code: def clf_to_bytes(
      model: torch.Tensor, clfs: Union[float, torch.Tensor]
  ) -> torch.Tensor:
      # evaluate affine model AX + B
      return (model[:, 0] * clfs + model[:, 1]).to(torch.int64)
  
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 11 for calling the EmbeddingOffloadScaleupProposer obj's underlying member method code with example usage: obj.clf_to_bytes(model, clfs) and returns: unknown