code: def load_plain_tensors(checkpoint_dir: str):
      """Load checkpoint tensors without any sharding.
  
      NOTE: common state dict is NOT included."""
      sharded_state_dict = load_tensors_metadata(checkpoint_dir)
      # Don't validate integrity because shards will be overlapped
      # if world_size > 1 (all processes load whole tensors)
      return load(
          sharded_state_dict,
          checkpoint_dir,
          validate_access_integrity=False,
      )
  
imports: import logging
  import os
  from collections import Counter, defaultdict
  from itertools import chain
  from pathlib import Path
  from typing import Iterable, List, Optional, Tuple, Union
  import numpy
  import torch
  from .core import CheckpointingConfig, maybe_load_config, save_config
  from .dict_utils import dict_list_map_inplace, diff, extract_matching_values, map_reduce, merge, nested_values
  from .mapping import CheckpointingException, ShardedObject, ShardedStateDict, ShardedTensor, ShardedTensorFactory, StateDict, apply_factories, apply_factory_merges, is_main_replica
  from .strategies.base import LoadCommonStrategy, LoadShardedStrategy, SaveCommonStrategy, SaveShardedStrategy, StrategyAction, get_default_strategy
  from .utils import extract_sharded_tensors, extract_sharded_tensors_or_nonpersistent
label_desc: Use image node_id 6 for calling a global function with example usage: load_plain_tensors(checkpoint_dir) and returns: load