code: def __init__(self, nbins=9, pool=7, gaussian_window=0):
      super(HOGLayerC, self).__init__()
      self.nbins = nbins
      self.pool = pool
      self.pi = math.pi
      weight_x = torch.FloatTensor([[1, 0, -1], [2, 0, -2], [1, 0, -1]])
      weight_x = weight_x.view(1, 1, 3, 3).repeat(3, 1, 1, 1)
      weight_y = weight_x.transpose(2, 3)
      self.register_buffer("weight_x", weight_x)
      self.register_buffer("weight_y", weight_y)
  
      self.gaussian_window = gaussian_window
      if gaussian_window:
          gkern = get_gkern(gaussian_window, gaussian_window // 2)
          self.register_buffer("gkern", gkern)
  
file_path: SlowFast/slowfast/models/operators.py
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from slowfast.models.utils import get_gkern
  from pytorchvideo.layers.swish import Swish
label_desc: Use image node_id 1 to create a new HOGLayerC object from inherited base classes: nn with example: obj = HOGLayerC(nbins, pool, gaussian_window)