def get_config(self): config = {"T": self.T, "n_hidden": self.n_hidden, "activation": activations.serialize(self.activation), "activation_lstm": activations.serialize( self.activation_lstm), "recurrent_activation": activations.serialize( self.recurrent_activation), "kernel_initializer": initializers.serialize( self.kernel_initializer), "recurrent_initializer": initializers.serialize( self.recurrent_initializer), "bias_initializer": initializers.serialize( self.bias_initializer), "use_bias": self.use_bias, "unit_forget_bias": self.unit_forget_bias, "kernel_regularizer": regularizers.serialize( self.kernel_regularizer), "recurrent_regularizer": regularizers.serialize( self.recurrent_regularizer), "bias_regularizer": regularizers.serialize( self.bias_regularizer), "kernel_constraint": constraints.serialize( self.kernel_constraint), "recurrent_constraint": constraints.serialize( self.recurrent_constraint), "bias_constraint": constraints.serialize(self.bias_constraint) } base_config = super(Set2Set, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = {'units': self.units, 'rank': self.rank, 'activation': activations.serialize(self.activation), 'recurrent_activation': activations.serialize(self.recurrent_activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'recurrent_initializer': initializers.serialize(self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'unit_forget_bias': self.unit_forget_bias, 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_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} base_config = super(CLSTM, self).get_config() del base_config['cell'] return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'activation': activations.serialize(self.activation), 'recurrent_activation': activations.serialize(self.recurrent_activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'recurrent_initializer': initializers.serialize(self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'recurrent_constraint': constraints.serialize(self.recurrent_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint) } base_config = super(ExtendedRNNCell, self).get_config() config.update(base_config) return config
def get_config(self): config = { 'units': self.units, 'bond_classes': self.bond_classes, 'activation': activations.serialize(self.activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint) } base_config = super(EdgeNetwork, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): """ Part of keras layer interface, where the signature is converted into a dict :return: """ config = { 'activation': activations.serialize(self.activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint) } base_config = super().get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'alpha_initializer': initializers.serialize(self.b_initializer), 'alpha_regularizer': regularizers.serialize(self.b_regularizer), 'alpha_constraint': constraints.serialize(self.b_constraint), 'b_initializer': initializers.serialize(self.b_initializer), 'b_regularizer': regularizers.serialize(self.b_regularizer), 'b_constraint': constraints.serialize(self.b_constraint), 'shared_axes': self.shared_axes } base_config = super(APLUnit, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'units': self.units, 'activation': activations.serialize(self.activation), 'recurrent_activation': activations.serialize(self.recurrent_activation), 'attention_activation': activations.serialize(self.attention_activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'recurrent_initializer': initializers.serialize(self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'attention_initializer': initializers.serialize(self.attention_initializer), 'unit_forget_bias': self.unit_forget_bias, 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'attention_regularizer': regularizers.serialize(self.attention_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'recurrent_constraint': constraints.serialize(self.recurrent_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint), 'attention_constraint': constraints.serialize(self.attention_constraint), 'dropout': self.dropout, 'recurrent_dropout': self.recurrent_dropout, 'return_attention': self.return_attention } base_config = super(AttentionLSTM, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'center': self.center, 'scale': self.scale, 'epsilon': self.epsilon, 'gamma_initializer': initializers.serialize(self.gamma_initializer), 'beta_initializer': initializers.serialize(self.beta_initializer), 'gamma_regularizer': regularizers.serialize(self.gamma_regularizer), 'beta_regularizer': regularizers.serialize(self.beta_regularizer), 'gamma_constraint': constraints.serialize(self.gamma_constraint), 'beta_constraint': constraints.serialize(self.beta_constraint), } base_config = super(LayerNormalization, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'units': self.units, 'steps': self.steps, 'output_dim': self.output_dim, 'atten_units': self.atten_units, 'activation': activations.serialize(self.activation), 'gmax': self.gmax, 'recurrent_activation': activations.serialize(self.recurrent_activation), 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'recurrent_initializer': initializers.serialize(self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'recurrent_constraint': constraints.serialize(self.recurrent_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint), 'dropout': self.dropout, 'recurrent_dropout': self.recurrent_dropout, 'return_probabilities': self.return_probabilities } base_config = super(attention_LSTM, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'units': self.units, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), } base_config = super().get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = {'input_dim': self.input_dim, 'output_dim': self.output_dim, 'mode': self.mode, 'embeddings_initializer': initializers.serialize(self.embeddings_initializer), 'embeddings_regularizer': regularizers.serialize(self.embeddings_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'embeddings_constraint': constraints.serialize(self.embeddings_constraint), 'mask_zero': self.mask_zero} base_config = super(PositionEmbedding, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'rank': self.rank, 'filters': self.filters, 'kernel_size': self.kernel_size_, 'strides': self.strides, 'padding': self.padding, 'data_format': self.data_format, 'dilation_rate': self.dilation_rate, 'activation': activations.serialize(self.activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'activity_regularizer': regularizers.serialize(self.activity_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_constraint), 'bias_constraint': constraints.serialize(self.bias_constraint) } base_config = super(Conv1D_linearphaseType, self).get_config() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = super(DepthConv2D, self).get_config() config.pop('kernel_initializer') config.pop('kernel_regularizer') config.pop('kernel_constraint') config['depth_multiplier'] = self.depth_multiplier config['depthwise_initializer'] = initializers.serialize( self.depthwise_initializer) config['depthwise_regularizer'] = regularizers.serialize( self.depthwise_regularizer) config['depthwise_constraint'] = constraints.serialize( self.depthwise_constraint) return config
def get_config(self): config = { 'units': self.units, 'activation': activations.serialize(self.activation), 'recurrent_activation': activations.serialize(self.recurrent_activation), 'use_bias': self.use_bias, 'kernel_initializer': initializers.serialize(self.kernel_initializer), 'recurrent_initializer': initializers.serialize(self.recurrent_initializer), 'bias_initializer': initializers.serialize(self.bias_initializer), 'kernel_regularizer': regularizers.serialize(self.kernel_regularizer), 'recurrent_regularizer': regularizers.serialize(self.recurrent_regularizer), 'bias_regularizer': regularizers.serialize(self.bias_regularizer), 'kernel_constraint': constraints.serialize(self.kernel_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, 'reset_after': self.reset_after } base_config = super(AttGRUCell, self).get_data_info() return dict(list(base_config.items()) + list(config.items()))
def get_config(self): config = { 'input_dim': self.input_dim, 'output_dim': self.output_dim, 'embeddings_initializer': initializers.serialize(self.embeddings_initializer), 'embeddings_regularizer': regularizers.serialize(self.embeddings_regularizer), 'embeddings_constraint': constraints.serialize(self.embeddings_constraint), } base_config = super(Embedding2D, self).get_config() return dict(list(base_config.items()) + list(config.items()))