code: def _get_docs_value(self, docs: rlt.DocList) -> torch.Tensor:
      # Multiplying by the mask to filter out selected padding items.
      value = docs.value * docs.mask
      if self.single_selection:
          value = F.softmax(value, dim=1)
      return value
  
imports: import enum
  import logging
  from typing import Optional
  import reagent.core.parameters
  import reagent.core.types
  import torch
  import torch.nn.functional
  from reagent.core.dataclasses import field
  from reagent.optimizer import Optimizer__Union, SoftUpdate
  from reagent.training.reagent_lightning_module import ReAgentLightningModule
  from reagent.training.rl_trainer_pytorch import RLTrainerMixin
label_desc: Use image node_id 7 for calling the SlateQTrainer obj's underlying member method code with example usage: obj._get_docs_value(docs) and returns: value