class_docstr: Up-sample residual block (from MSG-Net paper)
  Enables passing identity all the way through the generator
  ref https://arxiv.org/abs/1703.06953
  
  Args:
     inplanes(int): Number of input channels.
     planes(int): Number of output channels.
     stride(int): Number of stride, default is 2.
     norm_layer(nn.Layer): Batch norm layer, default is nn.BatchNorm2D.
  
  Return:
      img(paddle.Tensor): UpBottleneck output.
class_docstr_tok: ["Up-sample","residual","block","(","from","MSG-Net","paper",")","Enables","passing","identity","all","the","way","through","the","generator","ref","https",":","\/\/arxiv.org\/abs\/1703.06953","Args",":","inplanes","(","int",")",":","Number","of","input","channels",".","planes","(","int",")",":","Number","of","output","channels",".","stride","(","int",")",":","Number","of","stride",",","default","is","2.","norm_layer","(","nn.Layer",")",":","Batch","norm","layer",",","default","is","nn.BatchNorm2D",".","Return",":","img","(","paddle.Tensor",")",":","UpBottleneck","output","."]
code: def __init__(
      self,
      inplanes: int,
      planes: int,
      stride: int = 2,
      norm_layer: nn.Layer = nn.BatchNorm2D,
  ):
      super(UpBottleneck, self).__init__()
      self.expansion = 4
      self.residual_layer = UpsampleConvLayer(
          inplanes,
          planes * self.expansion,
          kernel_size=1,
          stride=1,
          upsample=stride,
      )
      conv_block = []
      conv_block += [
          norm_layer(inplanes),
          nn.ReLU(),
          nn.Conv2D(inplanes, planes, kernel_size=1, stride=1),
      ]
      conv_block += [
          norm_layer(planes),
          nn.ReLU(),
          UpsampleConvLayer(
              planes, planes, kernel_size=3, stride=1, upsample=stride
          ),
      ]
      conv_block += [
          norm_layer(planes),
          nn.ReLU(),
          nn.Conv2D(
              planes, planes * self.expansion, kernel_size=1, stride=1
          ),
      ]
      self.conv_block = nn.Sequential(*conv_block)
  
imports: import os
  import argparse
  import paddle
  import paddle.nn
  import numpy
  import paddle.nn.functional
  from paddlehub.env import MODULE_HOME
  from paddlehub.module.module import moduleinfo
  from paddlehub.vision.transforms import Compose, Resize, CenterCrop
  from paddlehub.module.cv_module import StyleTransferModule
label_desc: Use image node_id 1 to create a new UpBottleneck object from inherited base classes: nn with example: obj = UpBottleneck(inplanes, planes, stride, norm_layer)