code: def embedding_to_torch(speaker_embedding, cuda=False):
      if speaker_embedding is not None:
          speaker_embedding = np.asarray(speaker_embedding)
          speaker_embedding = (
              torch.from_numpy(speaker_embedding)
              .unsqueeze(0)
              .type(torch.FloatTensor)
          )
      if cuda:
          return speaker_embedding.cuda()
      return speaker_embedding
  
file_path: TTS/TTS/tts/utils/synthesis.py
imports: import pkg_resources
  import torch
  import numpy
  from .text import text_to_sequence, phoneme_to_sequence
label_desc: Use image node_id 14 for calling a global function with example usage: embedding_to_torch(speaker_embedding, cuda) and returns: speaker_embedding, speaker_embedding