models.py 文件源码

def local(nbfilters,fsize1,fsize2,inp,pad = True,subsample = (1,1), batchnorm =True, fast = True):
    if pad:
        inp = layers.ZeroPadding2D(padding=(int((fsize1-1)/2), int((fsize2-1)/2)))(inp)
    if not fast:
        lconv = layers.LocallyConnected2D(nbfilters,fsize1,fsize2,border_mode = 'valid',subsample=subsample)
    else:
        lconv = layers_perso.LocallyConnected2D_fast(nbfilters,fsize1,fsize2,border_mode = 'valid',subsample=subsample)
    conv = lconv((inp))
    if batchnorm:
        conv = layers_perso.BatchNormalization_local(lconv,conv)
    return activation()(conv)