Question

我是编码的初学者，我的项目现在涉及图像分类。在深度学习类的下面的代码中，有一个函数maybe_pickle，但我不知道“pickle”做了什么，虽然我尝试寻找一些答案，但它有多大帮助。

def maybe_pickle(data_folders, min_num_images_per_class, force=False):


dataset_names = []
  for folder in data_folders:
    set_filename = folder + '.pickle'
    dataset_names.append(set_filename)
    if os.path.exists(set_filename) and not force:
      # You may override by setting force=True.
      print('%s already present - Skipping pickling.' % set_filename)
    else:
      print('Pickling %s.' % set_filename)
      dataset = load_letter(folder, min_num_images_per_class)
      try:
        with open(set_filename, 'wb') as f:
          pickle.dump(dataset, f, pickle.HIGHEST_PROTOCOL)
      except Exception as e:
        print('Unable to save data to', set_filename, ':', e)

  return dataset_names

train_datasets = maybe_pickle(train_folders, 45000)
test_datasets = maybe_pickle(test_folders, 1800)
# import pickle

# Create a list
test_values = ['test value','test value 2','test value 3']


file_Name = "testfile"
# Open the file for writing
fileObject = open(file_Name,'wb') 

# This writes the object a to the
# file named 'testfile'
pickle.dump(test_values, fileObject)   

# Then we close the fileObject
fileObject.close()

# We then open the file for reading
fileObject = open(file_Name,'r')  

# And the object from the file into var b
test_values_loaded = pickle.load(fileObject)

Answer 1

首先查看官方pickle documentation。它需要一个可以序列化的Python对象并将其转换为可以保存到磁盘的字节流（或者反向，从文件开始并将其转换回Python对象。如果要在两者之间保存状态，通常会执行此操作。运行或者如果你想缓存长时间运行的操作的结果（例如，like_ *就像函数通常用于此目的）。

什么是“泡菜”实际上用于？

1 个答案: