code: def infer(self, txt_enc, spk_emb, lens=None):
      x_hat = self.forward(txt_enc, spk_emb, x=None, lens=lens)["x_hat"]
      x_hat = self.denormalize(x_hat)
      return x_hat
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from nemo.collections.tts.modules.common import ConvLSTMLinear
  from nemo.collections.tts.modules.submodules import ConvNorm, MaskedInstanceNorm1d
  from nemo.collections.tts.modules.transformer import FFTransformer
  from nemo.collections.tts.parts.utils.helpers import get_mask_from_lengths
label_desc: Use image node_id 3 for calling the DAP obj's underlying member method code with example usage: obj.infer(txt_enc, spk_emb, lens) and returns: x_hat