code: def __init__(
      self,
      parent,
      hidden_act="gelu",
      hidden_size=64,
      initializer_factor=1,
      layer_norm_eps=1e-05,
      num_attention_heads=4,
      num_hidden_layers=2,
      intermediate_size=128,
      tie_word_embeddings=False,
      output_hidden_states=False,
  ):
      self.parent = parent
      self.hidden_act = hidden_act
      self.hidden_size = hidden_size
      self.initializer_factor = initializer_factor
      self.layer_norm_eps = layer_norm_eps
      self.num_attention_heads = num_attention_heads
      self.num_hidden_layers = num_hidden_layers
      self.intermediate_size = intermediate_size
      self.tie_word_embeddings = tie_word_embeddings
      self.vocab_size = 99
      self.seq_length = 4
      self.batch_size = 1
      self.is_training = False
      self.output_hidden_states = output_hidden_states
  
imports: import tempfile
  import unittest
  import numpy
  from transformers import BridgeTowerConfig, BridgeTowerTextConfig, BridgeTowerVisionConfig, is_torch_available, is_vision_available
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new BridgeTowerTextModelTester object  with example: obj = BridgeTowerTextModelTester(parent, hidden_act, hidden_size, initializer_factor, layer_norm_eps, num_attention_heads, num_hidden_layers, intermediate_size, tie_word_embeddings, output_hidden_states)