class_docstr: This worker will take tensors from the request queue, do some computation,
  and then return the result back in the response queue.
class_docstr_tok: ["This","worker","will","take","tensors","from","the","request","queue",",","do","some","computation",",","and","then","return","the","result","back","in","the","response","queue","."]
code: def copy_data(self, input_buffer, data, copy_event, copy_sem):
      data = data.pin_memory()
      with torch.cuda.stream(self.h2d_stream):
          input_buffer.copy_(data, non_blocking=True)
          copy_event.record()
          copy_sem.release()
  
imports: import argparse
  import asyncio
  import os.path
  import subprocess
  import threading
  import time
  from concurrent.futures import ThreadPoolExecutor
  from queue import Empty
  import numpy
  import pandas
  import torch
  import torch.multiprocessing
label_desc: Use image node_id 4 for calling the BackendWorker obj's underlying member method code with example usage: obj.copy_data(input_buffer, data, copy_event, copy_sem) without return types