class_docstr: Base class for encoder decoder RNNT-based models with auxiliary CTC decoder/loss and subword tokenization.
class_docstr_tok: ["Base","class","for","encoder","decoder","RNNT-based","models","with","auxiliary","CTC","decoder\/loss","and","subword","tokenization","."]
docstr: This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud.
  
  Returns:
      List of available pre-trained models.
docstr_tok: ["This","method","returns","a","list","of","pre-trained","model","which","can","be","instantiated","directly","from","NVIDIA","'s","NGC","cloud",".","Returns",":","List","of","available","pre-trained","models","."]
code: def list_available_models(cls) -> List[PretrainedModelInfo]:
      """
      This method returns a list of pre-trained model which can be instantiated directly from NVIDIA's NGC cloud.
  
      Returns:
          List of available pre-trained models.
      """
      results = []
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_en_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_en_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_en_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_en_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_de_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_de_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_de_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_de_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_it_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_it_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_it_fastconformer_hybrid_large_pc/versions/1.20.0/files/stt_it_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_es_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_es_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_es_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_es_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_hr_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_hr_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_hr_fastconformer_hybrid_large_pc/versions/1.21.0/files/FastConformer-Hybrid-Transducer-CTC-BPE-v256-averaged.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_ua_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_ua_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_ua_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_ua_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_pl_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_pl_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_pl_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_pl_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_by_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_by_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_by_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_by_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_ru_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_ru_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_ru_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_ru_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_fr_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_fr_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_fr_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_fr_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_multilingual_fastconformer_hybrid_large_pc_blend_eu",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_multilingual_fastconformer_hybrid_large_pc_blend_eu",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_multilingual_fastconformer_hybrid_large_pc_blend_eu/versions/1.21.0/files/stt_multilingual_fastconformer_hybrid_large_pc_blend_eu.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_multilingual_fastconformer_hybrid_large_pc",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_multilingual_fastconformer_hybrid_large_pc",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_multilingual_fastconformer_hybrid_large_pc/versions/1.21.0/files/stt_multilingual_fastconformer_hybrid_large_pc.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_en_fastconformer_hybrid_large_streaming_80ms",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_en_fastconformer_hybrid_large_streaming_80ms",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_en_fastconformer_hybrid_large_streaming_80ms/versions/1.20.0/files/stt_en_fastconformer_hybrid_large_streaming_80ms.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_en_fastconformer_hybrid_large_streaming_480ms",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_en_fastconformer_hybrid_large_streaming_480ms",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_en_fastconformer_hybrid_large_streaming_480ms/versions/1.20.0/files/stt_en_fastconformer_hybrid_large_streaming_480ms.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_en_fastconformer_hybrid_large_streaming_1040ms",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_en_fastconformer_hybrid_large_streaming_1040ms",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_en_fastconformer_hybrid_large_streaming_1040ms/versions/1.20.0/files/stt_en_fastconformer_hybrid_large_streaming_1040ms.nemo",
      )
      results.append(model)
  
      model = PretrainedModelInfo(
          pretrained_model_name="stt_en_fastconformer_hybrid_large_streaming_multi",
          description="For details about this model, please visit https://ngc.nvidia.com/catalog/models/nvidia:nemo:stt_en_fastconformer_hybrid_large_streaming_multi",
          location="https://api.ngc.nvidia.com/v2/models/nvidia/nemo/stt_en_fastconformer_hybrid_large_streaming_multi/versions/1.20.0/files/stt_en_fastconformer_hybrid_large_streaming_multi.nemo",
      )
      results.append(model)
  
      return results
  
imports: import copy
  import os
  from typing import Dict, List, Optional, Union
  import torch
  from omegaconf import DictConfig, ListConfig, OmegaConf, open_dict
  from pytorch_lightning import Trainer
  from nemo.collections.asr.data import audio_to_text_dataset
  from nemo.collections.asr.data.audio_to_text_dali import AudioToBPEDALIDataset
  from nemo.collections.asr.data.audio_to_text_lhotse import LhotseSpeechToTextBpeDataset
  from nemo.collections.asr.losses.ctc import CTCLoss
  from nemo.collections.asr.losses.rnnt import RNNTLoss
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.models.hybrid_rnnt_ctc_models import EncDecHybridRNNTCTCModel
  from nemo.collections.asr.parts.mixins import ASRBPEMixin
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCBPEDecoding, CTCBPEDecodingConfig
  from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTBPEDecoding, RNNTBPEDecodingConfig
  from nemo.collections.common.data.lhotse import get_lhotse_dataloader_from_config
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 6 for calling the EncDecHybridRNNTCTCBPEModel obj's underlying member method code with example usage: obj.list_available_models(cls) and returns: results