code: def get_config(self):
      config = OneFormerConfig(
          text_encoder_vocab_size=self.vocab_size,
          hidden_size=self.hidden_dim,
          num_queries=self.num_queries,
          num_labels=self.num_labels,
          encoder_feedforward_dim=32,
          dim_feedforward=64,
          encoder_layers=2,
          decoder_layers=2,
      )
  
      config.backbone_config.embed_dim = 16
      config.backbone_config.depths = [1, 1, 1, 1]
      config.backbone_config.hidden_size = 16
      config.backbone_config.num_channels = self.num_channels
      config.backbone_config.num_heads = [1, 1, 2, 2]
  
      config.hidden_dim = self.hidden_dim
      config.mask_dim = self.hidden_dim
      config.conv_dim = self.hidden_dim
  
      config.text_encoder_width = self.hidden_dim
      config.task_seq_len = self.sequence_length
      config.max_seq_len = self.sequence_length
      config.text_encoder_context_length = self.sequence_length
      config.text_encoder_n_ctx = self.n_ctx
  
      return config
  
imports: import copy
  import inspect
  import unittest
  import numpy
  from tests.test_modeling_common import floats_tensor
  from transformers import OneFormerConfig, is_torch_available, is_vision_available
  from transformers.testing_utils import require_torch, require_torch_accelerator, require_torch_fp16, require_torch_multi_gpu, require_vision, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the OneFormerModelTester obj's underlying member method code with example usage: obj.get_config() and returns: config