class_docstr: Same as `LowPassFilters` but applies a single low pass filter.
  
  Shape:
  
      - Input: `[*, T]`
      - Output: `[*, T']`, with `T'=T` if `pad` is True and `stride` is 1.
  
  >>> lowpass = LowPassFilter(1/4, stride=2)
  >>> x = torch.randn(4, 124)
  >>> list(lowpass(x).shape)
  [4, 62]
code: def __init__(
      self,
      cutoff: float,
      stride: int = 1,
      pad: bool = True,
      zeros: float = 8,
      fft: Optional[bool] = None,
  ):
      super().__init__()
      self._lowpasses = LowPassFilters(
          [cutoff], stride, pad, zeros, fft
      )
  
imports: import math
  from typing import Sequence, Optional
  import torch
  from torch.nn import functional
  from .core import sinc
  from .fftconv import fft_conv1d
  from .utils import simple_repr
label_desc: Use image node_id 1 to create a new LowPassFilter object from inherited base classes: torch.nn with example: obj = LowPassFilter(cutoff, stride, pad, zeros, fft)