code: def vector_norm(
      x: ArrayLike,
      /,
      *,
      axis: int | None = None,
      keepdims: bool = False,
      ord: int | str = 2,
  ) -> Array:
      """Computes the vector norm of a vector (or batch of vectors) x."""
      check_arraylike("jnp.linalg.vector_norm", x)
      if axis is None:
          result = norm(jnp.ravel(x), ord=ord)
          if keepdims:
              result = lax.expand_dims(result, range(jnp.ndim(x)))
          return result
      return norm(x, axis=axis, keepdims=keepdims, ord=ord)
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from functools import partial
  import numpy
  import textwrap
  import operator
  from typing import Literal, cast, overload
  import jax
  from jax import jit, custom_jvp
  from jax import lax
  from jax._src.lax import lax
  from jax._src.lax import linalg
  from jax._src.numpy import lax_numpy
  from jax._src.numpy import reductions, ufuncs
  from jax._src.numpy.util import _wraps, promote_dtypes_inexact, check_arraylike
  from jax._src.util import canonicalize_axis
  from jax._src.typing import ArrayLike, Array
label_desc: Use image node_id 39 for calling a global function with example usage: vector_norm() and returns: norm, result