code: def _get_neural_hmm(deterministic_transition=None):
      config = deepcopy(config_global)
      neural_hmm = NeuralHMM(
          config.out_channels,
          config.ar_order,
          config.deterministic_transition
          if deterministic_transition is None
          else deterministic_transition,
          config.encoder_in_out_features,
          config.prenet_type,
          config.prenet_dim,
          config.prenet_n_layers,
          config.prenet_dropout,
          config.prenet_dropout_at_inference,
          config.memory_rnn_dim,
          config.outputnet_size,
          config.flat_start_params,
          config.std_floor,
      ).to(device)
      return neural_hmm
  
imports: import os
  import random
  import unittest
  from copy import deepcopy
  import torch
  from tests import get_tests_output_path
  from TTS.tts.configs.overflow_config import OverflowConfig
  from TTS.tts.layers.overflow.common_layers import Encoder, Outputnet, OverflowUtils
  from TTS.tts.layers.overflow.decoder import Decoder
  from TTS.tts.layers.overflow.neural_hmm import EmissionModel, NeuralHMM, TransitionModel
  from TTS.tts.models.overflow import Overflow
  from TTS.tts.utils.helpers import sequence_mask
  from TTS.utils.audio import AudioProcessor
label_desc: Use image node_id 1 for calling the TestNeuralHMM obj's underlying member method code with example usage: obj._get_neural_hmm(deterministic_transition) and returns: neural_hmm