code: def dorefa_clamp_round_output(
      target: torch.Tensor, target_space: QuantizationTargetSpace
  ) -> Any:
      target = torch.clamp(target, 0, 1)
      return ClampRound.apply(target, target_space)
  
imports: from typing import Any
  import torch
  from .target_space import PruningTargetSpace, QuantizationTargetSpace, TargetSpace, TargetType
label_desc: Use image node_id 2 for calling the DoferaGradClampRound obj's underlying member method code with example usage: obj.dorefa_clamp_round_output(target, target_space) and returns: ClampRound