code: def solve_triangular(
      x1: paddle.Tensor,
      x2: paddle.Tensor,
      /,
      *,
      upper: bool = True,
      adjoint: bool = False,
      unit_diagonal: bool = False,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      # Paddle does not support complex tensors for this operation (cpu and gpu),
      # so adjoint always equals transpose.
      return paddle.linalg.triangular_solve(
          x1,
          x2,
          upper=upper,
          transpose=adjoint,
          unitriangular=unit_diagonal,
      )
  
file_path: ivy/ivy/functional/backends/paddle/experimental/linear_algebra.py
imports: import paddle
  from typing import Optional, Tuple, Union, Any
  from ivy.functional.ivy.experimental.linear_algebra import _check_valid_dimension_size
  from ivy.func_wrapper import with_unsupported_device_and_dtypes, with_supported_device_and_dtypes
  from ivy.utils.exceptions import IvyNotImplementedException
  from ..None import backend_version
label_desc: Use image node_id 7 for calling a global function with example usage: solve_triangular() and returns: paddle