code: def __init__(
      self,
      orig_freq: int = 16000,
      new_freq: int = 16000,
      lowpass_filter_width: int = 6,
      rolloff: float = 0.99,
      beta: Optional[float] = None,
      dtype: Optional[dtypes] = None,
  ):
      (
          self.orig_freq,
          self.new_freq,
          self.lowpass_filter_width,
          self.rolloff,
          self.beta,
      ) = (orig_freq, new_freq, lowpass_filter_width, rolloff, beta)
      self.gcd = math.gcd(int(self.orig_freq), int(self.new_freq))
      self.kernel, self.width = (
          self._get_sinc_resample_kernel(dtype)
          if self.orig_freq != self.new_freq
          else (None, None)
      )
  
imports: import math
  from typing import Optional, Tuple
  from tinygrad import Tensor, dtypes
  import librosa
  import soundfile
  import numpy
  import parselmouth
label_desc: Use image node_id 1 to create a new Resample object  with example: obj = Resample(orig_freq, new_freq, lowpass_filter_width, rolloff, beta, dtype)