03a7eb89e27b70f2ca0ac932ef4bace7569d6fab,keras/layers/recurrent.py,LSTM,get_config,#LSTM#,891

Before Change


        return constants

    def get_config(self):
        config = {"output_dim": self.output_dim,
                  "init": initializers.get_config(self.init),
                  "inner_init": initializers.get_config(self.inner_init),
                  "forget_bias_init": initializers.get_config(self.forget_bias_init),
                  "activation": self.activation.__name__,
                  "inner_activation": self.inner_activation.__name__,
                  "W_regularizer": self.W_regularizer.get_config() if self.W_regularizer else None,
                  "U_regularizer": self.U_regularizer.get_config() if self.U_regularizer else None,
                  "b_regularizer": self.b_regularizer.get_config() if self.b_regularizer else None,
                  "dropout_W": self.dropout_W,
                  "dropout_U": self.dropout_U}
        base_config = super(LSTM, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))

After Change


        return h, [h, c]

    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),
                  "unit_forget_bias": self.unit_forget_bias,
                  "kernel_regularizer": regularizers.serialize(kernel_regularizer),
                  "recurrent_regularizer": regularizers.serialize(recurrent_regularizer),
                  "bias_regularizer": regularizers.serialize(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}
        base_config = super(LSTM, self).get_config()
        return dict(list(base_config.items()) + list(config.items()))
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 50

Instances


Project Name: keras-team/keras
Commit Name: 03a7eb89e27b70f2ca0ac932ef4bace7569d6fab
Time: 2017-02-13
Author: francois.chollet@gmail.com
File Name: keras/layers/recurrent.py
Class Name: LSTM
Method Name: get_config


Project Name: keras-team/keras
Commit Name: 03a7eb89e27b70f2ca0ac932ef4bace7569d6fab
Time: 2017-02-13
Author: francois.chollet@gmail.com
File Name: keras/layers/recurrent.py
Class Name: SimpleRNN
Method Name: get_config


Project Name: keras-team/keras
Commit Name: 03a7eb89e27b70f2ca0ac932ef4bace7569d6fab
Time: 2017-02-13
Author: francois.chollet@gmail.com
File Name: keras/layers/recurrent.py
Class Name: LSTM
Method Name: get_config


Project Name: keras-team/keras
Commit Name: 03a7eb89e27b70f2ca0ac932ef4bace7569d6fab
Time: 2017-02-13
Author: francois.chollet@gmail.com
File Name: keras/layers/recurrent.py
Class Name: GRU
Method Name: get_config