# -*- coding:utf-8 -*- import os import numpy as np ‘‘‘ def weight_bias(): value = [] fh = open(weight_path, ‘r‘) for line in fh: line = line.rstrip() line = line.strip(‘\n‘) words = line.split() value.append(words[0]) fh = open(bias_path, ‘r‘) for line in fh: line = line.rstrip() line = line.strip(‘\n‘) words = line.split() value.append(words[0]) print(len(value)) with open(out_path, ‘w‘)as f: for i in range(len(value)): val = ‘%.8f‘%(float(value[i])) f.write(val+‘,‘) if (i+1)%10==0: f.write(‘\n‘) f.close() if __name__ == ‘__main__‘: weight_path = "./_Conv2d_weights.txt" bias_path = "./_Conv2D_bias.txt" out_path = "./out.txt" weight_bias() ‘‘‘ def weight_bias(): weight_data = read_img_from_npy(weight_path) bias_data = read_img_from_npy(bias_path) bias_data = 0.00006179179035825655 * bias_data value = [] for i in range(weight_data.shape[0]): for j in range(weight_data.shape[1]): for s in range(weight_data.shape[2]): for t in range(weight_data.shape[3]): val = 0.0026262556202709675 * (weight_data[i,j,s,t] - 126) value.append(val) value.append(bias_data[0]) print(len(value)) with open(out_path, ‘w‘)as f: for i in range(len(value)): val = ‘%.8f‘%value[i] f.write(val+‘,‘) if (i+1)%10==0: f.write(‘\n‘) f.close() def read_img_from_npy(weight_path): datas = np.load(weight_path) return datas if __name__ == ‘__main__‘: weight_path = "./_Conv2d_weight.npy" bias_path = "./_Conv2d_bias.npy" out_path = "./out0902.txt" weight_bias()