code: def setup_seed(seed):
      if seed == -1:
          return
      torch.manual_seed(seed)
      if torch.cuda.is_available():
          torch.cuda.manual_seed_all(seed)
      np.random.seed(seed)
      random.seed(seed)
      torch.backends.cudnn.deterministic = True
  
file_path: TTS/TTS/tts/layers/xtts/stream_generator.py
imports: import copy
  import inspect
  import random
  import warnings
  from typing import Callable, List, Optional, Union
  import numpy
  import torch
  import torch.distributed
  from torch import nn
  from transformers import BeamSearchScorer, ConstrainedBeamSearchScorer, DisjunctiveConstraint, GenerationConfig, GenerationMixin, LogitsProcessorList, PhrasalConstraint, PreTrainedModel, StoppingCriteriaList
  from transformers.generation.utils import GenerateOutput, SampleOutput, logger
label_desc: Use image node_id 1 for calling a global function with example usage: setup_seed(seed) without return types