code: def see_memory_usage(message):
      # Print message except when distributed but not rank 0
      logger.info(message)
      logger.info(
          "Memory Allocated %s GigaBytes ",
          get_accelerator().memory_allocated() / (1024 * 1024 * 1024),
      )
      logger.info(
          "Max Memory Allocated %s GigaBytes",
          get_accelerator().max_memory_allocated()
          / (1024 * 1024 * 1024),
      )
      logger.info(
          "Cache Allocated %s GigaBytes",
          get_accelerator().memory_cached() / (1024 * 1024 * 1024),
      )
      logger.info(
          "Max cache Allocated %s GigaBytes",
          get_accelerator().max_memory_cached() / (1024 * 1024 * 1024),
      )
  
imports: import torch
  from deepspeed.pt.deepspeed_linear import LinearModuleForZeroStage3
  from deepspeed.pt.log_utils import logger
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 1 for calling a global function with example usage: see_memory_usage(message) without return types