code: def get_filename(
      model_name,
      batch_size,
      prompt_len,
      gen_len,
      cpu_offload,
      disk_offload,
      num_nodes,
      num_gpus_per_node,
      kv_offload,
      weight_quantize,
  ):
      simple_name = model_name.split("/")[-1]
      filename = "ds-"
      filename += f"{simple_name}-bs{batch_size}-prompt{prompt_len}-gen{gen_len}-"
      filename += f"n{num_nodes}x{num_gpus_per_node}-"
      if cpu_offload:
          filename += "cpu"
      elif disk_offload:
          filename += "disk"
      else:
          filename += "gpu"
      if kv_offload:
          filename += "-kv_offload"
      if weight_quantize:
          filename += "-w_quant"
  
      return filename
  
file_path: deepspeedexamples/inference/huggingface/zero_inference/utils.py
imports: import torch
  import time
label_desc: Use image node_id 10 for calling a global function with example usage: get_filename(model_name, batch_size, prompt_len, gen_len, cpu_offload, disk_offload, num_nodes, num_gpus_per_node, kv_offload, weight_quantize) and returns: filename