if you want to save and load models that contain this layers you shoud add get_config and from_config methods to custom layers like this
def get_config(self):
config = super(DenseKAN, self).get_config()
config.update({'units':self.units ,
'grid_size':self.grid_size,
'spline_order':self.spline_order,
'grid_range':self.grid_range,
'basis_activation':self.basis_activation,
'use_bias':self.use_bias,
'spline_initialize_stddev':self.spline_initialize_stddev})
return config
@classmethod
def from_config(cls, config):
return cls(**config)
and register them by "tf.keras.utils.get_custom_objects()['DenseKAN'] = DenseKAN"
if you want to save and load models that contain this layers you shoud add get_config and from_config methods to custom layers like this
and register them by "tf.keras.utils.get_custom_objects()['DenseKAN'] = DenseKAN"