code: def main():
      # NeMo Model config
      cfg = modelPT.NemoConfig(name="Custom QuartzNet")
  
      # Generate default asr model config
      builder = configs.EncDecCTCModelConfigBuilder(
          name="quartznet_15x5"
      )
  
      # set model global values
      builder.set_labels(LABELS)
      builder.set_optim(cfg=optim_cfg, sched_cfg=sched_cfg)
  
      model_cfg = builder.build()
  
      # set the model config to the NeMo Model
      cfg.model = model_cfg
  
      # Update values
      # MODEL UPDATES
      # train ds
      model_cfg.train_ds.manifest_filepath = ""
  
      # validation ds
      model_cfg.validation_ds.manifest_filepath = ""
  
      # Trainer config
      cfg.trainer.devices = 1
      cfg.trainer.max_epochs = 5
  
      # Exp Manager config
      cfg.exp_manager.name = cfg.name
  
      # Note usage of asdict
      trainer = pl.Trainer(**asdict(cfg.trainer))
      exp_manager(trainer, asdict(cfg.exp_manager))
      asr_model = EncDecCTCModel(cfg=cfg.model, trainer=trainer)
  
      trainer.fit(asr_model)
  
imports: from dataclasses import asdict
  import pytorch_lightning
  from nemo.collections.asr.models import EncDecCTCModel, configs
  from nemo.core.config import modelPT, optimizers, schedulers
  from nemo.utils.exp_manager import exp_manager
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types