code: def spsolve_triangular(
      A,
      b,
      lower=True,
      overwrite_A=False,
      overwrite_b=False,
      unit_diagonal=False,
  ):
      """Solves a sparse triangular system ``A x = b``.
  
      Args:
          A (cupyx.scipy.sparse.spmatrix):
              Sparse matrix with dimension ``(M, M)``.
          b (cupy.ndarray):
              Dense vector or matrix with dimension ``(M)`` or ``(M, K)``.
          lower (bool):
              Whether ``A`` is a lower or upper trinagular matrix.
              If True, it is lower triangular, otherwise, upper triangular.
          overwrite_A (bool):
              (not supported)
          overwrite_b (bool):
              Allows overwriting data in ``b``.
          unit_diagonal (bool):
              If True, diagonal elements of ``A`` are assumed to be 1 and will
              not be referenced.
  
      Returns:
          cupy.ndarray:
              Solution to the system ``A x = b``. The shape is the same as ``b``.
      """
      from cupyx import cusparse
  
      if not (
          cusparse.check_availability("spsm")
          or cusparse.check_availability("csrsm2")
      ):
          raise NotImplementedError
  
      if not sparse.isspmatrix(A):
          raise TypeError("A must be cupyx.scipy.sparse.spmatrix")
      if not isinstance(b, cupy.ndarray):
          raise TypeError("b must be cupy.ndarray")
      if A.shape[0] != A.shape[1]:
          raise ValueError(
              f"A must be a square matrix (A.shape: {A.shape})"
          )
      if b.ndim not in [1, 2]:
          raise ValueError(
              f"b must be 1D or 2D array (b.shape: {b.shape})"
          )
      if A.shape[0] != b.shape[0]:
          raise ValueError(
              "The size of dimensions of A must be equal to the "
              "size of the first dimension of b "
              f"(A.shape: {A.shape}, b.shape: {b.shape})"
          )
      if A.dtype.char not in "fdFD":
          raise TypeError(f"unsupported dtype (actual: {A.dtype})")
  
      if cusparse.check_availability("spsm") and _should_use_spsm(b):
          if not (
              sparse.isspmatrix_csr(A)
              or sparse.isspmatrix_csc(A)
              or sparse.isspmatrix_coo(A)
          ):
              warnings.warn(
                  "CSR, CSC or COO format is required. Converting to "
                  "CSR format.",
                  sparse.SparseEfficiencyWarning,
              )
              A = A.tocsr()
          A.sum_duplicates()
          x = cusparse.spsm(A, b, lower=lower, unit_diag=unit_diagonal)
      elif cusparse.check_availability("csrsm2"):
          if not (sparse.isspmatrix_csr(A) or sparse.isspmatrix_csc(A)):
              warnings.warn(
                  "CSR or CSC format is required. Converting to CSR "
                  "format.",
                  sparse.SparseEfficiencyWarning,
              )
              A = A.tocsr()
          A.sum_duplicates()
  
          if (
              overwrite_b
              and A.dtype == b.dtype
              and (b._c_contiguous or b._f_contiguous)
          ):
              x = b
          else:
              x = b.astype(A.dtype, copy=True)
  
          cusparse.csrsm2(A, x, lower=lower, unit_diag=unit_diagonal)
      else:
          assert False
  
      if x.dtype.char in "fF":
          # Note: This is for compatibility with SciPy.
          dtype = numpy.promote_types(x.dtype, "float64")
          x = x.astype(dtype)
      return x
  
imports: import numpy
  import cupy
  from cupy import cublas
  from cupy.cuda import device
  from cupy.cuda import runtime
  from cupy.linalg import _util
  from cupyx.scipy import sparse
  from cupyx.scipy.sparse.linalg import _interface
  from cupyx.scipy.sparse.linalg._iterative import _make_system
  import warnings
label_desc: Use image node_id 4 for calling a global function with example usage: spsolve_triangular(A, b, lower, overwrite_A, overwrite_b, unit_diagonal) and returns: x