code: def relu6(
      x: JaxArray,
      /,
      *,
      complex_mode="jax",
      out: Optional[JaxArray] = None,
  ) -> JaxArray:
      relu6_func = jax.nn.relu6
  
      # sets gradient at 0 and 6 to 0 instead of 0.5
      # can refactor to jax.nn.relu6 when this PR is merged
      # https://github.com/google/jax/pull/14682
      def custom_grad_func(x_and_grad, one):
          return lax.select(
              (x_and_grad[0] < 6) & (x_and_grad[0] > 0),
              one,
              lax.full_like(one, 0),
          )
  
      new_func = ivy.bind_custom_gradient_function(
          relu6_func, custom_grad_func
      )
  
      return new_func(x).astype(x.dtype)
  
imports: from typing import Optional, Union, Literal
  import jax
  import jax.numpy
  from ivy.functional.backends.jax import JaxArray
  from jax import lax
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
label_desc: Use image node_id 2 for calling a global function with example usage: relu6() and returns: new_func, lax