code: def split_and_load(data, ctx_list, batch_axis=0, even_split=True):
      """Splits an NDArray into `len(ctx_list)` slices along `batch_axis` and loads
      each slice to one context in `ctx_list`.
  
      Parameters
      ----------
      data : NDArray or ndarray
          A batch of data.
      ctx_list : list of Context
          A list of Contexts.
      batch_axis : int, default 0
          The axis along which to slice.
      even_split : bool, default True
          Whether to force all slices to have the same number of elements.
  
      Returns
      -------
      list of NDArrays or ndarrays
          Each corresponds to a context in `ctx_list`.
      """
      array_fn = _mx_np.array if is_np_array() else ndarray.array
      if not isinstance(data, ndarray.NDArray):
          data = array_fn(data, ctx=ctx_list[0])
      if len(ctx_list) == 1:
          return [data.as_in_context(ctx_list[0])]
  
      slices = split_data(data, len(ctx_list), batch_axis, even_split)
      return [i.as_in_context(ctx) for i, ctx in zip(slices, ctx_list)]
  
imports: import os
  import sys
  import hashlib
  import uuid
  import warnings
  import collections
  import weakref
  import requests
  import numpy
  from ..None import ndarray
  from ..util import is_np_shape, is_np_array, TemporaryDirectory
  from ..None import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: split_and_load(data, ctx_list, batch_axis, even_split) and returns: unknown, list