code: def style_mod(net: Tensor, style: Tensor) -> Tensor:
      style = style.view(style.shape[0], 2, net.shape[1], 1, 1)
      s0, s1 = style[:, 0], style[:, 1]
      return s1 + net * (s0 + 1.0)
  
imports: import math
  import torch
  from typing import *
  from torch import nn
  from torch import Tensor
  from torch.nn import init
  from cftool.types import tensor_dict_type
  from .schema import Decoder1DMixin
  from ....constants import INPUT_KEY
  from ....constants import LABEL_KEY
  from ....constants import LATENT_KEY
  from ....misc.toolkit import auto_num_layers
  from ....modules.blocks import Conv2d
  from ....modules.blocks import Linear
  from ....modules.blocks import GaussianBlur3
  from ....modules.blocks import Activation
  from ....modules.blocks import NormFactory
  from ....modules.blocks import UpsampleConv2d
label_desc: Use image node_id 1 for calling a global function with example usage: style_mod(net, style) and returns: unknown