class_docstr: Return the highest scoring action.
class_docstr_tok: ["Return","the","highest","scoring","action","."]
code: def log_prob(
      self, scores: torch.Tensor, action: torch.Tensor
  ) -> torch.Tensor:
      greedy_indices = self._get_greedy_indices(scores)
      match = greedy_indices == action.argmax(-1)
      lp = torch.zeros(scores.shape[0], device=scores.device).float()
      lp[match] = -float("inf")
      return lp
  
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 3 for calling the GreedyActionSampler obj's underlying member method code with example usage: obj.log_prob(scores, action) and returns: lp