code: def slice_with_int_dask_array(x, idx, offset, x_size, axis):
      """Chunk function of `slice_with_int_dask_array_on_axis`.
      Slice one chunk of x by one chunk of idx.
  
      Parameters
      ----------
      x: ndarray, any dtype, any shape
          i-th chunk of x
      idx: ndarray, ndim=1, dtype=any integer
          j-th chunk of idx (cartesian product with the chunks of x)
      offset: ndarray, shape=(1, ), dtype=int64
          Index of the first element along axis of the current chunk of x
      x_size: int
          Total size of the x da.Array along axis
      axis: int
          normalized axis to take elements from (0 <= axis < x.ndim)
  
      Returns
      -------
      x sliced along axis, using only the elements of idx that fall inside the
      current chunk.
      """
      from dask.array.utils import asarray_safe, meta_from_array
  
      idx = asarray_safe(idx, like=meta_from_array(x))
  
      # Needed when idx is unsigned
      idx = idx.astype(np.int64)
  
      # Normalize negative indices
      idx = np.where(idx < 0, idx + x_size, idx)
  
      # A chunk of the offset dask Array is a numpy array with shape (1, ).
      # It indicates the index of the first element along axis of the current
      # chunk of x.
      idx = idx - offset
  
      # Drop elements of idx that do not fall inside the current chunk of x
      idx_filter = (idx >= 0) & (idx < x.shape[axis])
      idx = idx[idx_filter]
  
      # np.take does not support slice indices
      # return np.take(x, idx, axis)
      return x[
          tuple(
              idx if i == axis else slice(None) for i in range(x.ndim)
          )
      ]
  
imports: from __future__ import annotations
  import contextlib
  from collections.abc import Container, Iterable, Sequence
  from functools import wraps
  from numbers import Integral
  import numpy
  from tlz import concat
  from dask.core import flatten
label_desc: Use image node_id 13 for calling a global function with example usage: slice_with_int_dask_array(x, idx, offset, x_size, axis) and returns: x