88 lines
1.8 KiB
C++
88 lines
1.8 KiB
C++
#include <cuda_runtime.h>
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#include <unistd.h>
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#include <cstdio>
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#include <cstdlib>
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#include "uNet.h"
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#include "util.h"
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int WARMUP = 0;
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int MEASURE = 1;
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// Global variables
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int N = 1;
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char *parameter_fname;
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char *output_fname;
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char *input_fname;
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/*
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Execute Parameters
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argv[1] = unet model parameters path
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argv[2] = input image path
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argv[3] = output save path
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argv[4] = the number of images to inference
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// optional
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argv[5] = warming up count
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argv[6] = performance measuring count
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*/
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int main(int argc, char **argv) {
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check_and_parse_args(argc, argv);
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print_model();
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// Initialize model
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uNet_initialize(N, parameter_fname);
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Tensor *input = new Tensor({N, 3, 128, 191});
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Tensor *output = new Tensor({N, 2, 128, 191});
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size_t input_size = 0;
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read_binary((void *) input->buf, input_fname, &input_size);
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if (argc > 5){
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WARMUP = atoi(argv[5]);
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MEASURE = atoi(argv[6]);
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}
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printf(" process %d image(s)...", N);
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printf(" Warm up [%d], Performance measure [%d]\n",WARMUP, MEASURE);
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fflush(stdout);
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// warming up
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printf("\nWarmimg up.");
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fflush(stdout);
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for (int i = 0; i < WARMUP; ++i) {
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uNet(input, output, N);
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fflush(stdout);
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printf(".");
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}
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cudaDeviceSynchronize();
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printf("\n");
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// performance measure
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printf("\nProcess.");
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double uNet_st = get_time();
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for (int j = 0; j < MEASURE; ++j) {
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uNet(input, output, N);
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printf(".");
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}
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cudaDeviceSynchronize();
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double uNet_en = get_time();
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printf("\n");
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double elapsed_time = uNet_en - uNet_st;
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elapsed_time = elapsed_time / MEASURE;
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printf("%lfsec (%lf img/sec)\n", elapsed_time, N / elapsed_time);
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write_binary((void *) output->buf, output_fname, (size_t)(N * 2 * 128 * 191));
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printf("Writing final result to %s ...", output_fname);
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fflush(stdout);
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printf("Done!\n\n");
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// Finalize program
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uNet_finalize();
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}
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