code: def pad_or_truncate(t, length):
      """
      Ensure a given tensor t has a specified sequence length by either padding it with zeros or clipping it.
  
      Args:
          t (torch.Tensor): The input tensor to be padded or truncated.
          length (int): The desired length of the tensor.
  
      Returns:
          torch.Tensor: The padded or truncated tensor.
      """
      tp = t[..., :length]
      if t.shape[-1] == length:
          tp = t
      elif t.shape[-1] < length:
          tp = F.pad(t, (0, length - t.shape[-1]))
      return tp
  
imports: import os
  from dataclasses import dataclass
  import librosa
  import torch
  import torch.nn.functional
  import torchaudio
  from coqpit import Coqpit
  from TTS.tts.layers.xtts.gpt import GPT
  from TTS.tts.layers.xtts.hifigan_decoder import HifiDecoder
  from TTS.tts.layers.xtts.stream_generator import init_stream_support
  from TTS.tts.layers.xtts.tokenizer import VoiceBpeTokenizer, split_sentence
  from TTS.tts.layers.xtts.xtts_manager import SpeakerManager, LanguageManager
  from TTS.tts.models.base_tts import BaseTTS
  from TTS.utils.io import load_fsspec
label_desc: Use image node_id 3 for calling a global function with example usage: pad_or_truncate(t, length) and returns: tp