def setup(self, model, dataset, algorithm):
        dataset = None

        # Central windowing of auxiliary datasets (e.g. validation sets)
        preprocessor = CentralWindow(self._window_shape)
        for data in self._center:
            preprocessor.apply(data)

        #
        # Do the initial random windowing
        #

        randomize_now = self._randomize + self._randomize_once

        # maps each dataset in randomize_now to a zero-padded topological view
        # of its data.
        self._original = dict((data, _zero_pad(
                               data.get_topological_view().astype('float32'),
                               self._pad_randomized))
                              for data in randomize_now)

        # For each dataset, for each image, extract a randomly positioned and
        # potentially horizontal-flipped window
        self.randomize_datasets(randomize_now)
Called by the ServiceTester in order to test query_users
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/train_extensions/window_flip.py/WindowAndFlip.setup--crossover with--dataset/ETHPy150Open viewfinderco/viewfinder/backend/www/test/query_users_test.py/_TestQueryUsers