code: def stop_gradient(
      x: Optional[paddle.Tensor],
      /,
      *,
      preserve_type: bool = True,
      out: Optional[paddle.Tensor] = None,
  ):
      is_var = is_variable(x)
      x.stop_gradient = True
      if is_var and preserve_type:
          return variable(x)
      return x
  
file_path: ivy/ivy/functional/backends/paddle/gradients.py
imports: from typing import Optional, Callable
  import paddle
  import ivy.functional.backends.paddle
  from itertools import chain
  import ivy
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from .None import backend_version
  from ivy.functional.ivy.gradients import _get_required_float_variables, _get_y_and_ret_idxs, _get_native_y, _set_duplicates, _process_func_ret_and_grads
label_desc: Use image node_id 7 for calling a global function with example usage: stop_gradient() and returns: x, variable