tensor

x = torch.rand(4,5)
torch.save(x.to(torch.device('cpu')), "myTensor.pth")

y = torch.load("myTensor.pth")
print(y)

list

保存到本地就是保存为.npy文件

import numpy as np
a = [(u'9000023330249', 1), (u'13142928', 1), (u'9000084906496', 1)]
# 保存
np.save('a.npy',a) # 保存为.npy格式

# 读取
b = np.load('a.npy', allow_pickle=True)
#此时b是numpy array
b = b.tolist()

保存为txt文件

 就是直接打开txt文件，往里写

file = open('file_name.txt','w');
file.write(str(list_variable));
file.close();

list保存为json

with open(os.path.join(path, "text_results_rects-format.json"), "w") as f:
    f.write(json.dumps(res))
    f.flush()

numpy array

np.save("filename.npy",a)
b = np.load("filename.npy")

dict

jsObj = json.dumps(dict_)  
fileObject = open('dict.json', 'w')  
fileObject.write(jsObj)  
fileObject.close()

如果字典中的项有numpy.array, 需要.tolist()一下

读就按照json文件来读

也可以用torch保存

保存成pkl或pth或npy都行

d = {0:'a', 1:'b'}
torch.save(d, 'test.pkl')

x = torch.load('test.pth')