code: def add_dummy_padding(x, depth, boundary):
      """
      Pads an array which has 'none' as the boundary type.
      Used to simplify trimming arrays which use 'none'.
  
      >>> import dask.array as da
      >>> x = da.arange(6, chunks=3)
      >>> add_dummy_padding(x, {0: 1}, {0: 'none'}).compute()  # doctest: +NORMALIZE_WHITESPACE
      array([..., 0, 1, 2, 3, 4, 5, ...])
      """
      for k, v in boundary.items():
          d = depth.get(k, 0)
          if v == "none" and d > 0:
              empty_shape = list(x.shape)
              empty_shape[k] = d
  
              empty_chunks = list(x.chunks)
              empty_chunks[k] = (d,)
  
              empty = empty_like(
                  getattr(x, "_meta", x),
                  shape=empty_shape,
                  chunks=empty_chunks,
                  dtype=x.dtype,
              )
  
              out_chunks = list(x.chunks)
              ax_chunks = list(out_chunks[k])
              ax_chunks[0] += d
              ax_chunks[-1] += d
              out_chunks[k] = tuple(ax_chunks)
  
              x = concatenate([empty, x, empty], axis=k)
              x = x.rechunk(out_chunks)
      return x
  
imports: from __future__ import annotations
  import warnings
  from numbers import Integral, Number
  import numpy
  from tlz import concat, get, partial
  from tlz.curried import map
  from dask.array import chunk
  from dask.array.core import Array, concatenate, map_blocks, unify_chunks
  from dask.array.creation import empty_like, full_like
  from dask.array.numpy_compat import normalize_axis_tuple
  from dask.base import tokenize
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import ArrayOverlapLayer
  from dask.utils import derived_from
label_desc: Use image node_id 14 for calling a global function with example usage: add_dummy_padding(x, depth, boundary) and returns: x