code: def __init__(self, data_length, alphabet_length, z_dim):
      super().__init__()
  
      self.input_size = data_length * alphabet_length
      self.f1_mn = nn.Linear(self.input_size, z_dim)
      self.f1_sd = nn.Linear(self.input_size, z_dim)
  
imports: import datetime
  import numpy
  import torch
  import torch.nn
  from torch.nn.functional import softplus
  from torch.optim import Adam
  from torch.utils.data import DataLoader
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.contrib.mue.missingdatahmm import MissingDataDiscreteHMM
  from pyro.contrib.mue.statearrangers import Profile
  from pyro.infer import SVI, JitTrace_ELBO, Trace_ELBO
  from pyro.optim import MultiStepLR
label_desc: Use image node_id 1 to create a new Encoder object from inherited base classes: nn with example: obj = Encoder(data_length, alphabet_length, z_dim)