blob: 18460dd8a23bad1b4e94b484815a94caa2881627 [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.
#include <algorithm>
#include <cmath>
#include <functional>
#include <random>
#include <vector>
#include <xnnpack.h>
#include <benchmark/benchmark.h>
#include "bench/utils.h"
static void add_nc_q8(benchmark::State& state) {
const size_t batch_size = static_cast<size_t>(state.range(0));
const size_t channels = static_cast<size_t>(state.range(1));
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(batch_size * channels);
std::vector<uint8_t> b(batch_size * channels);
std::vector<uint8_t> y(batch_size * channels);
std::generate(a.begin(), a.end(), std::ref(u8rng));
std::generate(b.begin(), b.end(), std::ref(u8rng));
xnn_status status = xnn_initialize();
if (status != xnn_status_success) {
state.SkipWithError("failed to initialize XNNPACK");
return;
}
xnn_operator_t add_op = nullptr;
status = xnn_create_add_nc_q8(
channels, channels /* a_stride */, channels /* b_stride */, channels /* sum_stride */,
127 /* a:zero point */, 1.0f /* a:scale */,
127 /* b:zero point */, 1.0f /* b:scale */,
127 /* y:zero point */, 1.0f /* y:scale */,
1 /* y:min */, 254 /* y:max */,
0 /* flags */, &add_op);
if (status != xnn_status_success || add_op == nullptr) {
state.SkipWithError("failed to create Q8 Add operator");
return;
}
status = xnn_setup_add_nc_q8(
add_op,
batch_size,
a.data(), b.data(), y.data(),
nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to setup Q8 Add operator");
return;
}
for (auto _ : state) {
status = xnn_run_operator(add_op, nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to run Q8 Add operator");
return;
}
}
status = xnn_delete_operator(add_op);
if (status != xnn_status_success) {
state.SkipWithError("failed to delete Q8 Add operator");
return;
}
state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency();
const size_t elements_per_iteration = batch_size * channels;
state.counters["elements"] =
benchmark::Counter(uint64_t(state.iterations()) * elements_per_iteration, benchmark::Counter::kIsRate);
const size_t bytes_per_iteration = 3 * elements_per_iteration * sizeof(uint8_t);
state.counters["bytes"] =
benchmark::Counter(uint64_t(state.iterations()) * bytes_per_iteration, benchmark::Counter::kIsRate);
}
static void add_nc_q8_inplace(benchmark::State& state) {
const size_t batch_size = static_cast<size_t>(state.range(0));
const size_t channels = static_cast<size_t>(state.range(1));
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(batch_size * channels);
std::vector<uint8_t> y(batch_size * channels);
std::generate(a.begin(), a.end(), std::ref(u8rng));
xnn_status status = xnn_initialize();
if (status != xnn_status_success) {
state.SkipWithError("failed to initialize XNNPACK");
return;
}
xnn_operator_t add_op = nullptr;
status = xnn_create_add_nc_q8(
channels, channels /* a_stride */, channels /* b_stride */, channels /* sum_stride */,
127 /* a:zero point */, 1.0f /* a:scale */,
127 /* b:zero point */, 1.0f /* b:scale */,
127 /* y:zero point */, 1.0f /* y:scale */,
1 /* y:min */, 254 /* y:max */,
0 /* flags */, &add_op);
if (status != xnn_status_success || add_op == nullptr) {
state.SkipWithError("failed to create Q8 Add operator");
return;
}
status = xnn_setup_add_nc_q8(
add_op,
batch_size,
a.data(), y.data(), y.data(),
nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to setup Q8 Add operator");
return;
}
for (auto _ : state) {
status = xnn_run_operator(add_op, nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to run Q8 Add operator");
return;
}
}
status = xnn_delete_operator(add_op);
if (status != xnn_status_success) {
state.SkipWithError("failed to delete Q8 Add operator");
return;
}
state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency();
const size_t elements_per_iteration = batch_size * channels;
state.counters["elements"] =
benchmark::Counter(uint64_t(state.iterations()) * elements_per_iteration, benchmark::Counter::kIsRate);
const size_t bytes_per_iteration = 3 * elements_per_iteration * sizeof(uint8_t);
state.counters["bytes"] =
benchmark::Counter(uint64_t(state.iterations()) * bytes_per_iteration, benchmark::Counter::kIsRate);
}
static void CharacteristicArguments(benchmark::internal::Benchmark* b)
{
b->ArgNames({"N", "C"});
int32_t c = 16;
for (int32_t n = 224; n >= 7; n /= 2) {
b->Args({n * n, c});
c *= 2;
}
}
BENCHMARK(add_nc_q8)->Apply(CharacteristicArguments)->UseRealTime();
BENCHMARK(add_nc_q8_inplace)->Apply(CharacteristicArguments)->UseRealTime();
#ifndef XNNPACK_BENCHMARK_NO_MAIN
BENCHMARK_MAIN();
#endif