code: def _flatten_kernel(
      k: Kernel, x2_is_none: bool, is_parallel: bool
  ) -> Kernel:
      """Flattens a kernel array or a `Kernel` along the batch dimension."""
  
      if hasattr(k, "_asdict") and hasattr(k, "_replace"):
          return k._replace(
              **_flatten_kernel_dict(
                  k._asdict(), x2_is_none, is_parallel
              )
          )
  
      elif isinstance(k, Kernel):
          return Kernel(
              **_flatten_kernel_dict(
                  k.asdict(), x2_is_none, is_parallel
              )
          )
  
      elif isinstance(k, (np.ndarray, jnp.ndarray)):
          return _flatten_batch_dimensions(k, is_parallel)
  
      raise TypeError(
          f"Expected kernel to be either a namedtuple, `Kernel`, or "
          f"`jnp.ndarray`, got {type(k)}."
      )
  
imports: from functools import partial
  from typing import Any, Callable, Iterable, Optional, TypeVar, Union
  import warnings
  import jax
  from jax import device_put
  from jax import devices
  from jax import jit
  from jax import pmap
  from jax import random
  import jax.numpy
  from jax.tree_util import tree_all
  from jax.tree_util import tree_flatten
  from jax.tree_util import tree_map
  from jax.tree_util import tree_unflatten
  import numpy
  from .utils import utils
  from .utils.kernel import Kernel
  from .utils.typing import KernelFn
  from .utils.typing import NTTree
label_desc: Use image node_id 5 for calling a global function with example usage: _flatten_kernel(k, x2_is_none, is_parallel) and returns: k, Kernel, _flatten_batch_dimensions