Method __call__

datasets/bucket_config.py:420–426

(self, n_frame: int, height: int, width: int,
                 rnd_state: np.random.RandomState)

        self.frame_grading_arr = np.arange(frame_grading_num) * 4 + 1

    def __call__(self, n_frame: int, height: int, width: int,
                 rnd_state: np.random.RandomState) -> Any:
        tgt_h, tgt_w = self.preprocess(n_frame, height, width, rnd_state)
        flop = FlopEstimator2D1DNotExact(n_frame, tgt_h, tgt_w,
                                         self.pixel_grading_arr,
                                         self.frame_grading_arr)
        return flop