class_docstr: Upsamples the input and then does a convolution. This method gives better results compared to ConvTranspose2d.
  ref: http://distill.pub/2016/deconv-checkerboard/
  
  Args:
     in_channels(int): Number of input channels.
     out_channels(int): Number of output channels.
     kernel_size(int): Number of kernel size.
     stride(int): Number of stride.
     upsample(int): Scale factor for upsample layer, default is None.
  
  Return:
      img(paddle.Tensor): UpsampleConvLayer output.
class_docstr_tok: ["Upsamples","the","input","and","then","does","a","convolution",".","This","method","gives","better","results","compared","to","ConvTranspose2d",".","ref",":","http",":","\/\/distill.pub\/2016\/deconv-checkerboard\/","Args",":","in_channels","(","int",")",":","Number","of","input","channels",".","out_channels","(","int",")",":","Number","of","output","channels",".","kernel_size","(","int",")",":","Number","of","kernel","size",".","stride","(","int",")",":","Number","of","stride",".","upsample","(","int",")",":","Scale","factor","for","upsample","layer",",","default","is","None",".","Return",":","img","(","paddle.Tensor",")",":","UpsampleConvLayer","output","."]
code: def __init__(
      self,
      in_channels: int,
      out_channels: int,
      kernel_size: int,
      stride: int,
      upsample=None,
  ):
      super(UpsampleConvLayer, self).__init__()
      self.upsample = upsample
      if upsample:
          self.upsample_layer = nn.Upsample(scale_factor=upsample)
      self.pad = int(np.floor(kernel_size / 2))
      if self.pad != 0:
          self.reflection_pad = nn.Pad2D(
              [self.pad, self.pad, self.pad, self.pad], mode="reflect"
          )
      self.conv2d = nn.Conv2D(
          in_channels, out_channels, kernel_size, stride
      )
  
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 UpsampleConvLayer object from inherited base classes: nn with example: obj = UpsampleConvLayer(in_channels, out_channels, kernel_size, stride, upsample)