ValueError: padding must be zero for average_exc_pad

[Shaofanl]

I got ValueError: padding must be zero for average_exc_pad when training the inception network (predicting works). Here is a minimal script to cause that error:

import numpy as np
from keras.models import Model
from keras.utils.np_utils import to_categorical
from keras.layers import Flatten, Dense, Input, BatchNormalization, merge
from keras.layers import Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D

if __name__ == '__main__':
    input_shape = (None, 3, 12, 12)

    bs, c, h, w = input_shape
    data = Input(shape=(c, h, w))

    conv1 = Convolution2D(32, 3, 3, subsample=(1, 1), border_mode='same')(data)

    pool = AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(conv1)

    flat = Flatten()(pool)

    fc = Dense(10, activation='softmax')(flat)

    m = Model(data, fc)
    m.compile('sgd', 'categorical_crossentropy')

    x = np.random.random((100,)+input_shape[1:])
    y = np.random.randint(10, size=(100,1))
    y = to_categorical(y, 10)
    m.predict(x)
    print 'predict done'
    m.fit(x, y)
    print 'fit done'

[Shaofanl]

I tried to replace line

 pool = AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(conv1)

into

#   pool = AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(conv1)      # (32, 12, 12) cannot be trained
#   pool = AveragePooling2D((3, 3), strides=(1, 1))(conv1)                          # (32, 10, 10) can be trained
    pool = AveragePooling2D((3, 3), strides=(1, 1))(ZeroPadding2D((1,1))(conv1))    # (32, 12, 12) can be trained

and the third option works.

However, when I output the result of the first and the third line with:

    check_pool = Model(data, [AveragePooling2D((3, 3), strides=(1, 1))(ZeroPadding2D((1,1))(conv1)),
                              AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(conv1)])
    res = check_pool(x)
    res[0] == res[1]

, I found they are same in all cells except the border.

Is there something wrong with Keras or in the implementation in here?

[fchollet]

The solution to this issue is to use the TensorFlow backend. This appears to be a Theano issue...

[Shaofanl]

Manually using ZeroPadding2D((1,1)) to pad is another choice.
But why the padding results in the following comment are different?

[stale]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed after 30 days if no further activity occurs, but feel free to re-open a closed issue if needed.