class_docstr: Standard ResNet bottleneck with MoVie modulation in
  https://arxiv.org/abs/2004.11883
  The code is inspired from
  https://pytorch.org/docs/stable/_modules/torchvision/models/resnet.html
class_docstr_tok: ["Standard","ResNet","bottleneck","with","MoVie","modulation","in","https",":","\/\/arxiv.org\/abs\/2004.11883","The","code","is","inspired","from","https",":","\/\/pytorch.org\/docs\/stable\/_modules\/torchvision\/models\/resnet.html"]
code: def init_layers(self):
      if self.cond_planes:
          self.cond = Modulation(
              self.inplanes,
              self.cond_planes,
              compressed=self.compressed,
          )
          self.se = (
              SEModule(self.planes * self.expansion, 4)
              if self.use_se
              else None
          )
  
imports: from collections import OrderedDict
  from typing import Optional, Tuple, Type
  import torch
  import torch.nn
  from torchvision.models.resnet import Bottleneck, conv1x1, conv3x3
  from torchvision.ops.misc import FrozenBatchNorm2d
label_desc: Use image node_id 2 for calling the MovieBottleneck obj's underlying member method code with example usage: obj.init_layers() without return types