code: def encode_and_initialize(
      self, inputs: pt.Tensor, valid_length: Optional[pt.Tensor] = None
  ):
      batch_size = inputs.shape[0]
      # 'lengths'
      internal_lengths = pt.zeros(batch_size, 1, dtype=pt.int)
      num_decode_step_calls = pt.zeros(1, dtype=pt.int)
      self.states = [
          internal_lengths,
          num_decode_step_calls,
      ]  # TODO add nested states
      predicted_output_length = pt.ones(
          batch_size, 1
      )  # does that work?
      nvs_prediction = None
      return self.states, predicted_output_length, nvs_prediction
  
imports: from typing import List, Optional
  from typing import Tuple
  import numpy
  import pytest
  import torch
  import numpy
  import sockeye.beam_search
  import sockeye.constants
  import sockeye.lexicon
  import sockeye.utils
label_desc: Use image node_id 3 for calling the _TestInference obj's underlying member method code with example usage: obj.encode_and_initialize(inputs, valid_length) and returns: self,  predicted_output_length,  nvs_prediction