code: def _create_read_item_for_tensor(
      dest_index, dest_offsets, storage_index, storage_offsets, lengths
  ):
      return ReadItem(
          type=LoadItemType.TENSOR,
          dest_index=dest_index,
          dest_offsets=torch.Size(dest_offsets),
          storage_index=storage_index,
          storage_offsets=torch.Size(storage_offsets),
          lengths=torch.Size(lengths),
      )
  
imports: from typing import Any, cast, List
  import torch
  import torch.distributed
  from torch._utils import _get_device_module
  from torch.distributed._shard.metadata import ShardMetadata
  from torch.distributed._shard.sharded_tensor import ShardedTensor
  from torch.distributed._shard.sharded_tensor.metadata import TensorProperties
  from torch.distributed._tensor import DTensor
  from torch.distributed._tensor._utils import compute_local_shape_and_global_offset
  from torch.utils._pytree import tree_map_only
  from .metadata import BytesStorageMetadata, ChunkStorageMetadata, MetadataIndex, STATE_DICT_TYPE, STORAGE_TYPES, TensorStorageMetadata
  from .planner import LoadItemType, ReadItem, SavePlan, TensorWriteData, WriteItem, WriteItemType
  from .resharding import _check_shard_metadata_pair_overlap, _shards_get_overlap_region_wrt_saved_tensor
label_desc: Use image node_id 9 for calling a global function with example usage: _create_read_item_for_tensor(dest_index, dest_offsets, storage_index, storage_offsets, lengths) and returns: ReadItem