docstr: Given a sequence logits over labels, get the best path string
  
  Args:
      logits (Tensor): Logit tensors. Shape `[num_seq, num_label]`.
  
  Returns:
      str: The resulting transcript
docstr_tok: ["Given","a","sequence","logits","over","labels",",","get","the","best","path","string","Args",":","logits","(","Tensor",")",":","Logit","tensors",".","Shape","`","[","num_seq",",","num_label","]","`",".","Returns",":","str",":","The","resulting","transcript"]
code: def forward(self, logits: torch.Tensor) -> str:
      """Given a sequence logits over labels, get the best path string
  
      Args:
          logits (Tensor): Logit tensors. Shape `[num_seq, num_label]`.
  
      Returns:
          str: The resulting transcript
      """
      best_path = torch.argmax(logits, dim=-1)  # [num_seq,]
      best_path = torch.unique_consecutive(best_path, dim=-1)
      hypothesis = []
      for i in best_path:
          if i != self.blank:
              hypothesis.append(self.labels[i])
      return "".join(hypothesis)
  
file_path: audio/test/integration_tests/conftest.py
imports: import os
  import shutil
  import pytest
  import torch
  import torchaudio
label_desc: Use image node_id 2 for calling the GreedyCTCDecoder obj's underlying member method code with example usage: obj.forward(logits) and returns: str