code: def propose(self) -> Optional[List[ShardingOption]]:
      if self._proposals and self._proposal_index < len(
          self._proposals
      ):
          proposal_indices = self._proposals[self._proposal_index]
          return [
              sharding_options[index]
              for index, sharding_options in zip(
                  proposal_indices,
                  self._sharding_options_by_fqn.values(),
              )
          ]
      else:
          return None
  
imports: import copy
  import itertools
  import logging
  from decimal import Decimal
  from typing import cast, Dict, List, Optional, Set, Tuple, Union
  import torch
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.planner.types import Enumerator, Perf, Proposer, ShardingOption, Topology
  from torchrec.distributed.planner.utils import BinarySearchPredicate, bytes_to_gb, prod
label_desc: Use image node_id 4 for calling the GridSearchProposer obj's underlying member method code with example usage: obj.propose() and returns: unknown, None