Python中这是什么意思Cannot load file containing pickled data when allow_pickle=False
时间: 2024-05-22 22:16:38 浏览: 10
这个错误意味着Python无法加载包含pickle数据的文件,因为在加载时没有启用allow_pickle标志。Python的pickle模块用于序列化和反序列化Python对象,而allow_pickle参数用于控制是否允许加载包含pickle数据的文件。如果allow_pickle=False,则不允许加载pickle数据,如果文件中包含pickle数据,则会引发此错误。要解决此错误,您需要设置allow_pickle=True并重新加载文件。
相关问题
Cannot load file containing pickled data when allow_pickle=False
As an AI language model, I cannot reproduce the error without the complete error message and the code. However, I can provide some general information on the error message "Cannot load file containing pickled data when allow_pickle=False".
This error message occurs when you try to load a file that contains pickled data using the `numpy.load()` function with `allow_pickle=False` argument. By default, `allow_pickle` is set to `True` which allows loading pickled objects. However, it is recommended to set `allow_pickle=False` to avoid security risks.
Here are some possible solutions to this error:
1. Set `allow_pickle=True` when loading the file:
```python
import numpy as np
# Load the file with allow_pickle=True
data = np.load('file.npy', allow_pickle=True)
```
2. Use a different file format that does not use pickling, such as CSV or JSON.
3. If you need to use pickling, consider using a more secure serialization protocol such as the `pickle` module with the `HIGHEST_PROTOCOL` option:
```python
import pickle
# Serialize data using the highest protocol
data = {'key': 'value'}
with open('file.pkl', 'wb') as f:
pickle.dump(data, f, protocol=pickle.HIGHEST_PROTOCOL)
# Load the file with pickle.load()
with open('file.pkl', 'rb') as f:
data = pickle.load(f)
```
这段代码报错ValueError: Cannot load file containing pickled data when allow_pickle=False
这个错误是因为在读取数据时,numpy默认不允许加载pickle数据,而在读取数据时又设置了`allow_pickle=False`,所以无法加载数据。可以尝试将`allow_pickle`设置为True,如下所示:
```python
train_data = np.load(train_mat, allow_pickle=True)
```
如果数据集中包含了可疑数据,建议在读取时将`allow_pickle`设置为False,这会使numpy不加载pickle数据,从而更加安全。如果确实需要加载pickle数据,可以使用`pickle`模块手动加载。例如:
```python
import pickle
with open(train_mat, "rb") as f:
train_data = pickle.load(f)
```
这样就可以手动加载pickle数据了。需要注意的是,pickle数据的加载可能会导致安全问题,因此在加载pickle数据时一定要非常小心。
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