code: def __init__(
      self,
      parent,
      batch_size=12,
      image_size=32,
      patch_size=16,
      num_channels=3,
      is_training=True,
      hidden_size=32,
      projection_dim=32,
      num_hidden_layers=2,
      num_attention_heads=4,
      intermediate_size=37,
      dropout=0.1,
      attention_dropout=0.1,
      initializer_range=0.02,
      scope=None,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.image_size = image_size
      self.patch_size = patch_size
      self.num_channels = num_channels
      self.is_training = is_training
      self.hidden_size = hidden_size
      self.projection_dim = projection_dim
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.intermediate_size = intermediate_size
      self.dropout = dropout
      self.attention_dropout = attention_dropout
      self.initializer_range = initializer_range
      self.scope = scope
  
      # in ViT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
      num_patches = (image_size // patch_size) ** 2
      self.seq_length = num_patches + 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 GitVisionModelTester object  with example: obj = GitVisionModelTester(parent, batch_size, image_size, patch_size, num_channels, is_training, hidden_size, projection_dim, num_hidden_layers, num_attention_heads, intermediate_size, dropout, attention_dropout, initializer_range, scope)