code: def _apply_sinc_resample_kernel(self, waveform: Tensor):
      if not waveform.is_floating_point():
          raise TypeError(
              f"Waveform tensor expected to be of type float, but received {waveform.dtype}."
          )
      orig_freq, new_freq = (int(self.orig_freq) // self.gcd), (
          int(self.new_freq) // self.gcd
      )
      shape = waveform.shape
      waveform = waveform.reshape(-1, shape[-1])  # pack batch
      num_wavs, length = waveform.shape
      target_length = int(math.ceil(new_freq * length / orig_freq))
      waveform = waveform.pad2d((self.width, self.width + orig_freq))
      resampled = waveform[:, None].conv2d(
          self.kernel, stride=orig_freq
      )
      resampled = resampled.transpose(1, 2).reshape(num_wavs, -1)
      resampled = resampled[..., :target_length]
      resampled = resampled.reshape(
          shape[:-1] + resampled.shape[-1:]
      )  # unpack batch
      return resampled
  
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 3 for calling the Resample obj's underlying member method code with example usage: obj._apply_sinc_resample_kernel(waveform) and returns: resampled