python – TypeError：write()参数必须是str,而不是保存.npy文件时的字节

代码写入.npy文件,如下所示：

bottleneck_features_train = model.predict_generator(generator, nb_train_samples // batch_size)
np.save(open('bottleneck_features_train.npy', 'w'),bottleneck_features_train)

然后它从这个文件中读取：

def train_top_model():
    train_data = np.load(open('bottleneck_features_train.npy'))

现在我收到一个错误说：

Found 2000 images belonging to 2 classes.
Traceback (most recent call last):
  File "kerasbottleneck.py", line 103, in <module>
    save_bottlebeck_features()
  File "kerasbottleneck.py", line 69, in save_bottlebeck_features
    np.save(open('bottleneck_features_train.npy', 'w'),bottleneck_features_train)
  File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/npyio.py", line 511, in save
    pickle_kwargs=pickle_kwargs)
  File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/format.py", line 565, in write_array
version)
  File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/format.py", line 335, in _write_array_header
fp.write(header_prefix)
TypeError: write() argument must be str, not bytes

在此之后,我尝试将文件模式从“w”更改为“wb”.这导致在读取文件时出错：

Found 2000 images belonging to 2 classes.
Found 800 images belonging to 2 classes.
Traceback (most recent call last):
  File "kerasbottleneck.py", line 104, in <module>
    train_top_model()
  File "kerasbottleneck.py", line 82, in train_top_model
    train_data = np.load(open('bottleneck_features_train.npy'))
  File "/opt/anaconda3/lib/python3.6/site-packages/numpy/lib/npyio.py", line 404, in load
magic = fid.read(N)
  File "/opt/anaconda3/lib/python3.6/codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte

我该如何解决这个错误？

np.save(
    open('bottleneck_features_train.npy', 'wb'),
    bottleneck_features_train)

阅读时：

train_data = np.load(open('bottleneck_features_train.npy', 'rb'))

注意模式参数中的b字符.

我将该文件用作上下文管理器,以确保它完全关闭：

with open('bottleneck_features_train.npy', 'wb') as features_train_file
    np.save(features_train_file, bottleneck_features_train)

和

with open('bottleneck_features_train.npy', 'wb') as features_train_file:
    train_data = np.load(features_train_file)

博客文章中的代码无论如何都应该使用这两种更改,因为在Python 2中,没有模式中的b标志文本文件已经翻译了特定于平台的换行约定,并且在Windows中,流中的某些字符将具有特定含义(包括如果出现EOF特征,导致文件显得比实际更短).二进制数据可能是一个真正的问题.