def conv2d_bn(x, nb_filter, nb_row, nb_col,
              border_mode='same', subsample=(1, 1), bias=False):
    """
    Utility function to apply conv + BN. 
    (Slightly modified from https://github.com/fchollet/keras/blob/master/keras/applications/inception_v3.py)
    """
    if K.image_dim_ordering() == "th":
        channel_axis = 1
    else:
        channel_axis = -1
    x = Convolution2D(nb_filter, nb_row, nb_col,
                      subsample=subsample,
                      border_mode=border_mode,
                      bias=bias)(x)
    x = BatchNormalization(axis=channel_axis)(x)
    x = Activation('relu')(x)
    return x

    Utility function to apply conv + BN. 
    (Slightly modified from https://github.com/fchollet/keras/blob/master/keras/applications/inception_v3.py)
    
inception_v4.py