562508c5edf9988078f3ca4300e1d6be569a4b8f,python/timeseries/timeseries_customRNN.py,TsRNNCustom,predict,#TsRNNCustom#Any#Any#,141

Before Change

        if self.n_inputs != 1:
            raise ValueError("Currently only supports univariate input per time-step")
        preds = list()
        x = np.zeros(shape=(1, self.n_lag, 1), dtype=np.float32)
        for i in range(self.n_lag):
            x[0, i, 0] = start_ts[i]
        init_state = np.zeros(shape=(1, self.state_size))
        for i in range(n):
            yhat = self.predict_op.eval(feed_dict={self.X: x,
                                                    self.init_state: init_state})

After Change

        if self.n_inputs != 1:
            raise ValueError("Currently only supports univariate input per time-step")
        seq = list(np.reshape(start_ts, newshape=(-1,)))
        logger.debug("seq: %s" % str(seq))
        preds = list()
        init_state = np.zeros(shape=(1, self.state_size))
        for i in range(n):

Instances