def get_config(self): config = { 'ensemble_activation': tf.keras.activations.serialize(self.ensemble_activation), 'use_ensemble_bias': self.use_ensemble_bias, 'alpha_initializer': initializers.serialize(self.alpha_initializer), 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'ensemble_bias_initializer': initializers.serialize(self.ensemble_bias_initializer), 'alpha_regularizer': regularizers.serialize(self.alpha_regularizer), 'gamma_regularizer': regularizers.serialize(self.gamma_regularizer), 'ensemble_bias_regularizer': regularizers.serialize(self.ensemble_bias_regularizer), 'alpha_constraint': constraints.serialize(self.alpha_constraint), 'gamma_constraint': constraints.serialize(self.gamma_constraint), 'ensemble_bias_constraint': constraints.serialize(self.ensemble_bias_constraint), 'ensemble_size': self.ensemble_size, } new_config = super().get_config() new_config.update(config) return new_config
def get_config(self): config = { 'activation': tf.keras.activations.serialize(self.activation), 'use_bias': self.use_bias, 'alpha_initializer': initializers.serialize(self.alpha_initializer), 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'alpha_regularizer': regularizers.serialize(self.alpha_regularizer), 'gamma_regularizer': regularizers.serialize(self.gamma_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'alpha_constraint': constraints.serialize(self.alpha_constraint), 'gamma_constraint': constraints.serialize(self.gamma_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint), 'use_additive_perturbation': self.use_additive_perturbation, 'ensemble_size': self.ensemble_size, } base_config = super().get_config() dense_config = self.dense.get_config() return dict( list(base_config.items()) + list(dense_config.items()) + list(config.items()))
def get_config(self): return { 'mean_initializer': serialize(self.mean_initializer), 'stddev_initializer': serialize(self.stddev_initializer), 'mean_regularizer': regularizers.serialize(self.mean_regularizer), 'stddev_regularizer': regularizers.serialize(self.stddev_regularizer), 'mean_constraint': constraints.serialize(self.mean_constraint), 'stddev_constraint': constraints.serialize(self.stddev_constraint), 'seed': self.seed, }
def get_config(self): return { 'loc_initializer': serialize(self.loc_initializer), 'scale_initializer': serialize(self.scale_initializer), 'loc_regularizer': regularizers.serialize(self.loc_regularizer), 'scale_regularizer': regularizers.serialize(self.scale_regularizer), 'loc_constraint': constraints.serialize(self.loc_constraint), 'scale_constraint': constraints.serialize(self.scale_constraint), 'seed': self.seed, }
def get_config(self): return { 'num_components': self.num_components, 'loc_initializer': serialize(self.loc_initializer), 'loc_regularizer': regularizers.serialize(self.loc_regularizer), 'loc_constraint': constraints.serialize(self.loc_constraint), 'seed': self.seed, }
def get_config(self): config = { 'units': self.units, 'lambda_key_to_index': self.lambda_key_to_index, 'rank': self.dense.rank, 'ensemble_size': self.ensemble_size, 'activation': tf.keras.activations.serialize(self.activation), 'use_bias': self.use_bias, 'alpha_initializer': initializers.serialize(self.alpha_initializer), 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'kernel_initializer': initializers.serialize(self.dense.kernel_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.dense.kernel_regularizer), 'bias_regularizer': regularizers.serialize(self.dense.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.dense.kernel_constraint), 'bias_constraint': constraints.serialize(self.dense.bias_constraint), 'regularize_fast_weights': self.regularize_fast_weights, 'fast_weights_eq_contraint': self.fast_weights_eq_contraint } new_config = super().get_config() new_config.update(config) return new_config
def get_config(self): config = { 'ensemble_size': self.ensemble_size, 'alpha_initializer': initializers.serialize(self.alpha_initializer), 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'bias_constraint': constraints.serialize(self.bias_constraint), 'activation': tf.keras.activations.serialize(self.activation), 'use_bias': self.use_bias, } new_config = super(DepthwiseConv2DBatchEnsemble, self).get_config() new_config.update(self.conv2d.get_config()) new_config.update(config) return new_config
def get_config(self): """Returns the configuration for the layer.""" config = { 'units': self.units, 'activation': tf.keras.activations.serialize(self.activation), 'recurrent_activation': tf.keras.activations.serialize( self.recurrent_activation), 'use_bias': self.use_bias, 'alpha_initializer': initializers.serialize(self.alpha_initializer), 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'kernel_initializer': initializers.serialize( self.kernel_initializer), 'recurrent_alpha_initializer': initializers.serialize( self.recurrent_alpha_initializer), 'recurrent_gamma_initializer': initializers.serialize( self.recurrent_gamma_initializer), 'recurrent_initializer': initializers.serialize( self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'unit_forget_bias': self.unit_forget_bias, 'alpha_regularizer': regularizers.serialize(self.alpha_regularizer), 'gamma_regularizer': regularizers.serialize(self.gamma_regularizer), 'kernel_regularizer': regularizers.serialize( self.kernel_regularizer), 'recurrent_alpha_regularizer': regularizers.serialize( self.recurrent_alpha_regularizer), 'recurrent_gamma_regularizer': regularizers.serialize( self.recurrent_gamma_regularizer), 'recurrent_regularizer': regularizers.serialize( self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'alpha_constraint': constraints.serialize(self.alpha_constraint), 'gamma_constraint': constraints.serialize(self.gamma_constraint), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'recurrent_alpha_constraint': constraints.serialize( self.recurrent_alpha_constraint), 'recurrent_gamma_constraint': constraints.serialize( self.recurrent_gamma_constraint), 'recurrent_constraint': constraints.serialize( self.recurrent_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint), 'dropout': self.dropout, 'recurrent_dropout': self.recurrent_dropout, 'implementation': self.implementation, 'use_additive_perturbation': self.use_additive_perturbation, 'ensemble_size': self.ensemble_size, } base_config = super().get_config() return dict(list(base_config.items()) + list(config.items()))