code: def get_eval_ds_config(offload, dtype, stage=0):
      device = "cpu" if offload else "none"
      if dtype == "fp16":
          data_type = "fp16"
          dtype_config = {
              "enabled": True,
          }
      elif dtype == "bf16":
          data_type = "bfloat16"
          dtype_config = {"enabled": True}
      zero_opt_dict = {
          "stage": stage,
          "stage3_param_persistence_threshold": 1e4,
          "offload_param": {"device": device},
          "memory_efficient_linear": False,
      }
      return {
          "train_batch_size": GLOBAL_BATCH_SIZE,
          "train_micro_batch_size_per_gpu": MICRO_BATCH_SIZE,
          "steps_per_print": 10,
          "zero_optimization": zero_opt_dict,
          data_type: dtype_config,
          "gradient_clipping": 1.0,
          "prescale_gradients": False,
          "wall_clock_breakdown": False,
      }
  
label_desc: Use image node_id 2 for calling a global function with example usage: get_eval_ds_config(offload, dtype, stage) and returns: dict