code: def _make_system(A, M, x0, b):
      """Make a linear system Ax = b
  
      Args:
          A (cupy.ndarray or cupyx.scipy.sparse.spmatrix or
              cupyx.scipy.sparse.LinearOperator): sparse or dense matrix.
          M (cupy.ndarray or cupyx.scipy.sparse.spmatrix or
              cupyx.scipy.sparse.LinearOperator): preconditioner.
          x0 (cupy.ndarray): initial guess to iterative method.
          b (cupy.ndarray): right hand side.
  
      Returns:
          tuple:
              It returns (A, M, x, b).
              A (LinaerOperator): matrix of linear system
              M (LinearOperator): preconditioner
              x (cupy.ndarray): initial guess
              b (cupy.ndarray): right hand side.
      """
      fast_matvec = _make_fast_matvec(A)
      A = _interface.aslinearoperator(A)
      if fast_matvec is not None:
          A = _interface.LinearOperator(
              A.shape,
              matvec=fast_matvec,
              rmatvec=A.rmatvec,
              dtype=A.dtype,
          )
      if A.shape[0] != A.shape[1]:
          raise ValueError(
              "expected square matrix (shape: {})".format(A.shape)
          )
      if A.dtype.char not in "fdFD":
          raise TypeError(
              "unsupprted dtype (actual: {})".format(A.dtype)
          )
      n = A.shape[0]
      if not (b.shape == (n,) or b.shape == (n, 1)):
          raise ValueError("b has incompatible dimensions")
      b = b.astype(A.dtype).ravel()
      if x0 is None:
          x = cupy.zeros((n,), dtype=A.dtype)
      else:
          if not (x0.shape == (n,) or x0.shape == (n, 1)):
              raise ValueError("x0 has incompatible dimensions")
          x = x0.astype(A.dtype).ravel()
      if M is None:
          M = _interface.IdentityOperator(shape=A.shape, dtype=A.dtype)
      else:
          fast_matvec = _make_fast_matvec(M)
          M = _interface.aslinearoperator(M)
          if fast_matvec is not None:
              M = _interface.LinearOperator(
                  M.shape,
                  matvec=fast_matvec,
                  rmatvec=M.rmatvec,
                  dtype=M.dtype,
              )
          if A.shape != M.shape:
              raise ValueError(
                  "matrix and preconditioner have different shapes"
              )
      return A, M, x, b
  
file_path: cupy/cupyx/scipy/sparse/linalg/_iterative.py
imports: import numpy
  import cupy
  from cupy import cublas
  from cupy._core import _dtype
  from cupy.cuda import device
  from cupy_backends.cuda.libs import cublas
  from cupyx.scipy.sparse import _csr
  from cupyx.scipy.sparse.linalg import _interface
label_desc: Use image node_id 4 for calling a global function with example usage: _make_system(A, M, x0, b) and returns: A,  M,  x,  b