Keras model.fit在Google Colab中内存不足

axr492tv  于 2022-11-13  发布在  Go
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我在一个简单的CNN keras模型中内存不足。下面是模型摘要:

Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv1d (Conv1D)             (None, 398, 250)          225250    
                                                                 
 global_max_pooling1d (Globa  (None, 250)              0         
 lMaxPooling1D)                                                  
                                                                 
 dense (Dense)               (None, 250)               62750     
                                                                 
 dropout (Dropout)           (None, 250)               0         
                                                                 
 activation (Activation)     (None, 250)               0         
                                                                 
 dense_1 (Dense)             (None, 1)                 251       
                                                                 
 activation_1 (Activation)   (None, 1)                 0         
                                                                 
=================================================================
Total params: 288,251
Trainable params: 288,251
Non-trainable params: 0
_________________________________________________________________

我有一个20,000 x 400 x 300的嵌入矩阵作为x_train输入(python嵌套列表),所有的值都是np.float16(总大小小于5GB)。

model.fit(x_train, y_train,
batch_size=32,
epochs=2,
verbose=1,
validation_data=(x_test, y_test),)

Colab崩溃并显示消息“您的内存不足”。它甚至没有开始输出详细消息。

7kjnsjlb

7kjnsjlb1#

您应该尝试使用较小的batch_size,您可以从4这样的小值开始,如果您的内存没有崩溃,请尝试将其递增为8、16

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