code: def _validate_args_for_toeplitz_ops(
      c_or_cr, b, check_finite, keep_b_shape, enforce_square=True
  ):
      """Validate arguments and format inputs for toeplitz functions
  
      Parameters
      ----------
      c_or_cr : array_like or tuple of (array_like, array_like)
          The vector ``c``, or a tuple of arrays (``c``, ``r``). Whatever the
          actual shape of ``c``, it will be converted to a 1-D array. If not
          supplied, ``r = conjugate(c)`` is assumed; in this case, if c[0] is
          real, the Toeplitz matrix is Hermitian. r[0] is ignored; the first row
          of the Toeplitz matrix is ``[c[0], r[1:]]``. Whatever the actual shape
          of ``r``, it will be converted to a 1-D array.
      b : (M,) or (M, K) array_like
          Right-hand side in ``T x = b``.
      check_finite : bool
          Whether to check that the input matrices contain only finite numbers.
          Disabling may give a performance gain, but may result in problems
          (result entirely NaNs) if the inputs do contain infinities or NaNs.
      keep_b_shape: bool
          Whether to convert a (M,) dimensional b into a (M, 1) dimensional
          matrix.
      enforce_square: bool, optional
          If True (default), this verifies that the Toeplitz matrix is square.
  
      Returns
      -------
      r : array
          1d array corresponding to the first row of the Toeplitz matrix.
      c: array
          1d array corresponding to the first column of the Toeplitz matrix.
      b: array
          (M,), (M, 1) or (M, K) dimensional array, post validation,
          corresponding to ``b``.
      dtype: numpy datatype
          ``dtype`` stores the datatype of ``r``, ``c`` and ``b``. If any of
          ``r``, ``c`` or ``b`` are complex, ``dtype`` is ``np.complex128``,
          otherwise, it is ``np.float``.
      b_shape: tuple
          Shape of ``b`` after passing it through ``_asarray_validated``.
  
      """
  
      if isinstance(c_or_cr, tuple):
          c, r = c_or_cr
          c = _asarray_validated(c, check_finite=check_finite).ravel()
          r = _asarray_validated(r, check_finite=check_finite).ravel()
      else:
          c = _asarray_validated(
              c_or_cr, check_finite=check_finite
          ).ravel()
          r = c.conjugate()
  
      if b is None:
          raise ValueError("`b` must be an array, not None.")
  
      b = _asarray_validated(b, check_finite=check_finite)
      b_shape = b.shape
  
      is_not_square = r.shape[0] != c.shape[0]
      if (enforce_square and is_not_square) or b.shape[0] != r.shape[0]:
          raise ValueError("Incompatible dimensions.")
  
      is_cmplx = (
          np.iscomplexobj(r) or np.iscomplexobj(c) or np.iscomplexobj(b)
      )
      dtype = np.complex128 if is_cmplx else np.double
      r, c, b = (np.asarray(i, dtype=dtype) for i in (r, c, b))
  
      if b.ndim == 1 and not keep_b_shape:
          b = b.reshape(-1, 1)
      elif b.ndim != 1:
          b = b.reshape(b.shape[0], -1)
  
      return r, c, b, dtype, b_shape
  
imports: from warnings import warn
  import numpy
  from numpy import atleast_1d, atleast_2d
  from .flinalg import get_flinalg_funcs
  from .lapack import get_lapack_funcs, _compute_lwork
  from .misc import LinAlgError, _datacopied, LinAlgWarning
  from .decomp import _asarray_validated
  from .None import decomp, decomp_svd
  from ._solve_toeplitz import levinson
label_desc: Use image node_id 16 for calling a global function with example usage: _validate_args_for_toeplitz_ops(c_or_cr, b, check_finite, keep_b_shape, enforce_square) and returns: r,  c,  b,  dtype,  b_shape