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
