773d9932c4b891800bf254d5cea61159056437f1,basenji/rnn.py,RNN,build,#RNN#Any#,18

Before Change

        // print variables
        for v in tf.global_variables():
            print(v.name, v.get_shape())


        //////////////////////////////////////////////////////////////////////////////////////////////////////

After Change

                // batch normalization and ReLU
                dinput = tf.contrib.layers.batch_norm(dinput, decay=0.9, center=True, scale=True, activation_fn=tf.nn.relu, is_training=self.is_training, updates_collections=None)
                print("Batch normalization")
                print("ReLU")

                // dropout
                if self.dcnn_dropout[li] > 0:
                    dinput = tf.nn.dropout(dinput, 1.0-self.dcnn_dropout_ph[li])

Instances