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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_dataset(self, X, y=None):
 """Get a dataset that contains the input data and is passed to the iterator. Override this if you want to initialize your dataset differently. Parameters X : input data, compatible with skorch.dataset.Dataset By default, you should be able to pass: * numpy arrays * torch tensors * pandas DataFrame or Series * scipy sparse CSR matrices * a dictionary of the former three * a list/tuple of the former three * a Dataset If this doesn't work with your data, you have to pass a ``Dataset`` that can deal with the data. y : target data, compatible with skorch.dataset.Dataset The same data types as for ``X`` are supported. If your X is a Dataset that contains the target, ``y`` may be set to None. Returns ------- dataset The initialized dataset. """

        if is_dataset(X):
            return X

        dataset = self.dataset
        is_initialized = not callable(dataset)

        kwargs = self._get_params_for('dataset')
        if kwargs and is_initialized:
            raise TypeError("Trying to pass an initialized Dataset while "
                            "passing Dataset arguments ({}) is not "
                            "allowed.".format(kwargs))

        if is_initialized:
            return dataset

        return dataset(X, y, **kwargs)