class_docstr: Postprocess raw prediction of the model (logits) to a list of words using CTC decoding
  
  Args:
  ----
      vocab: string containing the ordered sequence of supported characters
class_docstr_tok: ["Postprocess","raw","prediction","of","the","model","(","logits",")","to","a","list","of","words","using","CTC","decoding","Args",":","--","--","vocab",":","string","containing","the","ordered","sequence","of","supported","characters"]
docstr: Performs decoding of raw output with CTC and decoding of CTC predictions
  with label_to_idx mapping dictionnary
  
  Args:
  ----
      logits: raw output of the model, shape (N, C + 1, seq_len)
  
  Returns:
  -------
      A tuple of 2 lists: a list of str (words) and a list of float (probs)
docstr_tok: ["Performs","decoding","of","raw","output","with","CTC","and","decoding","of","CTC","predictions","with","label_to_idx","mapping","dictionnary","Args",":","--","--","logits",":","raw","output","of","the","model",",","shape","(","N",",","C","+","1",",","seq_len",")","Returns",":","--","--","--","-","A","tuple","of","2","lists",":","a","list","of","str","(","words",")","and","a","list","of","float","(","probs",")"]
code: def __call__(self, logits: torch.Tensor) -> List[Tuple[str, float]]:
      """Performs decoding of raw output with CTC and decoding of CTC predictions
      with label_to_idx mapping dictionnary
  
      Args:
      ----
          logits: raw output of the model, shape (N, C + 1, seq_len)
  
      Returns:
      -------
          A tuple of 2 lists: a list of str (words) and a list of float (probs)
  
      """
      # Decode CTC
      return self.ctc_best_path(
          logits=logits, vocab=self.vocab, blank=len(self.vocab)
      )
  
imports: from copy import deepcopy
  from itertools import groupby
  from typing import Any, Callable, Dict, List, Optional, Tuple
  import torch
  from torch import nn
  from torch.nn import functional
  from doctr.datasets import VOCABS, decode_sequence
  from ...classification import mobilenet_v3_large_r, mobilenet_v3_small_r, vgg16_bn_r
  from ...utils.pytorch import load_pretrained_params
  from ..core import RecognitionModel, RecognitionPostProcessor
label_desc: Use image node_id 2 for calling the CTCPostProcessor obj's underlying member method code with example usage: obj.__call__(logits) and returns: self