code: def __init__(
      self,
      local_size=1,
      alpha=1.0,
      beta=0.75,
      k=1,
      ACROSS_CHANNELS=True,
  ):
      super(SpatialCrossMapLRN, self).__init__()
      self.ACROSS_CHANNELS = ACROSS_CHANNELS
      if ACROSS_CHANNELS:
          self.average = nn.AvgPool3d(
              kernel_size=(local_size, 1, 1),
              stride=1,
              padding=(int((local_size - 1.0) / 2), 0, 0),
          )
      else:
          self.average = nn.AvgPool2d(
              kernel_size=local_size,
              stride=1,
              padding=int((local_size - 1.0) / 2),
          )
      self.alpha = alpha
      self.beta = beta
      self.k = k
  
imports: from __future__ import print_function, division, absolute_import
  import torch
  import torch.nn
  from torch.autograd import Variable
  import torch.utils.model_zoo
label_desc: Use image node_id 1 to create a new SpatialCrossMapLRN object from inherited base classes: nn with example: obj = SpatialCrossMapLRN(local_size, alpha, beta, k, ACROSS_CHANNELS)