code: def get_module_to_default_sharders() -> (
      Dict[Type[nn.Module], ModuleSharder[nn.Module]]
  ):
      return {
          sharder.module_type: sharder
          for sharder in get_default_sharders()
      }
  
imports: import math
  import warnings
  from typing import Callable, cast, Dict, List, Optional, Tuple, Type
  import torch
  from torch import distributed, nn
  from torchrec.distributed.comm import get_local_size
  from torchrec.distributed.embedding import EmbeddingCollectionSharder
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.embeddingbag import EmbeddingBagCollectionSharder
  from torchrec.distributed.fp_embeddingbag import FeatureProcessedEmbeddingBagCollectionSharder
  from torchrec.distributed.fused_embeddingbag import FusedEmbeddingBagCollectionSharder
  from torchrec.distributed.mc_embedding import ManagedCollisionEmbeddingCollectionSharder
  from torchrec.distributed.mc_embeddingbag import ManagedCollisionEmbeddingBagCollectionSharder
  from torchrec.distributed.planner.constants import MIN_CW_DIM
  from torchrec.distributed.quant_embedding import QuantEmbeddingCollectionSharder
  from torchrec.distributed.quant_embeddingbag import QuantEmbeddingBagCollectionSharder
  from torchrec.distributed.types import EmbeddingModuleShardingPlan, EnumerableShardingSpec, ModuleSharder, ParameterSharding, ShardingType, ShardMetadata
  from torchrec.distributed.utils import none_throws
label_desc: Use image node_id 2 for calling a global function with example usage: get_module_to_default_sharders() and returns: unknown