def get_config(self): base_config = super(PositionEmbedding, self).get_config() config = {'input_dim': self.input_dim, 'output_dim': self.output_dim, 'merge_mode': self.merge_mode, 'embeddings_initializer': initializers.serialize(self.embeddings_initializer)} return dict(list(base_config.items()) + list(config.items()))
def get_config(self): base_config = super(FeedForward, self).get_config() config = { 'units': self.units, 'activation': self.activation, 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer) } return dict(list(base_config.items()) + list(config.items()))
def get_config(self): base_config = super(LayerNormalization, self).get_config() base_config.update({"center": self.center, "scale": self.scale, "epsilon": self.epsilon, "conditional": self.conditional, "condition_hidden_units": self.condition_hidden_units, "condition_hidden_activation": activations.serialize(self.condition_hidden_activation), "condition_hidden_initializer": initializers.serialize(self.condition_hidden_initializer)}) return base_config
def get_config(self): config = super(MultiHeadAttention, self).get_config() config.update({'head_nums': self.head_nums, 'head_size': self.head_size, 'key_size': self.key_size, 'use_bias': self.use_bias, 'attention_scale': self.attention_scale, 'with_residual_attention': self.with_residual_attention, 'kernel_initializer': initializers.serialize(self.kernel_initializer)}) return config