docstr: Gets the q values from the model and target networks
docstr_tok: ["Gets","the","q","values","from","the","model","and","target","networks"]
code: def _get_unmasked_q_values(
      self, q_network, state: rlt.FeatureData, slate: rlt.DocList
  ) -> torch.Tensor:
      """Gets the q values from the model and target networks"""
      batch_size, slate_size, _ = slate.float_features.shape
      # TODO: Probably should create a new model type
      return q_network(
          state.repeat_interleave(slate_size, dim=0),
          slate.as_feature_data(),
      ).view(batch_size, slate_size)
  
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 4 for calling the SlateQTrainer obj's underlying member method code with example usage: obj._get_unmasked_q_values(q_network, state, slate) and returns: q_network