code: def highpass_filter(
      input: torch.Tensor,
      cutoff: float,
      stride: int = 1,
      pad: bool = True,
      zeros: float = 8,
      fft: Optional[bool] = None,
  ):
      """
      Functional version of `HighPassFilter`, refer to this class for more information.
      Output will not have a dimension inserted in the front.
      """
      return highpass_filters(input, [cutoff], stride, pad, zeros, fft)[
          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 a global function with example usage: highpass_filter(input, cutoff, stride, pad, zeros, fft) and returns: highpass_filters