code: def random_normal(
      *,
      mean: Union[float, JaxArray] = 0.0,
      std: Union[float, JaxArray] = 1.0,
      shape: Optional[Union[ivy.NativeShape, Sequence[int]]] = None,
      device: jaxlib.xla_extension.Device = None,
      dtype: jnp.dtype,
      seed: Optional[int] = None,
      out: Optional[JaxArray] = None,
  ) -> JaxArray:
      _check_valid_scale(std)
      shape = _check_bounds_and_get_shape(mean, std, shape).shape
  
      if seed:
          rng_input = jax.random.PRNGKey(seed)
      else:
          RNG_, rng_input = jax.random.split(_getRNG())
          _setRNG(RNG_)
      return (
          jax.random.normal(rng_input, shape, dtype=dtype) * std + mean
      )
  
file_path: ivy/ivy/functional/backends/jax/random.py
imports: import jax
  import jax.numpy
  import jaxlib.xla_extension
  from typing import Optional, Union, Sequence
  import ivy
  from ivy.functional.ivy.random import _check_bounds_and_get_shape, _randint_check_dtype_and_bound, _check_valid_scale
  from ivy.functional.backends.jax import JaxArray
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
label_desc: Use image node_id 4 for calling a global function with example usage: random_normal() and returns: unknown