code: def __init__(
      self,
      parent,
      batch_size=13,
      num_channels=3,
      is_training=True,
      use_labels=True,
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      image_size=224,
      num_labels=3,
      layer_depths=[1, 1, 1, 1],
      embed_dims=[16, 16, 32, 32],
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.num_channels = num_channels
      self.is_training = is_training
      self.use_labels = use_labels
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.num_labels = num_labels
      self.image_size = image_size
      self.layer_depths = layer_depths
      self.embed_dims = embed_dims
  
imports: import copy
  import unittest
  from transformers import PretrainedConfig, SwiftFormerConfig
  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, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new SwiftFormerModelTester object  with example: obj = SwiftFormerModelTester(parent, batch_size, num_channels, is_training, use_labels, hidden_dropout_prob, attention_probs_dropout_prob, image_size, num_labels, layer_depths, embed_dims)