class_docstr: DefaultLoadPlanner that adds multiple features on top of LoadPlanner.
  
  In particular it adds the following:
  
  flatten_state_dict: Handle state_dict with nested dicts
  flatten_sharded_tensors: For FSDP in 2D parallel mode
class_docstr_tok: ["DefaultLoadPlanner","that","adds","multiple","features","on","top","of","LoadPlanner",".","In","particular","it","adds","the","following",":","flatten_state_dict",":","Handle","state_dict","with","nested","dicts","flatten_sharded_tensors",":","For","FSDP","in","2D","parallel","mode"]
code: def __init__(
      self,
      flatten_state_dict: bool = True,
      flatten_sharded_tensors: bool = True,
  ) -> None:
      self.flatten_state_dict = flatten_state_dict
      self.flatten_sharded_tensors = flatten_sharded_tensors
      self.original_state_dict = {}
      self.mappings = {}
  
imports: import dataclasses
  import io
  import logging
  import operator
  from collections import ChainMap
  from functools import reduce
  from typing import Any, cast, Dict, List, Tuple, Union
  import torch
  from torch.distributed._shard._utils import narrow_tensor_by_index
  from torch.distributed._tensor import DTensor
  from torch.distributed.checkpoint._dedup_tensors import dedup_tensors
  from torch.distributed.checkpoint._nested_dict import FLATTEN_MAPPING, flatten_state_dict
  from torch.distributed.checkpoint._sharded_tensor_utils import _flatten_sharded_tensors
  from torch.distributed.checkpoint._traverse import set_element
  from torch.distributed.checkpoint.metadata import BytesStorageMetadata, ChunkStorageMetadata, Metadata, MetadataIndex, STATE_DICT_TYPE, STORAGE_TYPES, TensorStorageMetadata
  from torch.distributed.checkpoint.planner import LoadPlan, LoadPlanner, ReadItem, SavePlan, SavePlanner, WriteItem, WriteItemType
  from torch.distributed.checkpoint.planner_helpers import _create_default_metadata_only_plan, _create_read_items, _create_write_items, _init_state_dict
  from torch.distributed.checkpoint.utils import find_state_dict_object
label_desc: Use image node_id 1 to create a new DefaultLoadPlanner object from inherited base classes: LoadPlanner with example: obj = DefaultLoadPlanner(flatten_state_dict, flatten_sharded_tensors)