code: def clip(
      audio: Union[str, np.ndarray],
      sample_rate: int = DEFAULT_SAMPLE_RATE,
      offset_factor: float = 0.0,
      duration_factor: float = 1.0,
      output_path: Optional[str] = None,
      metadata: Optional[List[Dict[str, Any]]] = None,
  ) -> Tuple[np.ndarray, int]:
      """
      Clips the audio using the specified offset and duration factors
  
      @param audio: the path to the audio or a variable of type np.ndarray that
          will be augmented
  
      @param sample_rate: the audio sample rate of the inputted audio
  
      @param offset_factor: start point of the crop relative to the audio duration
          (this parameter is multiplied by the audio duration)
  
      @param duration_factor: the length of the crop relative to the audio duration
          (this parameter is multiplied by the audio duration)
  
      @param output_path: the path in which the resulting audio will be stored. If None,
          the resulting np.ndarray will still be returned
  
      @param metadata: if set to be a list, metadata about the function execution
          including its name, the source & dest duration, sample rates, etc. will be
          appended to the inputted list. If set to None, no metadata will be appended
  
      @returns: the augmented audio array and sample rate
      """
      assert (
          0.0 <= (offset_factor + duration_factor) <= 1.0
      ), "Combination of offset and duration factors exceed audio length"
  
      audio, sample_rate = audutils.validate_and_load_audio(
          audio, sample_rate
      )
  
      if metadata is not None:
          func_kwargs = deepcopy(locals())
          func_kwargs.pop("metadata")
  
      num_samples = audio.shape[-1]
      start = int(offset_factor * num_samples)
      end = int((offset_factor + duration_factor) * num_samples)
      aug_audio = audio[..., start:end]
  
      if metadata is not None:
          audutils.get_metadata(
              metadata=metadata,
              function_name="clip",
              dst_audio=aug_audio,
              dst_sample_rate=sample_rate,
              start_sample=start,
              end_sample=end,
              # pyre-fixme[61]: `func_kwargs` may not be initialized here.
              **func_kwargs,
          )
  
      return audutils.ret_and_save_audio(
          aug_audio, output_path, sample_rate
      )
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from augly.audio import utils
  from augly.utils import DEFAULT_SAMPLE_RATE
  from augly.utils.libsndfile import install_libsndfile
  import librosa
  from torchaudio import sox_effects
  from torchaudio.functional import fftconvolve, resample
label_desc: Use image node_id 5 for calling a global function with example usage: clip(audio, sample_rate, offset_factor, duration_factor, output_path, metadata) and returns: audutils