code: def __init__(
      self,
      parent,
      batch_size=13,
      image_size=[30, 30],
      patch_size=2,
      num_channels=3,
      is_training=True,
      use_labels=True,
      hidden_size=32,
      num_hidden_layers=5,
      num_attention_heads=4,
      intermediate_size=37,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      type_sequence_label_size=10,
      initializer_range=0.02,
      num_labels=3,
      scope=None,
      n_targets=8,
      num_detection_tokens=10,
  ):
      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.use_labels = use_labels
      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.type_sequence_label_size = type_sequence_label_size
      self.initializer_range = initializer_range
      self.num_labels = num_labels
      self.scope = scope
      self.n_targets = n_targets
      self.num_detection_tokens = num_detection_tokens
      # we set the expected sequence length (which is used in several tests)
      # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token) + num_detection_tokens
      num_patches = (image_size[1] // patch_size) * (
          image_size[0] // patch_size
      )
      self.expected_seq_len = (
          num_patches + 1 + self.num_detection_tokens
      )
  
imports: import inspect
  import unittest
  from transformers import YolosConfig
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from transformers.utils import cached_property, is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor
label_desc: Use image node_id 1 to create a new YolosModelTester object  with example: obj = YolosModelTester(parent, batch_size, image_size, patch_size, num_channels, is_training, use_labels, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, type_sequence_label_size, initializer_range, num_labels, scope, n_targets, num_detection_tokens)