code: def __init__(
      self,
      parent,
      batch_size=13,
      num_hidden_layers=1,
      num_attention_heads=2,
      hidden_size=24,
      seq_length=7,
      encoder_linear_units=384,
      decoder_linear_units=384,
      is_training=False,
      speech_decoder_postnet_units=128,
      speech_decoder_postnet_layers=2,
      pitch_predictor_layers=1,
      energy_predictor_layers=1,
      duration_predictor_layers=1,
      num_mel_bins=8,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.seq_length = seq_length
      self.is_training = is_training
      self.vocab_size = hidden_size
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.encoder_linear_units = encoder_linear_units
      self.decoder_linear_units = decoder_linear_units
      self.speech_decoder_postnet_units = speech_decoder_postnet_units
      self.speech_decoder_postnet_layers = speech_decoder_postnet_layers
      self.pitch_predictor_layers = pitch_predictor_layers
      self.energy_predictor_layers = energy_predictor_layers
      self.duration_predictor_layers = duration_predictor_layers
      self.num_mel_bins = num_mel_bins
  
imports: import inspect
  import tempfile
  import unittest
  from transformers import FastSpeech2ConformerConfig, FastSpeech2ConformerHifiGanConfig, FastSpeech2ConformerTokenizer, FastSpeech2ConformerWithHifiGanConfig, is_torch_available
  from transformers.testing_utils import require_g2p_en, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, ids_tensor
label_desc: Use image node_id 1 to create a new FastSpeech2ConformerModelTester object  with example: obj = FastSpeech2ConformerModelTester(parent, batch_size, num_hidden_layers, num_attention_heads, hidden_size, seq_length, encoder_linear_units, decoder_linear_units, is_training, speech_decoder_postnet_units, speech_decoder_postnet_layers, pitch_predictor_layers, energy_predictor_layers, duration_predictor_layers, num_mel_bins)