code: def __init__(
      self,
      input_size,
      hidden_size,
      pre_layers,
      post_layers,
      stack_time_factor,
      dropout,
  ):
      self.pre_rnn = LSTM(input_size, hidden_size, pre_layers, dropout)
      self.stack_time = StackTime(stack_time_factor)
      self.post_rnn = LSTM(
          stack_time_factor * hidden_size,
          hidden_size,
          post_layers,
          dropout,
      )
  
imports: from tinygrad.tensor import Tensor
  from tinygrad.jit import TinyJit
  from tinygrad.nn import Linear, Embedding
  from tinygrad.helpers import fetch
  import numpy
  from pathlib import Path
label_desc: Use image node_id 1 to create a new Encoder object  with example: obj = Encoder(input_size, hidden_size, pre_layers, post_layers, stack_time_factor, dropout)