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average-pooling.cc
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average-pooling.cc
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/*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
*
* 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 <chrono>
#include <cmath>
#include <functional>
#include <iostream>
#include <random>
#include <vector>
#include <iostream>
#include <qnnpack.h>
#include <benchmark/benchmark.h>
static void average_pooling_q8(benchmark::State& state, const char* net) {
const size_t batchSize = state.range(0);
const size_t inputHeight = state.range(1);
const size_t inputWidth = state.range(2);
const size_t poolingSize = state.range(3);
const size_t paddingSize = state.range(4);
const size_t stride = state.range(5);
const size_t channels = state.range(6);
std::random_device randomDevice;
auto rng = std::mt19937(randomDevice());
auto u8rng = std::bind(std::uniform_int_distribution<uint8_t>(), rng);
const size_t inputPixelStride = channels;
const size_t outputPixelStride = channels;
const size_t outputHeight = (2 * paddingSize + inputHeight - poolingSize) / stride + 1;
const size_t outputWidth = (2 * paddingSize + inputWidth - poolingSize) / stride + 1;
std::vector<uint8_t> input(batchSize * inputHeight * inputWidth * inputPixelStride);
std::generate(input.begin(), input.end(), std::ref(u8rng));
std::vector<uint8_t> output(batchSize * outputHeight * outputWidth * outputPixelStride);
std::fill(output.begin(), output.end(), 0xA5);
qnnp_status status = qnnp_initialize();
if (status != qnnp_status_success) {
state.SkipWithError("failed to initialize QNNPACK");
}
qnnp_operator_t poolingOperator = nullptr;
status = qnnp_create_average_pooling2d_nhwc_q8(
paddingSize, paddingSize, paddingSize, paddingSize,
poolingSize, poolingSize,
stride, stride,
channels,
127 /* input zero point */, 0.75f /* input scale */,
127 /* output zero point */, 1.25f /* output scale */,
0, 255,
0 /* flags */, &poolingOperator);
if (status != qnnp_status_success) {
state.SkipWithError("failed to create Average Pooling operator");
}
status = qnnp_setup_average_pooling2d_nhwc_q8(
poolingOperator,
batchSize, inputHeight, inputWidth,
input.data(), inputPixelStride,
output.data(), outputPixelStride,
nullptr /* thread pool */);
if (status != qnnp_status_success) {
state.SkipWithError("failed to setup Average Pooling operator");
}
for (auto _ : state) {
status = qnnp_run_operator(poolingOperator, nullptr /* thread pool */);
if (status != qnnp_status_success) {
state.SkipWithError("failed to run Average Pooling operator");
}
}
status = qnnp_delete_operator(poolingOperator);
if (status != qnnp_status_success) {
state.SkipWithError("failed to delete Average Pooling operator");
}
poolingOperator = nullptr;
state.SetBytesProcessed(
uint64_t(state.iterations()) *
batchSize * (inputHeight * inputWidth + outputHeight * outputWidth) * channels * sizeof(uint8_t));
}
/* 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);
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g2, "ShuffleNet v1 (2 groups)")->Apply(ShuffleNetV1G2);
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g3, "ShuffleNet v1 (3 groups)")->Apply(ShuffleNetV1G3);
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g4, "ShuffleNet v1 (4 groups)")->Apply(ShuffleNetV1G4);
BENCHMARK_CAPTURE(average_pooling_q8, shufflenet_v1_g8, "ShuffleNet v1 (8 groups)")->Apply(ShuffleNetV1G8);
#ifndef QNNPACK_BENCHMARK_NO_MAIN
BENCHMARK_MAIN();
#endif