(self, gaussian_process, beta=2., name='gaussian_process')
Initialization.
Initialization.
Initialization .
def __init__(self, gaussian_process, beta=2., name='gaussian_process'):
        """Initialization."""
        super(GaussianProcess, self).__init__(name=name)

        with tf.variable_scope(self.scope_name):
            self.n_dim = gaussian_process.X.shape[-1]
            self.gaussian_process = gaussian_process
            self.beta = float(beta)

            self.input_dim = gaussian_process.X.shape[1]
            self.output_dim = gaussian_process.Y.shape[1]

            self.hyperparameters = [tf.placeholder(config.dtype, [None])]
            self.gaussian_process.make_tf_array(self.hyperparameters[0])

            self.update_feed_dict()
def __init__ ( self , gaussian_process , beta = 2. , name = 'gaussian_process' ) : super ( GaussianProcess , self ) . __init__ ( name = name ) with tf . variable_scope ( self . scope_name ) : self . n_dim = gaussian_process . X . shape [ - 1 ] self . gaussian_process = gaussian_process self . beta = float ( beta ) self . input_dim = gaussian_process . X . shape [ 1 ] self . output_dim = gaussian_process . Y . shape [ 1 ] self . hyperparameters = [ tf . placeholder ( config . dtype , [ None ] ) ] self . gaussian_process . make_tf_array ( self . hyperparameters [ 0 ] ) self . update_feed_dict ( )