Tensorflow上的VGG16存儲器問題

Question

我一直試圖讓一個帶有Tensorflow後端的VGG16 Keras模型工作，以便對Kaggle上的'Planet: Understanding the Amazon from Space競賽進行分類。不幸的是，當試圖讓模型運行時，我一直遇到內存問題，即使在AWS的g.2.8大小的內存上運行時也有60 GB的內存。

問題的回溯如下：

Layer (type)     Output Shape    Param # 
================================================================= 
input_1 (InputLayer)   (None, 224, 224, 3)  0 
_________________________________________________________________ 
block1_conv1 (Conv2D)  (None, 224, 224, 64)  1792 
_________________________________________________________________ 
block1_conv2 (Conv2D)  (None, 224, 224, 64)  36928 
_________________________________________________________________ 
block1_pool (MaxPooling2D) (None, 112, 112, 64)  0 
_________________________________________________________________ 
block2_conv1 (Conv2D)  (None, 112, 112, 128)  73856 
_________________________________________________________________ 
block2_conv2 (Conv2D)  (None, 112, 112, 128)  147584 
_________________________________________________________________ 
block2_pool (MaxPooling2D) (None, 56, 56, 128)  0 
_________________________________________________________________ 
block3_conv1 (Conv2D)  (None, 56, 56, 256)  295168 
_________________________________________________________________ 
block3_conv2 (Conv2D)  (None, 56, 56, 256)  590080 
_________________________________________________________________ 
block3_conv3 (Conv2D)  (None, 56, 56, 256)  590080 
_________________________________________________________________ 
block3_pool (MaxPooling2D) (None, 28, 28, 256)  0 
_________________________________________________________________ 
block4_conv1 (Conv2D)  (None, 28, 28, 512)  1180160 
_________________________________________________________________ 
block4_conv2 (Conv2D)  (None, 28, 28, 512)  2359808 
_________________________________________________________________ 
block4_conv3 (Conv2D)  (None, 28, 28, 512)  2359808 
_________________________________________________________________ 
block4_pool (MaxPooling2D) (None, 14, 14, 512)  0 
_________________________________________________________________ 
block5_conv1 (Conv2D)  (None, 14, 14, 512)  2359808 
_________________________________________________________________ 
block5_conv2 (Conv2D)  (None, 14, 14, 512)  2359808 
_________________________________________________________________ 
block5_conv3 (Conv2D)  (None, 14, 14, 512)  2359808 
_________________________________________________________________ 
block5_pool (MaxPooling2D) (None, 7, 7, 512)   0 
_________________________________________________________________ 
sequential_1 (Sequential) (None, 1)     6423041 
================================================================= 
Total params: 21,137,729.0 
Trainable params: 21,137,729.0 
Non-trainable params: 0.0 
_________________________________________________________________ 
Traceback (most recent call last): 
    File "VGG16_Kg_Kernel.py", line 160, in <module> 
     train_datagen.fit(x_train) 
     File "/home/ec2-user/src/anaconda3/lib/python3.5/site-packages/keras/preprocessing/image.py", line 648, in fit 
     x = np.copy(x) 
     File "/home/ec2-user/src/anaconda3/lib/python3.5/site-packages/numpy/lib/function_base.py", line 1497, in copy 
     return array(a, order=order, copy=True) 
    MemoryError 

整個打印輸出可以在這裏找到：https://github.com/j-v-k/VGG16/blob/master/error_text.txt

從打印出來，在GPU似乎運行，但可能無法運行完美。

該數據包含〜100K 11.6 KB圖像。我用來運行模型的代碼可以在這裏找到：https://github.com/j-v-k/VGG16/blob/master/VGG16_Kg_Kernel.py

請讓我知道是否需要更多信息。謝謝！

Answer 1

它的缺點是你沒有GPU內存而不是RAM。 G2有4GB圖形處理器，VGG16和Tensorflow似乎存在問題。

我已經與Theano後端運行一樣，並沒有問題。我建議嘗試一下。