code: def _load_hp_checkpoint_state(self, checkpoint_dir):
      checkpoint_dir = os.path.join(checkpoint_dir, "zero")
      tp_rank = bwc_tensor_model_parallel_rank(mpu=self.mpu)
      tp_world_size = self.mpu.get_slice_parallel_world_size()
  
      for i, _ in enumerate(self.optimizer.param_groups):
          for lp in self.bf16_groups[i]:
              if lp._hp_mapping is not None:
                  # print(f"Loading {self.param_names[lp]} {tp_rank=} {tp_world_size=}")
                  lp.load_hp_checkpoint_state(
                      os.path.join(
                          checkpoint_dir, self.param_names[lp]
                      ),
                      tp_rank,
                      tp_world_size,
                  )
  
imports: from collections import OrderedDict
  import torch
  import sys
  import os
  from deepspeed import comm
  from deepspeed.runtime.constants import PIPE_REPLICATED
  from deepspeed.ops.op_builder import UtilsBuilder
  from deepspeed.runtime import ZeROOptimizer
  from packaging import version
  from deepspeed.git_version_info import version
  from deepspeed.runtime.utils import get_global_norm_of_tensors, clip_tensors_by_global_norm, DummyOptim, align_dense_tensors, all_gather_dp_groups, bwc_tensor_model_parallel_rank, is_model_parallel_parameter, see_memory_usage
  from deepspeed.utils import link_hp_params, fragment_address
  from deepspeed.checkpoint import enable_universal_checkpoint
  from deepspeed.checkpoint.constants import DS_VERSION, PARTITION_COUNT, BASE_OPTIMIZER_STATE, SINGLE_PARTITION_OF_FP32_GROUPS, CLIP_GRAD, GROUP_PADDINGS, PARAM_SLICE_MAPPINGS
label_desc: Use image node_id 25 for calling the BF16_Optimizer obj's underlying member method code with example usage: obj._load_hp_checkpoint_state(checkpoint_dir) without return types