code: def vector_norm(
      x: JaxArray,
      /,
      *,
      axis: Optional[Union[int, Sequence[int]]] = None,
      keepdims: bool = False,
      ord: Union[int, float, Literal[inf, -inf]] = 2,
      out: Optional[JaxArray] = None,
      dtype: Optional[jnp.dtype] = None,
  ) -> JaxArray:
      if dtype and x.dtype != dtype:
          x = x.astype(dtype)
      abs_x = jnp.abs(x)
      if ord == 0:
          return jnp.sum(
              (abs_x != 0).astype(abs_x.dtype),
              axis=axis,
              keepdims=keepdims,
              out=out,
          )
      elif ord == inf:
          return jnp.max(abs_x, axis=axis, keepdims=keepdims, out=out)
      elif ord == -inf:
          return jnp.min(abs_x, axis=axis, keepdims=keepdims, out=out)
      else:
          return jnp.sum(
              abs_x**ord, axis=axis, keepdims=keepdims
          ) ** (1.0 / ord)
  
imports: from collections import namedtuple
  from typing import Union, Optional, Tuple, Literal, Sequence, NamedTuple
  import jax.numpy
  import ivy
  from ivy import inf
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.backends.jax import JaxArray
  from .None import backend_version
  from ivy import promote_types_of_inputs
label_desc: Use image node_id 26 for calling a global function with example usage: vector_norm() and returns: jnp, jnp, jnp, unknown