code: def __init__(
      self,
      parent,
      batch_size=8,
      is_training=True,
      use_labels=True,
      hidden_size=32,
      num_hidden_layers=2,
      num_attention_heads=8,
      intermediate_size=4,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      num_queries=12,
      num_channels=3,
      image_size=196,
      n_targets=8,
      num_labels=91,
      num_feature_levels=4,
      encoder_n_points=2,
      decoder_n_points=6,
  ):
      self.parent = parent
      self.batch_size = batch_size
      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.num_queries = num_queries
      self.num_channels = num_channels
      self.image_size = image_size
      self.n_targets = n_targets
      self.num_labels = num_labels
      self.num_feature_levels = num_feature_levels
      self.encoder_n_points = encoder_n_points
      self.decoder_n_points = decoder_n_points
  
      # we also set the expected seq length for both encoder and decoder
      self.encoder_seq_length = (
          math.ceil(self.image_size / 8) ** 2
          + math.ceil(self.image_size / 16) ** 2
          + math.ceil(self.image_size / 32) ** 2
          + math.ceil(self.image_size / 64) ** 2
      )
      self.decoder_seq_length = self.num_queries
  
imports: import inspect
  import math
  import unittest
  from typing import Dict, List, Tuple
  from transformers import DeformableDetrConfig, ResNetConfig, is_torch_available, is_vision_available
  from transformers.file_utils import cached_property
  from transformers.testing_utils import require_timm, require_torch, require_torch_accelerator, require_vision, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new DeformableDetrModelTester object  with example: obj = DeformableDetrModelTester(parent, batch_size, is_training, use_labels, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, num_queries, num_channels, image_size, n_targets, num_labels, num_feature_levels, encoder_n_points, decoder_n_points)