code: def unpack_bin(binary, dtype, endianness="L"):
      """
      Unpack binary file.
      If endianness is big-endian, it my be converted
      to little endian for NVIDIA GPU compatibility.
  
      Parameters
      ----------
      binary : ndarray
          The binary array to be unpack.
      dtype : data-type, optional
          Any object that can be interpreted as a numpy data type.
      endianness : {'L', 'B'}, optional
          Data set byte order
  
      Returns
      -------
      out : ndarray
          An 1-dimensional array containing unpacked binary data.
  
      """
  
      if endianness != "L" and endianness != "B" and endianness != "N":
          raise ValueError("'endianness' should be 'L' or 'B'")
  
      out = _unpack(binary, dtype, endianness)
  
      return out
  
file_path: cusignal/python/cusignal/io/reader.py
imports: import json
  import re
  import cupy
  import numpy
  from ._reader_cuda import _unpack
label_desc: Use image node_id 3 for calling a global function with example usage: unpack_bin(binary, dtype, endianness) and returns: out