code: def stop_gradient(
      x: Union[tf.Tensor, tf.Variable],
      /,
      *,
      preserve_type: bool = True,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      is_var = is_variable(x)
      x = tf.stop_gradient(x)
      if is_var and preserve_type:
          return variable(x)
      return x
  
file_path: ivy/ivy/functional/backends/tensorflow/gradients.py
imports: import tensorflow
  from typing import Sequence, Union, Optional, Callable
  import ivy
  from ivy.func_wrapper import outputs_to_ivy_arrays, inputs_to_native_arrays
  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