inception_v4.py 文件源码

def conv2d_bn(x, nb_filter, num_row, num_col,
              padding='same', strides=(1, 1), use_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_data_format() == 'channels_first':
        channel_axis = 1
    else:
        channel_axis = -1
    x = Convolution2D(nb_filter, (num_row, num_col),
                      strides=strides,
                      padding=padding,
                      use_bias=use_bias,
                      kernel_regularizer=regularizers.l2(0.00004),
                      kernel_initializer=initializers.VarianceScaling(scale=2.0, mode='fan_in', distribution='normal', seed=None))(x)
    x = BatchNormalization(axis=channel_axis, momentum=0.9997, scale=False)(x)
    x = Activation('relu')(x)
    return x