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add test model yolofastest (OAID#868)
* update test_model_unet * add yolofast test model
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/* | ||
* Licensed to the Apache Software Foundation (ASF) under one | ||
* or more contributor license agreements. See the NOTICE file | ||
* distributed with this work for additional information | ||
* regarding copyright ownership. The ASF licenses this file | ||
* to you under the Apache License, Version 2.0 (the | ||
* License); you may not use this file except in compliance | ||
* with the License. You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, | ||
* software distributed under the License is distributed on an | ||
* AS IS BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
* KIND, either express or implied. See the License for the | ||
* specific language governing permissions and limitations | ||
* under the License. | ||
*/ | ||
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/* | ||
* Copyright (c) 2021, OPEN AI LAB | ||
* Author: [email protected] | ||
* | ||
* original model: https://github.com/dog-qiuqiu/Yolo-Fastest/tree/master/ModelZoo/yolo-fastest-1.1_coco | ||
*/ | ||
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#include <iostream> | ||
#include <iomanip> | ||
#include <vector> | ||
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#ifdef _MSC_VER | ||
#define NOMINMAX | ||
#endif | ||
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#include <algorithm> | ||
#include <cstdlib> | ||
#include <cmath> | ||
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#include "common.h" | ||
#include "tengine/c_api.h" | ||
#include "tengine_operations.h" | ||
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#define DEFAULT_REPEAT_COUNT 1 | ||
#define DEFAULT_THREAD_COUNT 1 | ||
int float_mismatch(float* current, float* reference, int size) | ||
{ | ||
for(int i=0;i<size;i++) | ||
{ | ||
float tmp = fabs(current[i]) - fabs(reference[i]); | ||
if(fabs(tmp) > 0.0001) | ||
{ | ||
fprintf(stderr, "test failed, index:%d, a:%f, b:%f\n", i, current[i], reference[i]); | ||
return -1; | ||
} | ||
} | ||
fprintf(stderr, "test pass\n"); | ||
return 0; | ||
} | ||
enum | ||
{ | ||
YOLOV3 = 0, | ||
YOLO_FASTEST = 1, | ||
YOLO_FASTEST_XL = 2 | ||
}; | ||
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using namespace std; | ||
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static void show_usage() | ||
{ | ||
fprintf(stderr, "[Usage]: [-h]\n [-m model_file] [-r repeat_count] [-t thread_count]\n"); | ||
} | ||
struct TMat | ||
{ | ||
operator const float*() const | ||
{ | ||
return (const float*)data; | ||
} | ||
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float *row(int row) const | ||
{ | ||
return (float *)data + w * row; | ||
} | ||
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TMat channel_range(int start, int chn_num) const | ||
{ | ||
TMat mat = { 0 }; | ||
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mat.batch = 1; | ||
mat.c = chn_num; | ||
mat.h = h; | ||
mat.w = w; | ||
mat.data = (float *)data + start * h * w; | ||
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return mat; | ||
} | ||
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TMat channel(int channel) const | ||
{ | ||
return channel_range(channel, 1); | ||
} | ||
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int batch, c, h, w; | ||
void *data; | ||
}; | ||
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int main(int argc, char* argv[]) | ||
{ | ||
int repeat_count = DEFAULT_REPEAT_COUNT; | ||
int num_thread = DEFAULT_THREAD_COUNT; | ||
char model_string[] = "./models/yolo-fastest-1.1.tmfile"; | ||
char* model_file = model_string; | ||
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int net_w = 320; | ||
int net_h = 320; | ||
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int res; | ||
while ((res = getopt(argc, argv, "m:i:r:t:h:")) != -1) | ||
{ | ||
switch (res) | ||
{ | ||
case 'm': | ||
model_file = optarg; | ||
break; | ||
case 'r': | ||
repeat_count = std::strtoul(optarg, nullptr, 10); | ||
break; | ||
case 't': | ||
num_thread = std::strtoul(optarg, nullptr, 10); | ||
break; | ||
case 'h': | ||
show_usage(); | ||
return 0; | ||
default: | ||
break; | ||
} | ||
} | ||
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/* check files */ | ||
if (nullptr == model_file) | ||
{ | ||
fprintf(stderr, "Error: Tengine model file not specified!\n"); | ||
show_usage(); | ||
return -1; | ||
} | ||
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if (!check_file_exist(model_file)) | ||
return -1; | ||
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/* set runtime options */ | ||
struct options opt; | ||
opt.num_thread = num_thread; | ||
opt.cluster = TENGINE_CLUSTER_ALL; | ||
opt.precision = TENGINE_MODE_FP32; | ||
opt.affinity = 0; | ||
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/* inital tengine */ | ||
if (init_tengine() != 0) | ||
{ | ||
fprintf(stderr, "Initial tengine failed.\n"); | ||
return -1; | ||
} | ||
fprintf(stderr, "tengine-lite library version: %s\n", get_tengine_version()); | ||
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/* create graph, load tengine model xxx.tmfile */ | ||
graph_t graph = create_graph(nullptr, "tengine", model_file); | ||
if (graph == nullptr) | ||
{ | ||
fprintf(stderr, "Create graph failed.\n"); | ||
return -1; | ||
} | ||
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/* set the input shape to initial the graph, and prerun graph to infer shape */ | ||
int img_size = net_h * net_w * 3; | ||
int dims[] = { 1, 3, net_h, net_w }; // nchw | ||
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std::vector<float> input_data(img_size); | ||
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tensor_t input_tensor = get_graph_input_tensor(graph, 0, 0); | ||
if (input_tensor == nullptr) | ||
{ | ||
fprintf(stderr, "Get input tensor failed\n"); | ||
return -1; | ||
} | ||
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if (set_tensor_shape(input_tensor, dims, 4) < 0) | ||
{ | ||
fprintf(stderr, "Set input tensor shape failed\n"); | ||
return -1; | ||
} | ||
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if (set_tensor_buffer(input_tensor, input_data.data(), img_size * 4) < 0) | ||
{ | ||
fprintf(stderr, "Set input tensor buffer failed\n"); | ||
return -1; | ||
} | ||
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/* prerun graph, set work options(num_thread, cluster, precision) */ | ||
if (prerun_graph_multithread(graph, opt) < 0) | ||
{ | ||
fprintf(stderr, "Prerun multithread graph failed.\n"); | ||
return -1; | ||
} | ||
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/* prepare process input data, set the data mem to input tensor */ | ||
std::string model_name="yolo-fastest-1.1"; | ||
std::string input_file = "./data/" + model_name + "_in.bin"; | ||
FILE *fp; | ||
fp = fopen(input_file.c_str(), "rb"); | ||
if (!fp ||fread(input_data.data(), sizeof(float), img_size, fp) == 0) | ||
{ | ||
fprintf(stderr, "read input data file failed!\n"); | ||
return -1; | ||
} | ||
fclose(fp); | ||
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/* run graph */ | ||
double min_time = DBL_MAX; | ||
double max_time = DBL_MIN; | ||
double total_time = 0.; | ||
for (int i = 0; i < repeat_count; i++) | ||
{ | ||
double start = get_current_time(); | ||
if (run_graph(graph, 1) < 0) | ||
{ | ||
fprintf(stderr, "Run graph failed\n"); | ||
return -1; | ||
} | ||
double end = get_current_time(); | ||
double cur = end - start; | ||
total_time += cur; | ||
min_time = std::min(min_time, cur); | ||
max_time = std::max(max_time, cur); | ||
} | ||
fprintf(stderr, "Repeat %d times, thread %d, avg time %.2f ms, max_time %.2f ms, min_time %.2f ms\n", repeat_count, | ||
num_thread, total_time / repeat_count, max_time, min_time); | ||
fprintf(stderr, "--------------------------------------\n"); | ||
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/* process the detection result */ | ||
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int output_node_num = get_graph_output_node_number(graph); | ||
int ret1 = 0; | ||
tensor_t out_tensor; | ||
for (int i = 0; i < output_node_num; ++i) | ||
{ | ||
out_tensor = get_graph_output_tensor(graph, i, 0); //"detection_out" | ||
// save output_data | ||
std::string model_name = "yolo-fastest-1.1"; | ||
int output_size1 = get_tensor_buffer_size(out_tensor) / sizeof(float);; | ||
float* yolo_outputs = (float*)get_tensor_buffer(out_tensor); | ||
std::string reference_file1 = "./data/" + model_name + "_out" + std::to_string(i+1)+".bin"; | ||
std::vector<float> reference_data1(output_size1); | ||
FILE *fp1; | ||
//read | ||
fp1 = fopen(reference_file1.c_str(), "rb"); | ||
if (fread(reference_data1.data(), sizeof(float), output_size1, fp1) == 0) | ||
{ | ||
fprintf(stderr, "read reference data file1 failed!\n"); | ||
return -1; | ||
} | ||
fclose(fp1); | ||
ret1 |= float_mismatch(yolo_outputs, reference_data1.data(), output_size1); | ||
} | ||
/* release tengine */ | ||
postrun_graph(graph); | ||
destroy_graph(graph); | ||
release_tengine(); | ||
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return ret1; | ||
} |
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