def _det_large_enough_mask(x, det_bounds):
<EOL>return tf.cast(tf.linalg.det(x) > det_bounds, dtype=x.dtype)<EOL>
Returns whether the input matches the given determinant limit.

    Args:
      x: A floating-point `Tensor` of shape `[B1, ..., Bn, M, M]`.
      det_bounds: A floating-point `Tensor` that must broadcast to shape
        `[B1, ..., Bn]`, giving the desired lower bound on the
        determinants in `x`.

    Returns:
      mask: A floating-point `Tensor` of shape [B1, ..., Bn].  Each
        scalar is 1 if the corresponding matrix had determinant above
        the corresponding bound, otherwise 0.