code: def get_shared_mem(
      shape,
      dtype=np.float32,
      strides=None,
      order="C",
      stream=0,
      portable=False,
      wc=True,
  ):
      """Return shared memory between GPU and CPU. Similar to numpy.zeros
  
      Parameters
      ----------
      shape : ndarray.shape
          Size of shared memory allocation
      dtype : cupy.dtype or numpy.dtype
          Data type of allocation
      strides: int or None
      order: char
      stream : int
          Stream number (0 for default)
      portable : bool
      wc : bool
      """
  
      return cuda.mapped_array(
          shape,
          dtype=dtype,
          strides=strides,
          order=order,
          stream=stream,
          portable=portable,
          wc=wc,
      )
  
file_path: cusignal/python/cusignal/utils/arraytools.py
imports: import cupy
  import numpy
  from numba import cuda
label_desc: Use image node_id 2 for calling a global function with example usage: get_shared_mem(shape, dtype, strides, order, stream, portable, wc) and returns: cuda