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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 parse_samples(self, t):
 """ Parse a list of samples to make sure that it has the correct dimensions. :param t: ``(nsamples,)`` or ``(nsamples, ndim)`` The list of samples. If 1-D, this is assumed to be a list of one-dimensional samples otherwise, the size of the second dimension is assumed to be the dimension of the input space. Raises: ValueError: If the input dimension doesn't match the dimension of the kernel. """

        t = np.atleast_1d(t)
        # Deal with one-dimensional data.
        if len(t.shape) == 1:
            t = np.atleast_2d(t).T

        # Double check the dimensions against the kernel.
        if len(t.shape) != 2 or (self.kernel is not None and
                                 t.shape[1] != self.kernel.ndim):
            raise ValueError("Dimension mismatch")

        return t