class_docstr: ``torch.nn.Module``-based feature extraction pipeline.
  
  Args:
      pipeline (torch.nn.Module): module that implements feature extraction logic.
class_docstr_tok: ["``","torch.nn.Module","``","-based","feature","extraction","pipeline",".","Args",":","pipeline","(","torch.nn.Module",")",":","module","that","implements","feature","extraction","logic","."]
code: def __init__(self, pipeline: torch.nn.Module) -> None:
      super().__init__()
      self.pipeline = pipeline
  
imports: import json
  import math
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from functools import partial
  from typing import Callable, List, Tuple
  import torch
  import torchaudio
  from torchaudio._internal import module_utils
  from torchaudio.models import emformer_rnnt_base, RNNT, RNNTBeamSearch
label_desc: Use image node_id 1 to create a new _ModuleFeatureExtractor object from inherited base classes: torch.nn, _FeatureExtractor with example: obj = _ModuleFeatureExtractor(pipeline)