mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-23 17:19:20 +08:00
nihui
100 lines
3.1 KiB
C++
100 lines
3.1 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2017 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#include "benchmark.h"
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#if NCNN_BENCHMARK
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#include <stdio.h>
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#include "layer/convolution.h"
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#ifdef _WIN32
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#define WIN32_LEAN_AND_MEAN
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#include <Windows.h>
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#include <stdint.h> // portable: uint64_t MSVC: __int64
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#else // _WIN32
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#include <sys/time.h>
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#endif // _WIN32
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namespace ncnn {
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#ifdef _WIN32
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struct timeval get_current_time()
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{
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// Note: some broken versions only have 8 trailing zero's, the correct epoch has 9 trailing zero's
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// This magic number is the number of 100 nanosecond intervals since January 1, 1601 (UTC)
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// until 00:00:00 January 1, 1970
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static const uint64_t EPOCH = ((uint64_t) 116444736000000000ULL);
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SYSTEMTIME system_time;
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FILETIME file_time;
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uint64_t time;
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GetSystemTime( &system_time );
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SystemTimeToFileTime( &system_time, &file_time );
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time = ((uint64_t)file_time.dwLowDateTime ) ;
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time += ((uint64_t)file_time.dwHighDateTime) << 32;
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struct timeval tp;
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tp.tv_sec = (long) ((time - EPOCH) / 10000000L);
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tp.tv_usec = (long) (system_time.wMilliseconds * 1000);
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return tp;
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}
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#else // _WIN32
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struct timeval get_current_time()
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{
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struct ::timeval tv;
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::gettimeofday(&tv, NULL);
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struct timeval tp = { tv.tv_sec, tv.tv_usec };
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return tp;
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}
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#endif // _WIN32
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double time_elapsed(struct timeval start, struct timeval end)
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{
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return (end.tv_sec - start.tv_sec) * 1000.0 + (end.tv_usec - start.tv_usec) / 1000.0;
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}
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void benchmark(const ncnn::Layer* layer, struct timeval start, struct timeval end)
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{
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fprintf(stderr, "%-24s %-24s %8.2lfms", layer->type.c_str(), layer->name.c_str(), time_elapsed(start, end));
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fprintf(stderr, " |");
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fprintf(stderr, "\n");
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}
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void benchmark(const Layer* layer, const Mat& bottom_blob, Mat& top_blob, struct timeval start, struct timeval end)
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{
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fprintf(stderr, "%-24s %-24s %8.2lfms", layer->type.c_str(), layer->name.c_str(), time_elapsed(start, end));
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fprintf(stderr, " | feature_map: %4d x %-4d inch: %4d outch: %4d", bottom_blob.w, bottom_blob.h, bottom_blob.c, top_blob.c);
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if (layer->type == "Convolution")
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{
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fprintf(stderr, " kernel: %1d x %1d stride: %1d x %1d",
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((Convolution*)layer)->kernel_w,
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((Convolution*)layer)->kernel_h,
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((Convolution*)layer)->stride_w,
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((Convolution*)layer)->stride_h
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);
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}
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fprintf(stderr, "\n");
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}
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} // namespace ncnn
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#endif // NCNN_BENCHMARK
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