blob: 531b6354191c357b2682bcd152b6596b4b261edb [file] [log] [blame]
// 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 <limits>
#include <random>
#include <vector>
#include <xnnpack.h>
class ChannelShuffleOperatorTester {
public:
inline ChannelShuffleOperatorTester& groups(size_t groups) {
assert(groups != 0);
this->groups_ = groups;
return *this;
}
inline size_t groups() const {
return this->groups_;
}
inline ChannelShuffleOperatorTester& group_channels(size_t group_channels) {
assert(group_channels != 0);
this->group_channels_ = group_channels;
return *this;
}
inline size_t group_channels() const {
return this->group_channels_;
}
inline size_t channels() const {
return groups() * group_channels();
}
inline ChannelShuffleOperatorTester& input_stride(size_t input_stride) {
assert(input_stride != 0);
this->input_stride_ = input_stride;
return *this;
}
inline size_t input_stride() const {
if (this->input_stride_ == 0) {
return channels();
} else {
assert(this->input_stride_ >= channels());
return this->input_stride_;
}
}
inline ChannelShuffleOperatorTester& output_stride(size_t output_stride) {
assert(output_stride != 0);
this->output_stride_ = output_stride;
return *this;
}
inline size_t output_stride() const {
if (this->output_stride_ == 0) {
return channels();
} else {
assert(this->output_stride_ >= channels());
return this->output_stride_;
}
}
inline ChannelShuffleOperatorTester& 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 ChannelShuffleOperatorTester& iterations(size_t iterations) {
this->iterations_ = iterations;
return *this;
}
inline size_t iterations() const {
return this->iterations_;
}
void TestX8() const {
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto u8rng = std::bind(std::uniform_int_distribution<uint32_t>(0, std::numeric_limits<uint8_t>::max()), rng);
std::vector<uint8_t> input(XNN_EXTRA_BYTES / sizeof(uint8_t) + (batch_size() - 1) * input_stride() + channels());
std::vector<uint8_t> output((batch_size() - 1) * output_stride() + channels());
for (size_t iteration = 0; iteration < iterations(); iteration++) {
std::generate(input.begin(), input.end(), std::ref(u8rng));
std::fill(output.begin(), output.end(), 0xA5);
// Create, setup, run, and destroy Channel Shuffle operator.
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
xnn_operator_t channel_shuffle_op = nullptr;
ASSERT_EQ(xnn_status_success,
xnn_create_channel_shuffle_nc_x8(
groups(), group_channels(),
input_stride(), output_stride(),
0, &channel_shuffle_op));
ASSERT_NE(nullptr, channel_shuffle_op);
// Smart pointer to automatically delete channel_shuffle_op.
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_channel_shuffle_op(channel_shuffle_op, xnn_delete_operator);
ASSERT_EQ(xnn_status_success,
xnn_setup_channel_shuffle_nc_x8(
channel_shuffle_op,
batch_size(),
input.data(), output.data(),
nullptr /* thread pool */));
ASSERT_EQ(xnn_status_success,
xnn_run_operator(channel_shuffle_op, nullptr /* thread pool */));
// Verify results.
for (size_t i = 0; i < batch_size(); i++) {
for (size_t g = 0; g < groups(); g++) {
for (size_t c = 0; c < group_channels(); c++) {
ASSERT_EQ(uint32_t(input[i * input_stride() + g * group_channels() + c]),
uint32_t(output[i * output_stride() + c * groups() + g]))
<< "batch index " << i << ", group " << g << ", channel " << c;
}
}
}
}
}
void TestX32() 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> input(XNN_EXTRA_BYTES / sizeof(float) + (batch_size() - 1) * input_stride() + channels());
std::vector<float> output((batch_size() - 1) * output_stride() + channels());
for (size_t iteration = 0; iteration < iterations(); iteration++) {
std::generate(input.begin(), input.end(), std::ref(f32rng));
std::fill(output.begin(), output.end(), std::nanf(""));
// Create, setup, run, and destroy Channel Shuffle operator.
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
xnn_operator_t channel_shuffle_op = nullptr;
ASSERT_EQ(xnn_status_success,
xnn_create_channel_shuffle_nc_x32(
groups(), group_channels(),
input_stride(), output_stride(),
0, &channel_shuffle_op));
ASSERT_NE(nullptr, channel_shuffle_op);
// Smart pointer to automatically delete channel_shuffle_op.
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_channel_shuffle_op(channel_shuffle_op, xnn_delete_operator);
ASSERT_EQ(xnn_status_success,
xnn_setup_channel_shuffle_nc_x32(
channel_shuffle_op,
batch_size(),
input.data(), output.data(),
nullptr /* thread pool */));
ASSERT_EQ(xnn_status_success,
xnn_run_operator(channel_shuffle_op, nullptr /* thread pool */));
// Verify results.
for (size_t i = 0; i < batch_size(); i++) {
for (size_t g = 0; g < groups(); g++) {
for (size_t c = 0; c < group_channels(); c++) {
ASSERT_EQ(input[i * input_stride() + g * group_channels() + c],
output[i * output_stride() + c * groups() + g])
<< "batch index " << i << ", group " << g << ", channel " << c;
}
}
}
}
}
private:
size_t groups_{1};
size_t group_channels_{1};
size_t batch_size_{1};
size_t input_stride_{0};
size_t output_stride_{0};
size_t iterations_{15};
};