class_docstr: Return the highest scoring action.
class_docstr_tok: ["Return","the","highest","scoring","action","."]
code: def sample_action(self, scores: torch.Tensor) -> rlt.ActorOutput:
      batch_size, num_actions = scores.shape
      raw_action = self._get_greedy_indices(scores)
      action = F.one_hot(raw_action, num_actions)
      assert action.shape == (batch_size, num_actions)
      return rlt.ActorOutput(
          action=action,
          log_prob=torch.zeros_like(raw_action, dtype=torch.float),
      )
  
imports: import reagent.core.types
  import torch
  import torch.nn.functional
  from reagent.gym.types import Sampler
  from reagent.models.dqn import INVALID_ACTION_CONSTANT
label_desc: Use image node_id 2 for calling the GreedyActionSampler obj's underlying member method code with example usage: obj.sample_action(scores) and returns: rlt