389 lines
14 KiB
C
389 lines
14 KiB
C
#include "cnn_model.h"
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Model conv1_bias;
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Model conv1_weight;
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Model conv2_bias;
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Model conv2_weight;
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Model conv3_bias;
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Model conv3_weight;
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Model fc1_bias;
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Model fc1_weight;
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Model fc2_bias;
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Model fc2_weight;
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Model data;
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float* modelmym_init(char* model_name){
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if(conv1_bias.array == NULL && strcmp(model_name, "conv1_bias") == 0)
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return conv1_bias.array = (float*)malloc(CONV1_BIAS_ARRSIZE * sizeof(float));
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else if(conv1_weight.array == NULL && strcmp(model_name, "conv1_weight") == 0)
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return conv1_weight.array = (float*)malloc(CONV1_WEIGHT_ARRSIZE * sizeof(float));
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else if(conv2_bias.array == NULL && strcmp(model_name, "conv2_bias") == 0)
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return conv2_bias.array = (float*)malloc(CONV2_BIAS_ARRSIZE * sizeof(float));
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else if(conv2_weight.array == NULL && strcmp(model_name, "conv2_weight") == 0)
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return conv2_weight.array = (float*)malloc(CONV2_WEIGHT_ARRSIZE * sizeof(float));
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else if(conv3_bias.array == NULL && strcmp(model_name, "conv3_bias") == 0)
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return conv3_bias.array = (float*)malloc(CONV3_BIAS_ARRSIZE * sizeof(float));
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else if(conv3_weight.array == NULL && strcmp(model_name, "conv3_weight") == 0)
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return conv3_weight.array = (float*)malloc(CONV3_WEIGHT_ARRSIZE * sizeof(float));
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else if(fc1_bias.array == NULL && strcmp(model_name, "fc1_bias") == 0)
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return fc1_bias.array = (float*)malloc(FC1_BIAS_ARRSIZE * sizeof(float));
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else if(fc1_weight.array == NULL && strcmp(model_name, "fc1_weight") == 0)
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return fc1_weight.array = (float*)malloc(FC1_WEIGHT_ARRSIZE * sizeof(float));
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else if(fc2_bias.array == NULL && strcmp(model_name, "fc2_bias") == 0)
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return fc2_bias.array = (float*)malloc(FC2_BIAS_ARRSIZE * sizeof(float));
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else if(fc2_weight.array == NULL && strcmp(model_name, "fc2_weight") == 0)
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return fc2_weight.array = (float*)malloc(FC2_WEIGHT_ARRSIZE * sizeof(float));
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else if(data.array == NULL && strcmp(model_name, "data") == 0)
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return data.array = (float*)malloc(DATA_ARRSIZE * sizeof(float));
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else if(strcmp(model_name, "all") == 0){
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if(conv1_bias.array == NULL)conv1_bias.array = (float*)malloc(CONV1_BIAS_ARRSIZE * sizeof(float));
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if(conv1_weight.array == NULL)conv1_weight.array = (float*)malloc(CONV1_WEIGHT_ARRSIZE * sizeof(float));
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if(conv2_bias.array == NULL)conv2_bias.array = (float*)malloc(CONV2_BIAS_ARRSIZE * sizeof(float));
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if(conv2_weight.array == NULL)conv2_weight.array = (float*)malloc(CONV2_WEIGHT_ARRSIZE * sizeof(float));
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if(conv3_bias.array == NULL)conv3_bias.array = (float*)malloc(CONV3_BIAS_ARRSIZE * sizeof(float));
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if(conv3_weight.array == NULL)conv3_weight.array = (float*)malloc(CONV3_WEIGHT_ARRSIZE * sizeof(float));
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if(fc1_bias.array == NULL)fc1_bias.array = (float*)malloc(FC1_BIAS_ARRSIZE * sizeof(float));
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if(fc1_weight.array == NULL)fc1_weight.array = (float*)malloc(FC1_WEIGHT_ARRSIZE * sizeof(float));
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if(fc2_bias.array == NULL)fc2_bias.array = (float*)malloc(FC2_BIAS_ARRSIZE * sizeof(float));
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if(fc2_weight.array == NULL)fc2_weight.array = (float*)malloc(FC2_WEIGHT_ARRSIZE * sizeof(float));
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if(data.array == NULL)data.array = (float*)malloc(DATA_ARRSIZE * sizeof(float));
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}
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return NULL;
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}
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u8 modelmym_free(char* model_name){
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if(conv1_bias.array != NULL && strcmp(model_name, "conv1_bias") == 0){
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free(conv1_bias.array);
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conv1_bias.array = NULL;
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conv1_bias.realength = 0;
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return 1;
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}
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else if(conv1_weight.array != NULL && strcmp(model_name, "conv1_weight") == 0){
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free(conv1_weight.array);
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conv1_weight.array = NULL;
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conv1_weight.realength = 0;
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return 1;
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}
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else if(conv2_bias.array != NULL && strcmp(model_name, "conv2_bias") == 0){
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free(conv2_bias.array);
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conv2_bias.array = NULL;
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conv2_bias.realength = 0;
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return 1;
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}
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else if(conv2_weight.array != NULL && strcmp(model_name, "conv2_weight") == 0){
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free(conv2_weight.array);
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conv2_weight.array = NULL;
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conv2_weight.realength = 0;
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return 1;
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}
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else if(conv3_bias.array != NULL && strcmp(model_name, "conv3_bias") == 0){
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free(conv3_bias.array);
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conv3_bias.array = NULL;
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conv3_bias.realength = 0;
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return 1;
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}
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else if(conv3_weight.array != NULL && strcmp(model_name, "conv3_weight") == 0){
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free(conv3_weight.array);
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conv3_weight.array = NULL;
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conv3_weight.realength = 0;
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return 1;
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}
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else if(fc1_bias.array != NULL && strcmp(model_name, "fc1_bias") == 0){
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free(fc1_bias.array);
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fc1_bias.array = NULL;
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fc1_bias.realength = 0;
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return 1;
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}
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else if(fc1_weight.array != NULL && strcmp(model_name, "fc1_weight") == 0){
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free(fc1_weight.array);
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fc1_weight.array = NULL;
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fc1_weight.realength = 0;
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return 1;
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}
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else if(fc2_bias.array != NULL && strcmp(model_name, "fc2_bias") == 0){
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free(fc2_bias.array);
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fc2_bias.array = NULL;
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fc2_bias.realength = 0;
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return 1;
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}
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else if(fc2_weight.array != NULL && strcmp(model_name, "fc2_weight") == 0){
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free(fc2_weight.array);
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fc2_weight.array = NULL;
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fc2_weight.realength = 0;
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return 1;
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}
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else if(data.array != NULL && strcmp(model_name, "data") == 0){
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free(data.array);
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data.array = NULL;
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data.realength = 0;
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return 1;
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}
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else if(strcmp(model_name, "all") == 0){
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modelmym_free("conv1_bias");
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modelmym_free("conv1_weight");
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modelmym_free("conv2_bias");
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modelmym_free("conv2_weight");
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modelmym_free("conv3_bias");
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modelmym_free("conv3_weight");
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modelmym_free("fc1_bias");
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modelmym_free("fc1_weight");
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modelmym_free("fc2_bias");
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modelmym_free("fc2_weight");
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modelmym_free("data");
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return 2;
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}
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return 0;
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}
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u8 model_write(char* model_name)
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{
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if(strcmp(model_name, "all") == 0){
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model_write("conv1_bias");
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model_write("conv1_weight");
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model_write("conv2_bias");
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model_write("conv2_weight");
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model_write("conv3_bias");
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model_write("conv3_weight");
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model_write("fc1_bias");
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model_write("fc1_weight");
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model_write("fc2_bias");
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model_write("fc2_weight");
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model_info("all");
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SDRAM_USED();
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}else{
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u8 _times=0;
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u32 _larr = 0;
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u8 _len = strlen(model_name);
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char _path[_len+1+7+30];
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char _fstr[READLENGTH+1] = {0};
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int progress;
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Model *_model = model(model_name);
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if(_model == NULL || strcmp(model_name, "data") == 0){
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sprintf(_path, "./dataset/%s.txt", model_name);
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FILE *file = fopen(_path, "r");
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if(file == NULL){
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DEBUG_PRINTF("\r\n输入了一个无效的模型或Data数据集的名字\r\n");
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return 199;
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}else{
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_model = model("data");
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_model -> dname = model_name;
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}
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}
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if(_model -> dname == NULL){
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sprintf(_path, "./dataset/%s.txt", _model -> name);
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FILE *file = fopen(_path, "r");
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if(file == NULL){
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DEBUG_PRINTF("预设里没有这个模型：[%s]\r\n", _path);
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return 4;
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}
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}
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if(_model -> array == NULL && modelmym_init(_model -> name) == NULL){
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DEBUG_PRINTF("无法创建模型参数[%s]的数组到SDRAM里\r\n", _model -> name);
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return 200;
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}
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sprintf(_path, "./dataset/%s.txt", _model -> name);
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FILE *file = fopen(_path, "r");
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DEBUG_PRINTF("写入的模型参数名字是：%s\r\n", _model -> name);
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if(_model -> dname)DEBUG_PRINTF("写入的Data数据集是：%s\r\n", _model -> dname);
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DEBUG_PRINTF("写入模型参数数组的最大长度为：%d\r\n", _model -> maxlength);
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DEBUG_PRINTF("目前数组存活的元素数量为：%d", _model -> realength);
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printf("\r\n正在写入模型参数'%s'，请稍后......\r\n",_model -> dname ? _model -> dname : _model -> name);
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while(_larr < _model->maxlength && fgets(_fstr, sizeof(_fstr), file) != NULL){
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char *endptr;
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float value = strtof(_fstr, &endptr);
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// 检查是否转换成功
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if (endptr == _fstr) {
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fprintf(stderr, "第 %d 行不是有效的浮点数: %s", _larr + 1, _fstr);
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continue; // 跳过无效行
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}
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_model->array[_larr++] = value;
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_model->realength++;
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if(_model -> maxlength >= 73728 && (_larr >= (_model -> maxlength/10)*_times)){
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progress = _larr >= _model -> maxlength ? 100 : _times++ == 0 ? 0 : progress + 10;
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DEBUG_PRINTF("\r\n[");
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for(u16 j=0; j<50;j++){
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if(j < progress/2) DEBUG_PRINTF("=");
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else DEBUG_PRINTF(" ");
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}
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DEBUG_PRINTF("] %d%%", progress);
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}
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if(_larr >= _model -> maxlength)break;
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}
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DEBUG_PRINTF("\r\n模型参数[%s]已写入到内存中! 模型长度为 %d\r\n",_model -> dname ? _model -> dname : _model -> name,_model -> realength);
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return 1;
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}
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return 0;
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}
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u8 model_read(char* model_name, u32 start, u32 end, u32 gap){
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if(strcmp(model_name, "all") == 0){
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model_read("conv1_bias", start, end, gap);
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model_read("conv1_weight", start, end, gap);
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model_read("conv2_bias", start, end, gap);
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model_read("conv2_weight", start, end, gap);
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model_read("conv3_bias", start, end, gap);
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model_read("conv3_weight", start, end, gap);
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model_read("fc1_bias", start, end, gap);
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model_read("fc1_weight", start, end, gap);
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model_read("fc2_bias", start, end, gap);
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model_read("fc2_weight", start, end, gap);
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model_read("data", start, end, gap);
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}else{
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Model *_model = model(model_name);
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if(_model == NULL || end == 0 || start > _model -> realength || end > _model -> realength)return 0;
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if(_model -> realength){
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for (u32 i=0;i<((end > (_model -> realength) ? _model -> realength : (end-start))+(end > (_model -> realength) ? _model -> realength : (end-start)%gap ? 2 : 1));i+=gap)
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printf("\r\n%s_floatArray[%d]: %f",_model->name,(i+start)<_model->realength ? i+start : _model->realength-1,(i+start)<_model->realength ? _model->array[i+start] : _model->array[_model -> realength-1]);
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printf("\r\n");
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return 1;
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}
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}
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return 0;
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}
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u8 model_switchdata(char* data_name){
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u8 _len = strlen(data_name);
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char _path[_len+1+7];
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if(data.array != NULL)modelmym_free("data");
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sprintf(_path, "./dataset/%s.txt", data_name);
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FILE *file = fopen(_path, "r");
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if(file == NULL){
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DEBUG_PRINTF("\r\nData数据集[%s]不存在\r\n",data_name);
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return 0;
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}else{
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u8 _res = model_write(data_name);
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if (_res == 0) {
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DEBUG_PRINTF("Data数据集[%s]切换失败！！\r\n",data_name);
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return 0;
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}
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else printf("Data数据集[%s]切换成功！\r\n",data_name);
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DEBUG_PRINTF("data_name的长度为：%d\r\n_path的长度为：%d\r\n_path为：%s\r\n",_len,sizeof(_path),_path);
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return 1;
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}
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}
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void model_dataset(){
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printf("\r\ndataset is: %s\r\n",data.dname);
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}
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u8 model_info(char* model_name){
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if(strcmp(model_name, "all") == 0){
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model_info("conv1_bias");
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model_info("conv1_weight");
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model_info("conv2_bias");
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model_info("conv2_weight");
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model_info("conv3_bias");
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model_info("conv3_weight");
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model_info("fc1_bias");
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model_info("fc1_weight");
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model_info("fc2_bias");
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model_info("fc2_weight");
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model_info("data");
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return 1;
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}else if(model(model_name)){
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Model *_model = model(model_name);
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printf("\r\nmodel.name is: %s\r\n",_model -> name);
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printf("model.array.address is: 0X%X\r\n",_model -> array);
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printf("model.maxlength is: %d\r\n",_model -> maxlength);
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printf("model.realength is: %d\r\n",_model -> realength);
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//if(strcmp(_model -> name, "data") == 0)printf("dataset is: %s\r\n",_model -> dname); 这函数有BUG，用model_dataset函数
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return 1;
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}
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return 0;
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}
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void* model(char* model_name){
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if(strcmp(model_name, "conv1_bias") == 0)return &conv1_bias;
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else if(strcmp(model_name, "conv1_weight") == 0)return &conv1_weight;
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else if(strcmp(model_name, "conv2_bias") == 0)return &conv2_bias;
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else if(strcmp(model_name, "conv2_weight") == 0)return &conv2_weight;
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else if(strcmp(model_name, "conv3_bias") == 0)return &conv3_bias;
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else if(strcmp(model_name, "conv3_weight") == 0)return &conv3_weight;
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else if(strcmp(model_name, "fc1_bias") == 0)return &fc1_bias;
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else if(strcmp(model_name, "fc1_weight") == 0)return &fc1_weight;
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else if(strcmp(model_name, "fc2_bias") == 0)return &fc2_bias;
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else if(strcmp(model_name, "fc2_weight") == 0)return &fc2_weight;
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else if(strcmp(model_name, "data") == 0)return &data;
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return NULL;
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}
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void model_init(){
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conv1_bias.name = "conv1_bias";
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conv1_bias.array = modelmym_init(conv1_bias.name);
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conv1_bias.maxlength = CONV1_BIAS_ARRSIZE;
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conv1_weight.name = "conv1_weight";
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conv1_weight.array = modelmym_init(conv1_weight.name);
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conv1_weight.maxlength = CONV1_WEIGHT_ARRSIZE;
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conv1_weight.channel = 1;
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conv1_weight.num_kernels = 32;
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conv2_bias.name = "conv2_bias";
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conv2_bias.array = modelmym_init(conv2_bias.name);
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conv2_bias.maxlength = CONV2_BIAS_ARRSIZE;
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conv2_weight.name = "conv2_weight";
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conv2_weight.array = modelmym_init(conv2_weight.name);
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conv2_weight.maxlength = CONV2_WEIGHT_ARRSIZE;
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conv2_weight.channel = 32;
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conv2_weight.num_kernels = 64;
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conv3_bias.name = "conv3_bias";
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conv3_bias.array = modelmym_init(conv3_bias.name);
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conv3_bias.maxlength = CONV3_BIAS_ARRSIZE;
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conv3_weight.name = "conv3_weight";
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conv3_weight.array = modelmym_init(conv3_weight.name);
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conv3_weight.maxlength = CONV3_WEIGHT_ARRSIZE;
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conv3_weight.channel = 64;
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conv3_weight.num_kernels = 128;
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fc1_bias.name = "fc1_bias";
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fc1_bias.array = modelmym_init(fc1_bias.name);
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fc1_bias.maxlength = FC1_BIAS_ARRSIZE;
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fc1_weight.name = "fc1_weight";
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fc1_weight.array = modelmym_init(fc1_weight.name);
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fc1_weight.maxlength = FC1_WEIGHT_ARRSIZE;
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fc2_bias.name = "fc2_bias";
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fc2_bias.array = modelmym_init(fc2_bias.name);
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fc2_bias.maxlength = FC2_BIAS_ARRSIZE;
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fc2_weight.name = "fc2_weight";
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fc2_weight.array = modelmym_init(fc2_weight.name);
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fc2_weight.maxlength = FC2_WEIGHT_ARRSIZE;
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data.name = "data";
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data.array = modelmym_init(data.name);
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data.maxlength = DATA_ARRSIZE;
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data.dname = "data";
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}
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