code: def _normal_jax(
      shape,
      mean=0.0,
      stddev=1.0,
      dtype=np.float32,
      seed=None,
      name=None,
  ):  # pylint: disable=unused-argument
      dtype = utils.common_dtype([mean, stddev], dtype_hint=dtype)
      shape = _bcast_shape(shape, [mean, stddev])
      import jax.random as jaxrand  # pylint: disable=g-import-not-at-top
  
      if seed is None:
          raise ValueError("Must provide PRNGKey to sample in JAX.")
      return (
          jaxrand.normal(key=seed, shape=shape, dtype=dtype) * stddev
          + mean
      )
  
imports: import numpy
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy.numpy_math import softmax
label_desc: Use image node_id 9 for calling a global function with example usage: _normal_jax(shape, mean, stddev, dtype, seed, name) and returns: unknown