trainer.py 文件源码

def conv2d(nb_filter, k_size=3, downsample=False):
    from keras.layers import Convolution2D
    from keras.regularizers import l2
    def f(x):
        subsample = (2, 2) if downsample else (1, 1)
        border_mode = 'valid' if k_size == 1 else 'same'
        return Convolution2D(
                    nb_filter=nb_filter, nb_row=k_size, nb_col=k_size, subsample=subsample,
                    init='glorot_normal', W_regularizer=l2(_Wreg_l2), border_mode=border_mode)(x)
    return f