code: def __init__(self, fused=True):
      super().__init__()
  
      self.progression = nn.HybridSequential()
      with self.progression.name_scope():
          self.progression.add(
              StyledConvBlock(512, 512, 3, 1, initial=True, blur=blur)
          )  # 4
          self.progression.add(
              StyledConvBlock(512, 512, 3, 1, upsample=True, blur=blur)
          )  # 8
          self.progression.add(
              StyledConvBlock(512, 512, 3, 1, upsample=True, blur=blur)
          )  # 16
          self.progression.add(
              StyledConvBlock(512, 512, 3, 1, upsample=True, blur=blur)
          )  # 32
          self.progression.add(
              StyledConvBlock(512, 256, 3, 1, upsample=True, blur=blur)
          )  # 64
          self.progression.add(
              StyledConvBlock(
                  256, 128, 3, 1, upsample=True, fused=fused, blur=blur
              )
          )  # 128
          self.progression.add(
              StyledConvBlock(
                  128, 64, 3, 1, upsample=True, fused=fused, blur=blur
              )
          )  # 256
          self.progression.add(
              StyledConvBlock(
                  64, 32, 3, 1, upsample=True, fused=fused, blur=blur
              )
          )  # 512
          self.progression.add(
              StyledConvBlock(
                  32, 16, 3, 1, upsample=True, fused=fused, blur=blur
              )
          )  # 1024
  
      self.to_rgb = nn.HybridSequential()
      with self.to_rgb.name_scope():
          self.to_rgb.add(EqualConv2d(512, 3, 1))
          self.to_rgb.add(EqualConv2d(512, 3, 1))
          self.to_rgb.add(EqualConv2d(512, 3, 1))
          self.to_rgb.add(EqualConv2d(512, 3, 1))
          self.to_rgb.add(EqualConv2d(256, 3, 1))
          self.to_rgb.add(EqualConv2d(128, 3, 1))
          self.to_rgb.add(EqualConv2d(64, 3, 1))
          self.to_rgb.add(EqualConv2d(32, 3, 1))
          self.to_rgb.add(EqualConv2d(16, 3, 1))
  
file_path: gluon-cv/scripts/gan/stylegan/model.py
imports: import random
  import numpy
  from math import sqrt
  import mxnet
  import mxnet.ndarray
  from modules import *
label_desc: Use image node_id 1 to create a new Generator object from inherited base classes: nn with example: obj = Generator(fused)