class_docstr: From DeepVoice 3
class_docstr_tok: ["From","DeepVoice","3"]
code: def forward(
      self, x: torch.Tensor, embeddings: torch.Tensor
  ) -> torch.Tensor:
      x = x.permute((0, 2, 1))
      residual = x
      x = self.conv(x)
      splitdim = 1
      a, b = x.split(x.size(splitdim) // 2, dim=splitdim)
      embeddings = self.embedding_proj(embeddings).unsqueeze(2)
      softsign = self.softsign(embeddings)
      softsign = softsign.expand_as(a)
      a = a + softsign
      x = a * torch.sigmoid(b)
      x = x + residual
      x = x * self.sqrt
      x = x.permute((0, 2, 1))
      return x
  
imports: from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.utils import parametrize
  from TTS.tts.layers.delightful_tts.kernel_predictor import KernelPredictor
label_desc: Use image node_id 2 for calling the Conv1dGLU obj's underlying member method code with example usage: obj.forward(x, embeddings) and returns: x