docstr: Generates input examples for tracing etc.
  Returns:
      A tuple of input examples.
docstr_tok: ["Generates","input","examples","for","tracing","etc",".","Returns",":","A","tuple","of","input","examples","."]
code: def input_example(self, max_batch=1, max_dim=256):
      """
      Generates input examples for tracing etc.
      Returns:
          A tuple of input examples.
      """
      par = next(self.parameters())
      mel = torch.randn(
          (max_batch, self.n_mel_channels, max_dim),
          device=par.device,
          dtype=par.dtype,
      )
      z = torch.randn(
          (
              max_batch,
              self.n_mel_channels,
              max_dim * self.upsample.stride[0] // self.n_group,
          ),
          device=par.device,
          dtype=par.dtype,
      )
      return {"spec": mel, "z": z}
  
file_path: NeMo/nemo/collections/tts/modules/waveglow.py
imports: from typing import Tuple
  import torch
  from nemo.collections.tts.modules.submodules import Invertible1x1Conv, WaveNet
  from nemo.collections.tts.parts.utils.helpers import OperationMode, remove, split_view
  from nemo.core.classes import Exportable, NeuralModule, typecheck
  from nemo.core.neural_types.elements import AudioSignal, IntType, MelSpectrogramType, NormalDistributionSamplesType, VoidType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 6 for calling the WaveGlowModule obj's underlying member method code with example usage: obj.input_example(max_batch, max_dim) and returns: dict