code: def unif_init(m, n_in, n_out):
      scale = np.sqrt(6.0 / (n_in + n_out))
      m.weight.data.uniform_(-scale, scale)
      m.bias.data = torch.zeros((1, n_out))
  
imports: import logging
  import os
  from typing import List
  import numpy
  import torch
  import torch.nn
  from torch.utils.data import Dataset
  from pythae.data.datasets import DatasetOutput
  from pythae.models import MIWAE, AutoModel, MIWAEConfig
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.nn import BaseDecoder, BaseEncoder
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
label_desc: Use image node_id 1 for calling a global function with example usage: unif_init(m, n_in, n_out) without return types