当我使用 tensorflow 时出现错误 Segmentation fault (core dumped)

Question

当我使用 tensorflow 时出现错误 Segmentation fault (core dumped)，我的代码是：

from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras.layers import Embedding
from keras.layers import LSTM
from keras.utils import to_categorical

model = Sequential()
max_features = 100
model.add(Embedding(max_features, output_dim=256))
model.add(LSTM(128))
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy',
              optimizer='rmsprop',
              metrics=['accuracy'])

print("model is ok ")

Answer 1

Segmentation fault意味着您尝试访问您无权访问的内存。 如果选择正确的Tensorflow组合， CUDA和cuDNN将解决这个问题。 您可以参考经过测试的构建配置。

我能够毫无问题地执行上面的代码。 请参考下图

import tensorflow as tf
print(tf.__version__)
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Embedding, LSTM

model = Sequential()
max_features = 100
model.add(Embedding(max_features, output_dim=256))
model.add(LSTM(128))
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))
model.summary()

model.compile(loss='binary_crossentropy',
              optimizer='rmsprop',
              metrics=['accuracy'])

print("model is ok ")

输出：

2.5.0
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
embedding (Embedding)        (None, None, 256)         25600     
_________________________________________________________________
lstm (LSTM)                  (None, 128)               197120    
_________________________________________________________________
dropout (Dropout)            (None, 128)               0         
_________________________________________________________________
dense (Dense)                (None, 1)                 129       
=================================================================
Total params: 222,849
Trainable params: 222,849
Non-trainable params: 0
_________________________________________________________________
model is ok