class_docstr: Implementation of 51 Categorical DQN (C51)
  
  See https://arxiv.org/abs/1707.06887 for details
class_docstr_tok: ["Implementation","of","51","Categorical","DQN","(","C51",")","See","https",":","\/\/arxiv.org\/abs\/1707.06887","for","details"]
code: def boost_rewards(
      self, rewards: torch.Tensor, actions: torch.Tensor
  ) -> torch.Tensor:
      # Apply reward boost if specified
      reward_boosts = torch.sum(
          actions.float() * self.reward_boosts, dim=1, keepdim=True
      )
      return rewards + reward_boosts
  
file_path: ReAgent/reagent/training/c51_trainer.py
imports: from typing import List
  import reagent.core.types
  import torch
  from reagent.core.configuration import resolve_defaults
  from reagent.core.dataclasses import field
  from reagent.core.parameters import RLParameters
  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 C51Trainer obj's underlying member method code with example usage: obj.boost_rewards(rewards, actions) and returns: unknown