code: def test_outputnet_forward_with_flat_start(self):
      model = self._get_outputnet()
      input_dummy, one_timestep_frame = self._get_embedded_input()
      mean, std, transition_vector = model(
          one_timestep_frame, input_dummy
      )
      self.assertTrue(
          torch.isclose(
              mean, torch.tensor(model.flat_start_params["mean"] * 1.0)
          ).all()
      )
      self.assertTrue(
          torch.isclose(
              std, torch.tensor(model.flat_start_params["std"] * 1.0)
          ).all()
      )
      self.assertTrue(
          torch.isclose(
              transition_vector.sigmoid(),
              torch.tensor(
                  model.flat_start_params["transition_p"] * 1.0
              ),
          ).all()
      )
  
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 3 for calling the TestOverflowOutputNet obj's underlying member method code with example usage: obj.test_outputnet_forward_with_flat_start() without return types