# import xlrd
# import numpy as np
# PATH = './result.xlsx'
#
# def read_excel():
#     workbook = xlrd.open_workbook(PATH, encoding_override='utf-8')
#     allsheetnames = workbook.sheet_names()
#     print(allsheetnames)
#     sheetcontent1 = workbook.sheet_by_index(0)
#     print(sheetcontent1.name, sheetcontent1.nrows, sheetcontent1.ncols)
#     group_result=[]
#     # for i in range(29,41):
#     #     rows = sheetcontent1.row_values(i)
#     #     #print(rows)
#     #     temp_array = np.array(rows[1:])
#     #     arr_mean = np.mean(temp_array)
#     #     arr_std = np.std(temp_array, ddof=1)
#     #     print("列名：", rows[0])
#     #     print('平均值：{}， 标准差：{}'.format(arr_mean, arr_std))
#     #     group_result=[]
#     for i in range(29):
#         rows = sheetcontent1.row_values(i)
#         print(rows)
#         # alone_array = np.array(rows[1:])
#         # arr_mean_row = np.mean(alone_array)
#         # arr_std_row = np.std(alone_array, ddof=1)
#         # #print("列名：", rows[0])
#         # print('单行平均值：{}， 单行标准差：{}'.format(arr_mean_row, arr_std_row))
#         if (i+1) % 4 != 0:
#             group_result.append(rows[1:])
#         else:
#             group_result.append(rows[1:])
#             temp_array = np.array(group_result)
#             arr_mean = np.mean(temp_array)
#             arr_std = np.std(temp_array, ddof=1)
#             print("列名：", rows[0])
#             print('平均值：{}， 标准差：{}'.format(arr_mean, arr_std))
#             group_result=[]
#
#
#
#
# if __name__=='__main__':
#     read_excel()
#
#
#
import numpy as np
import torch
# temp_index = []
# while len(temp_index) < 2:
#     a = np.random.randint(2, 502)
#     if a not in temp_index:
#         temp_index.append(a)
# print(temp_index)
a = torch.rand(256, 1)
b = torch.rand(256, 32)
print((a-b).shape)