class_docstr: KL-Divergence metric based on pre-trained PASST classifier on AudioSet.
  
  From: PaSST: Efficient Training of Audio Transformers with Patchout
  Paper: https://arxiv.org/abs/2110.05069
  Implementation: https://github.com/kkoutini/PaSST
  
  Follow instructions from the github repo:
  ```
  pip install 'git+https://github.com/kkoutini/passt_hear21@0.0.19#egg=hear21passt'
  ```
  
  Args:
      pretrained_length (float, optional): Audio duration used for the pretrained model.
class_docstr_tok: ["KL-Divergence","metric","based","on","pre-trained","PASST","classifier","on","AudioSet",".","From",":","PaSST",":","Efficient","Training","of","Audio","Transformers","with","Patchout","Paper",":","https",":","\/\/arxiv.org\/abs\/2110.05069","Implementation",":","https",":","\/\/github.com\/kkoutini\/PaSST","Follow","instructions","from","the","github","repo",":","``","`","pip","install","'git+https",":","\/\/github.com\/kkoutini\/passt_hear21","@","0.0.19","#","egg=hear21passt'","``","`","Args",":","pretrained_length","(","float",",","optional",")",":","Audio","duration","used","for","the","pretrained","model","."]
docstr: Run the pretrained model and get the predictions.
docstr_tok: ["Run","the","pretrained","model","and","get","the","predictions","."]
code: def _get_model_preds(self, wav: torch.Tensor) -> torch.Tensor:
      """Run the pretrained model and get the predictions."""
      assert (
          wav.dim() == 3
      ), f"Unexpected number of dims for preprocessed wav: {wav.shape}"
      wav = wav.mean(dim=1)
      # PaSST is printing a lot of garbage that we are not interested in
      with open(os.devnull, "w") as f, contextlib.redirect_stdout(f):
          with torch.no_grad(), _patch_passt_stft():
              logits = self.model(wav.to(self.device))
              probs = torch.softmax(logits, dim=-1)
              return probs
  
imports: import contextlib
  from functools import partial
  import logging
  import os
  import typing
  import torch
  import torchmetrics
  from ..data.audio_utils import convert_audio
label_desc: Use image node_id 5 for calling the PasstKLDivergenceMetric obj's underlying member method code with example usage: obj._get_model_preds(wav) and returns: probs