class_docstr: NN Module attending to style tokens based on prosody encodings.
class_docstr_tok: ["NN","Module","attending","to","style","tokens","based","on","prosody","encodings","."]
code: def forward(self, inputs):
      batch_size = inputs.size(0)
      prosody_encoding = inputs.unsqueeze(1)
      # prosody_encoding: 3D tensor [batch_size, 1, encoding_size==128]
      tokens = (
          torch.tanh(self.style_tokens)
          .unsqueeze(0)
          .expand(batch_size, -1, -1)
      )
      # tokens: 3D tensor [batch_size, num tokens, token embedding size]
      style_embed = self.attention(prosody_encoding, tokens)
  
      return style_embed
  
file_path: TTS/TTS/tts/layers/tacotron/gst_layers.py
imports: import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the StyleTokenLayer obj's underlying member method code with example usage: obj.forward(inputs) and returns: style_embed