Memory error while using keras

问题

I am using keras for CNN but the problem is that there is memory leak. The error is

        anushreej@cpusrv-gpu-109:~/12EC35005/MTP_Workspace/MTP$ python cnn_implement.py
        Using Theano backend.
        [INFO] compiling model...
        Traceback (most recent call last):
          File "cnn_implement.py", line 23, in <module>
            model = CNNModel.build(width=150, height=150, depth=3)
          File "/home/ms/anushreej/12EC35005/MTP_Workspace/MTP/cnn/networks/model_define.py", line 27, in build
            model.add(Dense(depth*height*width))
          File "/home/ms/anushreej/anaconda3/lib/python3.5/site-packages/keras/models.py", line 146, in add
            output_tensor = layer(self.outputs[0])
          File "/home/ms/anushreej/anaconda3/lib/python3.5/site-packages/keras/engine/topology.py", line 458, in __call__
            self.build(input_shapes[0])
          File "/home/ms/anushreej/anaconda3/lib/python3.5/site-packages/keras/layers/core.py", line 604, in build
            name='{}_W'.format(self.name))
          File "/home/ms/anushreej/anaconda3/lib/python3.5/site-packages/keras/initializations.py", line 61, in glorot_uniform
            return uniform(shape, s, name=name)
          File "/home/ms/anushreej/anaconda3/lib/python3.5/site-packages/keras/initializations.py", line 32, in uniform
            return K.variable(np.random.uniform(low=-scale, high=scale, size=shape),
          File "mtrand.pyx", line 1255, in mtrand.RandomState.uniform (numpy/random/mtrand/mtrand.c:13575)
          File "mtrand.pyx", line 220, in mtrand.cont2_array_sc (numpy/random/mtrand/mtrand.c:2902)
        MemoryError

Now I am unable to understand why is this happening. My training images are very small of the size 150*150*3.

The code is -:

        # import the necessary packages
        from keras.models import Sequential
        from keras.layers.convolutional import Convolution2D
        from keras.layers.core import Activation
        from keras.layers.core import Flatten
        from keras.layers.core import Dense

        class CNNModel:
          @staticmethod
          def build(width, height, depth):
            # initialize the model
            model = Sequential()
            # first set of CONV => RELU
            model.add(Convolution2D(50, 5, 5, border_mode="same", batch_input_shape=(None, depth, height, width)))
            model.add(Activation("relu"))

            # second set of CONV => RELU
            # model.add(Convolution2D(50, 5, 5, border_mode="same"))
            # model.add(Activation("relu"))

            # third set of CONV => RELU
            # model.add(Convolution2D(50, 5, 5, border_mode="same"))
            # model.add(Activation("relu"))

            model.add(Flatten())

            model.add(Dense(depth*height*width))

            # if weightsPath is not None:
            #   model.load_weights(weightsPath) 

            return model

回答1:

I faced the same problem, I think the issue is the number data points just before the Flattening layer are more than your system can handle(i tried in difference systems so one with high ram worked and with less ram gave this error). Just add more CNN layers to reduce the size and then add a flattening layer it works.

This gave me and error:

model = Sequential()
model.add(Convolution2D(32, 3, 3,border_mode='same',input_shape=(1, 96, 96),activation='relu'))
model.add(Convolution2D(64, 3, 3,border_mode='same',activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(Flatten())
model.add(Dense(1000,activation='relu'))
model.add(Dense(97,activation='softmax'))

This didnt give an error

model = Sequential()
model.add(Convolution2D(32, 3, 3,border_mode='same',input_shape=(1, 96, 96),activation='relu'))
model.add(Convolution2D(64, 3, 3,border_mode='same',activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(Convolution2D(64, 3, 3,border_mode='same',activation='relu'))
model.add(Convolution2D(128, 3, 3,border_mode='same',activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(Flatten())
model.add(Dense(1000,activation='relu'))
model.add(Dense(97,activation='softmax')

Hope it helps.

来源：https://stackoverflow.com/questions/38889352/memory-error-while-using-keras

标签

memory-leaks

keras