code: def mlp(sizes, activation, output_activation=nn.Identity):
      layers = []
      for j in range(len(sizes) - 1):
          act = activation if j < len(sizes) - 2 else output_activation
          layers += [nn.Linear(sizes[j], sizes[j + 1]), act()]
      return nn.Sequential(*layers)
  
imports: import numpy
  import scipy.signal
  from gym.spaces import Box, Discrete
  import torch
  import torch.nn
  from torch.distributions.normal import Normal
  from torch.distributions.categorical import Categorical
label_desc: Use image node_id 2 for calling a global function with example usage: mlp(sizes, activation, output_activation) and returns: nn