tune.py
def create_rnn_experiment(self):
        """Create experiment. Modify as needed."""
        self.experiment = self.conn.experiments().create(
            name="RNNModel Accuracy v1",
            parameters=[dict(name="learning_rate",
                             bounds=dict(min=0.00001, max=0.1),
                             type="double"),
                        dict(name="dropout_rate",
                             bounds=dict(min=0.2, max=0.9),
                             type="double"),
                        dict(name="beta1",
                             bounds=dict(min=0.0001, max=0.999),
                             type="double"),
                        dict(name="beta2",
                             bounds=dict(min=0.0001, max=0.999),
                             type="double"),
                        dict(name="epsilon",
                             bounds=dict(min=1e-8, max=1.0),
                             type="double"),
                        dict(name="n_hidden",
                             bounds=dict(min=1, max=40),
                             type="int"),
                        dict(name="num_fc_1",
                             bounds=dict(min=1, max=40),
                             type="int"),
                        dict(name="n_layers",
                             bounds=dict(min=1, max=10),
                             type="int")
                        ])

        self.logger.info('Experiment created! ID %d.', self.experiment.id)
Create experiment. Modify as needed.
Create experiment. Modify as needed.
Create experiment . Modify as needed .
def create_rnn_experiment(self):
        self.experiment = self.conn.experiments().create(
            name="RNNModel Accuracy v1",
            parameters=[dict(name="learning_rate",
                             bounds=dict(min=0.00001, max=0.1),
                             type="double"),
                        dict(name="dropout_rate",
                             bounds=dict(min=0.2, max=0.9),
                             type="double"),
                        dict(name="beta1",
                             bounds=dict(min=0.0001, max=0.999),
                             type="double"),
                        dict(name="beta2",
                             bounds=dict(min=0.0001, max=0.999),
                             type="double"),
                        dict(name="epsilon",
                             bounds=dict(min=1e-8, max=1.0),
                             type="double"),
                        dict(name="n_hidden",
                             bounds=dict(min=1, max=40),
                             type="int"),
                        dict(name="num_fc_1",
                             bounds=dict(min=1, max=40),
                             type="int"),
                        dict(name="n_layers",
                             bounds=dict(min=1, max=10),
                             type="int")
                        ])
        self.logger.info('Experiment created! ID %d.', self.experiment.id)
def create_rnn_experiment ( self ) : self . experiment = self . conn . experiments ( ) . create ( name = "RNNModel Accuracy v1" , parameters = [ dict ( name = "learning_rate" , bounds = dict ( min = 0.00001 , max = 0.1 ) , type = "double" ) , dict ( name = "dropout_rate" , bounds = dict ( min = 0.2 , max = 0.9 ) , type = "double" ) , dict ( name = "beta1" , bounds = dict ( min = 0.0001 , max = 0.999 ) , type = "double" ) , dict ( name = "beta2" , bounds = dict ( min = 0.0001 , max = 0.999 ) , type = "double" ) , dict ( name = "epsilon" , bounds = dict ( min = 1e-8 , max = 1.0 ) , type = "double" ) , dict ( name = "n_hidden" , bounds = dict ( min = 1 , max = 40 ) , type = "int" ) , dict ( name = "num_fc_1" , bounds = dict ( min = 1 , max = 40 ) , type = "int" ) , dict ( name = "n_layers" , bounds = dict ( min = 1 , max = 10 ) , type = "int" ) ] ) self . logger . info ( 'Experiment created! ID %d.' , self . experiment . id )
Create experiment.
Create experiment .
"""Create experiment. Modify as needed."""
self