code: def from_config_dict(cls, config=None):
      _config = {} if config is None else config
      return NoisyOverlapAugment(
          _config.get("rate", _DEFAULTS["rate"]),
          _config.get(
              "mixing_noise_rate", _DEFAULTS["mixing_noise_rate"]
          ),
          _config.get("noise_path", _DEFAULTS["noise_path"]),
          _config.get("noise_snr_min", _DEFAULTS["noise_snr_min"]),
          _config.get("noise_snr_max", _DEFAULTS["noise_snr_max"]),
          _config.get(
              "utterance_snr_min", _DEFAULTS["utterance_snr_min"]
          ),
          _config.get(
              "utterance_snr_max", _DEFAULTS["utterance_snr_max"]
          ),
      )
  
file_path: fairseq/fairseq/data/audio/dataset_transforms/noisyoverlapaugment.py
imports: import numpy
  import torch
  from fairseq.data.audio import rand_uniform
  from fairseq.data.audio.dataset_transforms import AudioDatasetTransform, register_audio_dataset_transform
  from fairseq.data.audio.waveform_transforms.noiseaugment import NoiseAugmentTransform
label_desc: Use image node_id 1 for calling the NoisyOverlapAugment obj's underlying member method code with example usage: obj.from_config_dict(cls, config) and returns: NoisyOverlapAugment