code: def asr_model_ctc_bpe_config(test_data_dir):
      preprocessor = {
          "_target_": "nemo.collections.asr.modules.AudioToMelSpectrogramPreprocessor"
      }
      encoder = {
          "_target_": "nemo.collections.asr.modules.ConvASREncoder",
          "feat_in": 64,
          "activation": "relu",
          "conv_mask": True,
          "jasper": [
              {
                  "filters": 1024,
                  "repeat": 1,
                  "kernel": [1],
                  "stride": [1],
                  "dilation": [1],
                  "dropout": 0.0,
                  "residual": False,
                  "separable": True,
                  "se": True,
                  "se_context_size": -1,
              }
          ],
      }
  
      decoder = {
          "_target_": "nemo.collections.asr.modules.ConvASRDecoder",
          "feat_in": 1024,
          "num_classes": -1,
          "vocabulary": None,
      }
  
      tokenizer = {
          "dir": str(
              Path(test_data_dir) / "asr/tokenizers/an4_wpe_128"
          ),
          "type": "wpe",
      }
  
      model_config = DictConfig(
          {
              "preprocessor": DictConfig(preprocessor),
              "encoder": DictConfig(encoder),
              "decoder": DictConfig(decoder),
              "tokenizer": DictConfig(tokenizer),
          }
      )
      return model_config
  
imports: import tempfile
  from pathlib import Path
  import pytest
  import torch.nn
  from omegaconf import DictConfig
  from nemo.collections.asr.models import ASRModel, EncDecCTCModelBPE, EncDecRNNTBPEModel
  from nemo.collections.asr.models.hybrid_asr_tts_models import ASRWithTTSModel
  from nemo.collections.asr.parts.submodules.batchnorm import FusedBatchNorm1d
  from nemo.collections.tts.models import FastPitchModel
label_desc: Use image node_id 7 for calling a global function with example usage: asr_model_ctc_bpe_config(test_data_dir) and returns: model_config