models.py 文件源码

def finetune(self, X, Y, batch_size=32, gp_n_iter=1, verbose=1):
        """Finetune the output GP layers assuming the network is pre-trained.

        Arguments:
        ----------
            X : np.ndarray or list of np.ndarrays
            Y : np.ndarray or list of np.ndarrays
            batch_size : uint (default: 128)
                Batch size used for data streaming through the network.
            gp_n_iter : uint (default: 100)
                Number of iterations for GP training.
            verbose : uint (default: 1)
                Verbosity mode, 0 or 1.
        """
        # Validate user data
        X = _standardize_input_data(
            X, self.input_names, self.internal_input_shapes,
            check_batch_axis=False)

        H = self.transform(X, batch_size=batch_size)

        if verbose:
            print("Finetuning output GPs...")

        for gp, h, y in zip(self.output_gp_layers, H, Y):
            # Update GP data (and grid if necessary)
            gp.backend.update_data('tr', h, y)
            if gp.update_grid:
                gp.backend.update_grid('tr')

            # Train GP
            gp.hyp = gp.backend.train(gp_n_iter, verbose=verbose)

        if verbose:
            print("Done.")