code: def _get_ckpt_name(self, checkpoints_path, tag, mp_placeholder=None):
      if mp_placeholder is not None:
          mp_rank_str = mp_placeholder
      else:
          mp_rank = (
              0
              if self.mpu is None
              else self.mpu.get_model_parallel_rank()
          )
          mp_rank_str = "{:02d}".format(mp_rank)
  
      ckpt_name = os.path.join(
          checkpoints_path,
          "mp_rank_" + mp_rank_str + "_model_states.pt",
      )
      return ckpt_name
  
imports: import torch
  import time
  import os
  from deepspeed import comm
  from deepspeed.utils.logging import log_dist
  from torch.nn.modules import Module
  from packaging import version
  from deepspeed.runtime.checkpoint_engine.torch_checkpoint_engine import TorchCheckpointEngine
  from deepspeed.utils.timer import SynchronizedWallClockTimer
  from ..runtime.state_dict_factory import SDLoaderFactory
  from ..runtime.weight_quantizer import WeightQuantization
  from ..module_inject import replace_transformer_layer, generic_injection
  from ..comm.comm import init_distributed
  from ..pipe import PipelineModule
  from ..moe.utils import has_moe_layers
  from ..module_inject import LinearAllreduce, LinearLayer, Normalize, ReplaceWithTensorSlicing
  from deepspeed.accelerator import get_accelerator
  from ..module_inject.policy import TransformerPolicy
  from ..module_inject.auto_tp import AutoTP
  from ..module_inject.replace_policy import generic_policies
  from ..module_inject.auto_tp_model_utils import build_bloom_alibi_tensor, build_mpt_atten_bias_tensor, build_mpt_alibi_tensor, get_alibi_mask
  from ..ops.transformer.inference.ds_attention import DeepSpeedSelfAttention
  from ..model_implementations.transformers.ds_transformer import DeepSpeedTransformerInference
  from torch import nn
label_desc: Use image node_id 17 for calling the InferenceEngine obj's underlying member method code with example usage: obj._get_ckpt_name(checkpoints_path, tag, mp_placeholder) and returns: ckpt_name