class_docstr: Same as `HighPassFilters` but applies a single high pass filter.
  
  Shape:
  
      - Input: `[*, T]`
      - Output: `[*, T']`, with `T'=T` if `pad` is True and `stride` is 1.
  
  >>> highpass = HighPassFilter(1/4, stride=1)
  >>> x = torch.randn(4, 124)
  >>> list(highpass(x).shape)
  [4, 124]
code: def cutoff(self):
      return self._highpasses.cutoffs[0]
  
imports: from typing import Sequence, Optional
  import torch
  from .lowpass import lowpass_filter, lowpass_filters, LowPassFilter, LowPassFilters
  from .utils import simple_repr
label_desc: Use image node_id 2 for calling the HighPassFilter obj's underlying member method code with example usage: obj.cutoff() and returns: self