code: def normalize_chunks(self, size, chunks):
      if isinstance(chunks, int):
          # *chunks* is the chunksize
          return cuda.as_cuda_array(
              cp.arange(start=0, stop=size, step=chunks)
          ).view("int64")
      else:
          # *chunks* is an array of chunk leading offset
          return cuda.as_cuda_array(cp.asarray(chunks)).view("int64")
  
imports: import functools
  from typing import Any, Dict
  import cupy
  from numba import cuda
  from numba.core.utils import pysignature
  import cudf
  from cudf import _lib
  from cudf.core.buffer import acquire_spill_lock
  from cudf.core.column import column
  from cudf.utils import utils
  from cudf.utils._numba import _CUDFNumbaConfig
  from cudf.utils.docutils import docfmt_partial
label_desc: Use image node_id 3 for calling the ApplyChunksCompiler obj's underlying member method code with example usage: obj.normalize_chunks(size, chunks) and returns: cuda, cuda