code: def sample_action(self, scores: torch.Tensor) -> rlt.ActorOutput:
      top_values, item_idxs = torch.topk(scores, self.k, dim=1)
      return rlt.ActorOutput(
          action=item_idxs, log_prob=torch.zeros(item_idxs.shape[0], 1)
      )
  
file_path: ReAgent/reagent/gym/policies/samplers/top_k_sampler.py
imports: import reagent.core.types
  import torch
  from reagent.gym.types import Sampler
label_desc: Use image node_id 2 for calling the TopKSampler obj's underlying member method code with example usage: obj.sample_action(scores) and returns: rlt