blob: a757890614b51d9f593209345d5524f62d77f3cd [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 <cfloat>
#include <cmath>
#include <functional>
#include <random>
#include <vector>
#include <xnnpack.h>
#include <benchmark/benchmark.h>
#include "bench/utils.h"
static void average_pooling_q8(benchmark::State& state, const char* net) {
const size_t batch_size = state.range(0);
const size_t input_height = state.range(1);
const size_t input_width = state.range(2);
const size_t pooling_size = state.range(3);
const size_t padding_size = state.range(4);
const size_t stride = state.range(5);
const size_t channels = state.range(6);
std::random_device random_device;
auto rng = std::mt19937(random_device());
auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);
const size_t output_height = (2 * padding_size + input_height - pooling_size) / stride + 1;
const size_t output_width = (2 * padding_size + input_width - pooling_size) / stride + 1;
std::vector<uint8_t> input(batch_size * input_height * input_width * channels + XNN_EXTRA_BYTES / sizeof(uint8_t));
std::generate(input.begin(), input.end(), std::ref(u8rng));
std::vector<uint8_t> output(batch_size * output_height * output_width * channels);
std::fill(output.begin(), output.end(), 0xA5);
xnn_status status = xnn_initialize(nullptr /* allocator */);
if (status != xnn_status_success) {
state.SkipWithError("failed to initialize XNNPACK");
return;
}
xnn_operator_t pooling_op = nullptr;
status = xnn_create_average_pooling2d_nhwc_q8(
padding_size, padding_size, padding_size, padding_size,
pooling_size, pooling_size,
stride, stride,
channels, channels /* input pixel stride */, channels /* output pixel stride */,
127 /* input zero point */, 0.75f /* input scale */,
127 /* output zero point */, 1.25f /* output scale */,
0, 255,
0 /* flags */, &pooling_op);
if (status != xnn_status_success) {
state.SkipWithError("failed to create Average Pooling operator");
return;
}
status = xnn_setup_average_pooling2d_nhwc_q8(
pooling_op,
batch_size, input_height, input_width,
input.data(), output.data(),
nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to setup Average Pooling operator");
return;
}
for (auto _ : state) {
status = xnn_run_operator(pooling_op, nullptr /* thread pool */);
if (status != xnn_status_success) {
state.SkipWithError("failed to run Average Pooling operator");
return;
}
}
status = xnn_delete_operator(pooling_op);
if (status != xnn_status_success) {
state.SkipWithError("failed to delete Average Pooling operator");
return;
}
pooling_op = nullptr;
state.counters["Freq"] = benchmark::utils::GetCurrentCpuFrequency();
state.counters["bytes"] = benchmark::Counter(
uint64_t(state.iterations()) *
batch_size * (input_height * input_width + output_height * output_width) * channels * sizeof(uint8_t),
benchmark::Counter::kIsRate);
}
// ShuffleNet v1 with 1 group.
static void ShuffleNetV1G1(benchmark::internal::Benchmark* b) {
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
/* N H W K P S C */
b->Args({1, 56, 56, 3, 1, 2, 24});
b->Args({1, 28, 28, 3, 1, 2, 144});
b->Args({1, 14, 14, 3, 1, 2, 288});
b->Args({1, 7, 7, 3, 1, 2, 576});
}
// ShuffleNet v1 with 2 groups.
static void ShuffleNetV1G2(benchmark::internal::Benchmark* b) {
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
/* N H W K P S C */
b->Args({1, 56, 56, 3, 1, 2, 24});
b->Args({1, 28, 28, 3, 1, 2, 200});
b->Args({1, 14, 14, 3, 1, 2, 400});
b->Args({1, 7, 7, 3, 1, 2, 800});
}
// ShuffleNet v1 with 3 groups.
static void ShuffleNetV1G3(benchmark::internal::Benchmark* b) {
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
/* N H W K P S C */
b->Args({1, 56, 56, 3, 1, 2, 24});
b->Args({1, 28, 28, 3, 1, 2, 240});
b->Args({1, 14, 14, 3, 1, 2, 480});
b->Args({1, 7, 7, 3, 1, 2, 960});
}
// ShuffleNet v1 with 4 groups.
static void ShuffleNetV1G4(benchmark::internal::Benchmark* b) {
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
/* N H W K P S C */
b->Args({1, 56, 56, 3, 1, 2, 24});
b->Args({1, 28, 28, 3, 1, 2, 272});
b->Args({1, 14, 14, 3, 1, 2, 576});
b->Args({1, 7, 7, 3, 1, 2, 1088});
}
// ShuffleNet v1 with 8 groups.
static void ShuffleNetV1G8(benchmark::internal::Benchmark* b) {
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
/* N H W K P S C */
b->Args({1, 56, 56, 3, 1, 2, 24});
b->Args({1, 28, 28, 3, 1, 2, 384});
b->Args({1, 14, 14, 3, 1, 2, 768});
b->Args({1, 7, 7, 3, 1, 2, 1536});
}
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g1, "ShuffleNet v1 (1 group)")->Apply(ShuffleNetV1G1)->UseRealTime();
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g2, "ShuffleNet v1 (2 groups)")->Apply(ShuffleNetV1G2)->UseRealTime();
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g3, "ShuffleNet v1 (3 groups)")->Apply(ShuffleNetV1G3)->UseRealTime();
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g4, "ShuffleNet v1 (4 groups)")->Apply(ShuffleNetV1G4)->UseRealTime();
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g8, "ShuffleNet v1 (8 groups)")->Apply(ShuffleNetV1G8)->UseRealTime();
#ifndef XNNPACK_BENCHMARK_NO_MAIN
BENCHMARK_MAIN();
#endif