size() * output_height() * output_width() - 1) * output_pixel_stride() + channels());
|
|
std::vector<float> output_ref(batch_size() * output_height() * output_width() * channels());
|
|
std::vector<uint32_t> index(batch_size() * output_height() * output_width() * channels());
|
|
std::vector<uint32_t> index_ref(batch_size() * output_height() * output_width() * channels());
|
|
for (size_t iteration = 0; iteration < iterations(); iteration++) {
|
|
std::generate(input.begin(), input.end(), std::ref(f32rng));
|
|
std::fill(output.begin(), output.end(), nanf(""));
|
|
|
|
// Compute reference results, without clamping.
|
|
for (size_t i = 0; i < batch_size(); i++) {
|
|
for (size_t oy = 0; oy < output_height(); oy++) {
|
|
for (size_t ox = 0; ox < output_width(); ox++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
const size_t iy_top_left = std::max<size_t>(oy * pooling_height(), padding_top()) - padding_top();
|
|
const size_t ix_top_left = std::max<size_t>(ox * pooling_width(), padding_left()) - padding_left();
|
|
float max_value =
|
|
input[((i * input_height() + iy_top_left) * input_width() + ix_top_left) * input_pixel_stride() + c];
|
|
uint32_t max_index = 0;
|
|
for (size_t py = 0; py < pooling_height(); py++) {
|
|
const size_t iy = oy * pooling_height() + py - padding_top();
|
|
for (size_t px = 0; px < pooling_width(); px++) {
|
|
const size_t ix = ox * pooling_width() + px - padding_left();
|
|
if (ix < input_width() && iy < input_height()) {
|
|
const float value = input[((i * input_height() + iy) * input_width() + ix) * input_pixel_stride() + c];
|
|
if (value > max_value) {
|
|
max_value = value;
|
|
max_index = uint32_t(px * pooling_height() + py);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_value;
|
|
index_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_index;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Create, setup, run, and destroy Argmax Pooling operator.
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
|
|
xnn_operator_t argmax_pooling_op = nullptr;
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_create_argmax_pooling2d_nhwc_f32(
|
|
padding_tf_same() ? 0 : padding_top(), padding_tf_same() ? 0 : padding_right(),
|
|
padding_tf_same() ? 0 : padding_bottom(), padding_tf_same() ? 0 : padding_left(),
|
|
pooling_height(), pooling_width(),
|
|
channels(), input_pixel_stride(), output_pixel_stride(),
|
|
padding_tf_same() ? XNN_FLAG_TENSORFLOW_SAME_PADDING : 0,
|
|
&argmax_pooling_op));
|
|
ASSERT_NE(nullptr, argmax_pooling_op);
|
|
|
|
// Smart pointer to automatically delete argmax_pooling_op.
|
|
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_argmax_pooling_op(argmax_pooling_op, xnn_delete_operator);
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_argmax_pooling2d_nhwc_f32(
|
|
argmax_pooling_op,
|
|
batch_size(), input_height(), input_width(),
|
|
input.data(), output.data(), index.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(argmax_pooling_op, nullptr /* thread pool */));
|
|
|
|
// Verify results.
|
|
for (size_t i = 0; i < batch_size(); i++) {
|
|
for (size_t y = 0; y < output_height(); y++) {
|
|
for (size_t x = 0; x < output_width(); x++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
ASSERT_EQ(output_ref[((i * output_height() + y) * output_width() + x) * channels() + c],
|
|
output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c]) <<
|
|
"in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
ASSERT_EQ(index_ref[((i * output_height() + y) * output_width() + x) * channels() + c],
|
|
index[((i * output_height() + y) * output_width() + x) * channels() + c]) <<
|
|
"in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void TestSetupF32() 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> input(XNN_EXTRA_BYTES / sizeof(float) + std::max(
|
|
(batch_size() * input_height() * input_width() - 1) * input_pixel_stride() + channels(),
|
|
(next_batch_size() * next_input_height() * next_input_width() - 1) * input_pixel_stride() + channels()));
|
|
std::vector<float> output(std::max(
|
|
(batch_size() * output_height() * output_width() - 1) * output_pixel_stride() + channels(),
|
|
(next_batch_size() * next_output_height() * next_output_width() - 1) * output_pixel_stride() + channels()));
|
|
std::vector<uint32_t> index(std::max(
|
|
batch_size() * output_height() * output_width() * channels(),
|
|
next_batch_size() * next_output_height() * next_output_width() * channels()));
|
|
std::vector<float> output_ref(batch_size() * output_height() * output_width() * channels());
|
|
std::vector<float> next_output_ref(next_batch_size() * next_output_height() * next_output_width() * channels());
|
|
std::vector<uint32_t> index_ref(batch_size() * output_height() * output_width() * channels());
|
|
std::vector<uint32_t> next_index_ref(next_batch_size() * next_output_height() * next_output_width() * channels());
|
|
for (size_t iteration = 0; iteration < iterations(); iteration++) {
|
|
std::generate(input.begin(), input.end(), std::ref(f32rng));
|
|
std::fill(output.begin(), output.end(), nanf(""));
|
|
|
|
// Compute reference results, without clamping.
|
|
for (size_t i = 0; i < batch_size(); i++) {
|
|
for (size_t oy = 0; oy < output_height(); oy++) {
|
|
for (size_t ox = 0; ox < output_width(); ox++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
const size_t iy_top_left = std::max<size_t>(oy * pooling_height(), padding_top()) - padding_top();
|
|
const size_t ix_top_left = std::max<size_t>(ox * pooling_width(), padding_left()) - padding_left();
|
|
float max_value =
|
|
input[((i * input_height() + iy_top_left) * input_width() + ix_top_left) * input_pixel_stride() + c];
|
|
uint32_t max_index = 0;
|
|
for (size_t py = 0; py < pooling_height(); py++) {
|
|
const size_t iy = oy * pooling_height() + py - padding_top();
|
|
for (size_t px = 0; px < pooling_width(); px++) {
|
|
const size_t ix = ox * pooling_width() + px - padding_left();
|
|
if (ix < input_width() && iy < input_height()) {
|
|
const float value = input[((i * input_height() + iy) * input_width() + ix) * input_pixel_stride() + c];
|
|
if (value > max_value) {
|
|
max_value = value;
|
|
max_index = uint32_t(px * pooling_height() + py);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
output_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_value;
|
|
index_ref[((i * output_height() + oy) * output_width() + ox) * channels() + c] = max_index;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Create, setup, and run Argmax Pooling operator once.
|
|
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
|
|
xnn_operator_t argmax_pooling_op = nullptr;
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_create_argmax_pooling2d_nhwc_f32(
|
|
padding_top(), padding_right(), padding_bottom(), padding_left(),
|
|
pooling_height(), pooling_width(),
|
|
channels(), input_pixel_stride(), output_pixel_stride(),
|
|
0, &argmax_pooling_op));
|
|
ASSERT_NE(nullptr, argmax_pooling_op);
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_argmax_pooling2d_nhwc_f32(
|
|
argmax_pooling_op,
|
|
batch_size(), input_height(), input_width(),
|
|
input.data(), output.data(), index.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(argmax_pooling_op, nullptr /* thread pool */));
|
|
|
|
// Verify results of the first run.
|
|
for (size_t i = 0; i < batch_size(); i++) {
|
|
for (size_t y = 0; y < output_height(); y++) {
|
|
for (size_t x = 0; x < output_width(); x++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
ASSERT_EQ(
|
|
output_ref[((i * output_height() + y) * output_width() + x) * channels() + c],
|
|
output[((i * output_height() + y) * output_width() + x) * output_pixel_stride() + c])
|
|
<< "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
ASSERT_EQ(
|
|
index_ref[((i * output_height() + y) * output_width() + x) * channels() + c],
|
|
index[((i * output_height() + y) * output_width() + x) * channels() + c])
|
|
<< "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Re-generate data for the second run.
|
|
std::generate(input.begin(), input.end(), std::ref(f32rng));
|
|
std::fill(output.begin(), output.end(), 0xA5);
|
|
|
|
// Compute reference results for the second run, including clamping.
|
|
for (size_t i = 0; i < next_batch_size(); i++) {
|
|
for (size_t oy = 0; oy < next_output_height(); oy++) {
|
|
for (size_t ox = 0; ox < next_output_width(); ox++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
const size_t iy_top_left = std::max<size_t>(oy * pooling_height(), padding_top()) - padding_top();
|
|
const size_t ix_top_left = std::max<size_t>(ox * pooling_width(), padding_left()) - padding_left();
|
|
float max_value =
|
|
input[((i * next_input_height() + iy_top_left) * next_input_width() + ix_top_left) * input_pixel_stride() + c];
|
|
uint32_t max_index = 0;
|
|
for (size_t py = 0; py < pooling_height(); py++) {
|
|
const size_t iy = oy * pooling_height() + py - padding_top();
|
|
for (size_t px = 0; px < pooling_width(); px++) {
|
|
const size_t ix = ox * pooling_width() + px - padding_left();
|
|
if (ix < next_input_width() && iy < next_input_height()) {
|
|
const float value = input[((i * next_input_height() + iy) * next_input_width() + ix) * input_pixel_stride() + c];
|
|
if (value > max_value) {
|
|
max_value = value;
|
|
max_index = uint32_t(px * pooling_height() + py);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
next_output_ref[((i * next_output_height() + oy) * next_output_width() + ox) * channels() + c] = max_value;
|
|
next_index_ref[((i * next_output_height() + oy) * next_output_width() + ox) * channels() + c] = max_index;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Setup and run Argmax Pooling operator the second time, and destroy the operator.
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_setup_argmax_pooling2d_nhwc_f32(
|
|
argmax_pooling_op,
|
|
next_batch_size(), next_input_height(), next_input_width(),
|
|
input.data(), output.data(), index.data(),
|
|
nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_run_operator(argmax_pooling_op, nullptr /* thread pool */));
|
|
|
|
ASSERT_EQ(xnn_status_success,
|
|
xnn_delete_operator(argmax_pooling_op));
|
|
argmax_pooling_op = nullptr;
|
|
|
|
// Verify results of the second run.
|
|
for (size_t i = 0; i < next_batch_size(); i++) {
|
|
for (size_t y = 0; y < next_output_height(); y++) {
|
|
for (size_t x = 0; x < next_output_width(); x++) {
|
|
for (size_t c = 0; c < channels(); c++) {
|
|
ASSERT_EQ(
|
|
next_output_ref[((i * next_output_height() + y) * next_output_width() + x) * channels() + c],
|
|
output[((i * next_output_height() + y) * next_output_width() + x) * output_pixel_stride() + c])
|
|
<< "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
ASSERT_EQ(
|
|
next_index_ref[((i * next_output_height() + y) * next_output_width() + x) * channels() + c],
|
|
index[((i * next_output_height() + y) * next_output_width() + x) * output_pixel_stride() + c])
|
|
<< "in batch index " << i << ", pixel (" << y << ", " << x << "), channel " << c;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
private:
|
|
uint32_t padding_top_{0};
|
|
uint32_t padding_right_{0};
|
|
uint32_t padding_bottom_{0};
|
|
uint32_t padding_left_{0};
|
|
bool padding_tf_same_{false};
|
|
size_t input_height_{1};
|
|
size_t input_width_{1};
|
|
size_t channels_{1};
|
|
size_t batch_size_{1};
|
|
size_t input_pixel_stride_{0};
|
|
size_t output_pixel_stride_{0};
|
|
uint32_t pooling_height_{1};
|
|
uint32_t pooling_width_{1};
|
|
size_t next_input_height_{0};
|
|
size_t next_input_width_{0};
|
|
size_t next_batch_size_{0};
|
|
uint8_t qmin_{0};
|
|
uint8_t qmax_{255};
|
|
size_t iterations_{1};
|
|
};
|