code: def _use_resources(n_procs, mem_gb):
      """
      Function to execute multiple use_gb_ram functions in parallel
      """
      import os
      import sys
      import psutil
      from multiprocessing import Pool
      from nipype import logging
      from nipype.utils.profiler import _use_cpu
  
      iflogger = logging.getLogger("nipype.interface")
  
      # Getsize of one character string
      BSIZE = sys.getsizeof("  ") - sys.getsizeof(" ")
      BOFFSET = sys.getsizeof("")
      _GB = 1024.0**3
  
      def _use_gb_ram(mem_gb):
          """A test function to consume mem_gb GB of RAM"""
          num_bytes = int(mem_gb * _GB)
          # Eat mem_gb GB of memory for 1 second
          gb_str = " " * ((num_bytes - BOFFSET) // BSIZE)
          assert sys.getsizeof(gb_str) == num_bytes
          return gb_str
  
      # Measure the amount of memory this process already holds
      p = psutil.Process(os.getpid())
      mem_offset = p.memory_info().rss / _GB
      big_str = _use_gb_ram(mem_gb - mem_offset)
      _use_cpu(5)
      mem_total = p.memory_info().rss / _GB
      del big_str
      iflogger.info(
          "[%d] Memory offset %0.2fGB, total %0.2fGB",
          os.getpid(),
          mem_offset,
          mem_total,
      )
  
      if n_procs > 1:
          pool = Pool(n_procs)
          pool.map(_use_cpu, range(n_procs))
      return True
  
imports: import os
  import numpy
  import threading
  from time import time
  from ..None import config, logging
label_desc: Use image node_id 7 for calling a global function with example usage: _use_resources(n_procs, mem_gb) and returns: True, gb_str