code: def get_probs(
      self, decoder_out: Tuple[Tensor, Dict[str, Tensor]]
  ) -> Tuple[Tensor, Tensor, Tensor]:
      model_out, output_dict = decoder_out
      if self.model_output_logprob:
          probs = model_out.exp()
          max_probs, idx = probs.max(dim=-1)
      else:
          max_probs, idx = model_out.max(dim=-1)
      return idx, max_probs, model_out
  
file_path: pytext/pytext/models/seq_models/projection_layers.py
imports: from typing import Dict, Optional, Tuple
  import torch
  import torch.nn.functional
  from pytext.models.seq_models.utils import Linear
  from torch import nn, Tensor
  from .attention import DecoupledMultiheadAttention
  from .utils import verify_encoder_out
label_desc: Use image node_id 3 for calling the DecoupledDecoderHead obj's underlying member method code with example usage: obj.get_probs(decoder_out) and returns: idx,  max_probs,  model_out