239 lines
8.3 KiB
C++
239 lines
8.3 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.
|
|
|
|
#include <algorithm>
|
|
#include <cfloat>
|
|
#include <cmath>
|
|
#include <functional>
|
|
#include <limits>
|
|
#include <random>
|
|
#include <vector>
|
|
|
|
#include <xnnpack.h>
|
|
|
|
#include <benchmark/benchmark.h>
|
|
#include "bench/utils.h"
|
|
|
|
|
|
void max_pooling_u8(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<uint32_t>(0, std::numeric_limits<uint8_t>::max()), std::ref(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);
|
|
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_max_pooling2d_nhwc_u8(
|
|
padding_size, padding_size, padding_size, padding_size,
|
|
pooling_size, pooling_size,
|
|
stride, stride,
|
|
1 /* dilation height */, 1 /* dilation width */,
|
|
channels, channels /* input pixel stride */, channels /* output pixel stride */,
|
|
0, 255,
|
|
0 /* flags */, &pooling_op);
|
|
if (status != xnn_status_success) {
|
|
state.SkipWithError("failed to create Max Pooling operator");
|
|
return;
|
|
}
|
|
|
|
status = xnn_setup_max_pooling2d_nhwc_u8(
|
|
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 Max 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 Max Pooling operator");
|
|
return;
|
|
}
|
|
}
|
|
|
|
status = xnn_delete_operator(pooling_op);
|
|
if (status != xnn_status_success) {
|
|
state.SkipWithError("failed to delete Max Pooling operator");
|
|
return;
|
|
}
|
|
pooling_op = nullptr;
|
|
|
|
const uint64_t cpu_frequency = benchmark::utils::GetCurrentCpuFrequency();
|
|
if (cpu_frequency != 0) {
|
|
state.counters["cpufreq"] = cpu_frequency;
|
|
}
|
|
|
|
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);
|
|
}
|
|
|
|
void max_pooling_f32(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 f32rng = std::bind(std::uniform_real_distribution<float>(0.0f, 1.0f), std::ref(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<float> input(batch_size * input_height * input_width * channels);
|
|
std::generate(input.begin(), input.end(), std::ref(f32rng));
|
|
std::vector<float> output(batch_size * output_height * output_width * channels);
|
|
std::fill(output.begin(), output.end(), nanf(""));
|
|
|
|
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_max_pooling2d_nhwc_f32(
|
|
padding_size, padding_size, padding_size, padding_size,
|
|
pooling_size, pooling_size,
|
|
stride, stride,
|
|
1 /* dilation height */, 1 /* dilation width */,
|
|
channels, channels /* input pixel stride */, channels /* output pixel stride */,
|
|
-std::numeric_limits<float>::infinity(), +std::numeric_limits<float>::infinity(),
|
|
0 /* flags */, &pooling_op);
|
|
if (status != xnn_status_success) {
|
|
state.SkipWithError("failed to create Max Pooling operator");
|
|
return;
|
|
}
|
|
|
|
status = xnn_setup_max_pooling2d_nhwc_f32(
|
|
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 Max 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 Max Pooling operator");
|
|
return;
|
|
}
|
|
}
|
|
|
|
status = xnn_delete_operator(pooling_op);
|
|
if (status != xnn_status_success) {
|
|
state.SkipWithError("failed to delete Max Pooling operator");
|
|
return;
|
|
}
|
|
pooling_op = nullptr;
|
|
|
|
const uint64_t cpu_frequency = benchmark::utils::GetCurrentCpuFrequency();
|
|
if (cpu_frequency != 0) {
|
|
state.counters["cpufreq"] = cpu_frequency;
|
|
}
|
|
|
|
state.counters["bytes"] = benchmark::Counter(
|
|
uint64_t(state.iterations()) *
|
|
batch_size * (input_height * input_width + output_height * output_width) * channels * sizeof(float),
|
|
benchmark::Counter::kIsRate);
|
|
}
|
|
|
|
// ShuffleNet v1/v2.
|
|
static void ShuffleNet(benchmark::internal::Benchmark* b) {
|
|
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
|
|
|
|
/* N H W K P S C */
|
|
b->Args({1, 112, 112, 3, 1, 2, 24});
|
|
}
|
|
|
|
// SqueezeNet 1.0
|
|
static void SqueezeNetV10(benchmark::internal::Benchmark* b) {
|
|
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
|
|
|
|
/*********** MaxPool 1 ************/
|
|
/* N H W K P S C */
|
|
b->Args({1, 111, 111, 3, 0, 2, 96});
|
|
/*********** MaxPool 4 ************/
|
|
/* N H W K P S C */
|
|
b->Args({1, 27, 27, 3, 0, 2, 256});
|
|
/*********** MaxPool 8 ************/
|
|
/* N H W K P S C */
|
|
b->Args({1, 13, 13, 3, 0, 2, 512});
|
|
}
|
|
|
|
// SqueezeNet 1.1
|
|
static void SqueezeNetV11(benchmark::internal::Benchmark* b) {
|
|
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
|
|
|
|
/*********** MaxPool 1 ***********/
|
|
/* N H W K P S C */
|
|
b->Args({1, 111, 111, 3, 0, 2, 64});
|
|
/*********** MaxPool 3 ************/
|
|
/* N H W K P S C */
|
|
b->Args({1, 55, 55, 3, 0, 2, 128});
|
|
/*********** MaxPool 5 ************/
|
|
/* N H W K P S C */
|
|
b->Args({1, 13, 13, 3, 0, 2, 256});
|
|
}
|
|
|
|
static void VGG(benchmark::internal::Benchmark* b) {
|
|
b->ArgNames({"N", "H", "W", "K", "P", "S", "C"});
|
|
|
|
/* N H W K P S C */
|
|
b->Args({1, 224, 224, 2, 1, 2, 64});
|
|
b->Args({1, 112, 112, 2, 1, 2, 128});
|
|
b->Args({1, 56, 56, 2, 1, 2, 256});
|
|
b->Args({1, 28, 28, 2, 1, 2, 512});
|
|
b->Args({1, 14, 14, 2, 1, 2, 512});
|
|
}
|
|
|
|
BENCHMARK_CAPTURE(max_pooling_f32, shufflenet, "ShuffleNet v1/v2")->Apply(ShuffleNet)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_f32, squeezenet_v10, "SqueezeNet v1.0")->Apply(SqueezeNetV10)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_f32, squeezenet_v11, "SqueezeNet v1.1")->Apply(SqueezeNetV11)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_f32, vgg, "VGG")->Apply(VGG);
|
|
|
|
BENCHMARK_CAPTURE(max_pooling_u8, shufflenet, "ShuffleNet v1/v2")->Apply(ShuffleNet)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_u8, squeezenet_v10, "SqueezeNet v1.0")->Apply(SqueezeNetV10)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_u8, squeezenet_v11, "SqueezeNet v1.1")->Apply(SqueezeNetV11)->UseRealTime();
|
|
BENCHMARK_CAPTURE(max_pooling_u8, vgg, "VGG")->Apply(VGG);
|
|
|
|
#ifndef XNNPACK_BENCHMARK_NO_MAIN
|
|
BENCHMARK_MAIN();
|
|
#endif
|