code: def __init__(
      self,
      parent,
      num_channels=3,
      image_size=32,
      patch_size=16,
      batch_size=13,
      text_seq_length=7,
      is_training=True,
      use_input_mask=True,
      use_labels=True,
      vocab_size=99,
      hidden_size=32,
      num_hidden_layers=2,
      num_attention_heads=4,
      intermediate_size=37,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      max_position_embeddings=512,
      type_vocab_size=16,
      initializer_range=0.02,
      num_labels=3,
      scope=None,
  ):
      self.parent = parent
      self.num_channels = num_channels
      self.image_size = image_size
      self.patch_size = patch_size
      self.batch_size = batch_size
      self.text_seq_length = text_seq_length
      self.is_training = is_training
      self.use_input_mask = use_input_mask
      self.use_labels = use_labels
      self.vocab_size = vocab_size
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.intermediate_size = intermediate_size
      self.hidden_act = hidden_act
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.max_position_embeddings = max_position_embeddings
      self.type_vocab_size = type_vocab_size
      self.initializer_range = initializer_range
      self.num_labels = num_labels
      self.scope = scope
  
      # make sure the BOS, EOS and PAD tokens are within the vocab
      self.bos_token_id = vocab_size - 1
      self.eos_token_id = vocab_size - 1
      self.pad_token_id = vocab_size - 1
  
      # for GIT, the sequence length is the sum of the text and patch tokens, + 1 due to the CLS token
      self.seq_length = (
          self.text_seq_length
          + int((self.image_size / self.patch_size) ** 2)
          + 1
      )
  
imports: import inspect
  import unittest
  from huggingface_hub import hf_hub_download
  from transformers import GitConfig, GitProcessor, GitVisionConfig, is_torch_available, is_vision_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new GitModelTester object  with example: obj = GitModelTester(parent, num_channels, image_size, patch_size, batch_size, text_seq_length, is_training, use_input_mask, use_labels, vocab_size, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_vocab_size, initializer_range, num_labels, scope)