code: def __init__(
      self,
      parent,
      batch_size=13,
      image_size=32,
      num_channels=3,
      kernel_sizes=[3, 3, 5],
      in_channels=[32, 16, 24],
      out_channels=[16, 24, 20],
      strides=[1, 1, 2],
      num_block_repeats=[1, 1, 2],
      expand_ratios=[1, 6, 6],
      is_training=True,
      use_labels=True,
      intermediate_size=37,
      hidden_act="gelu",
      num_labels=10,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.image_size = image_size
      self.num_channels = num_channels
      self.kernel_sizes = kernel_sizes
      self.in_channels = in_channels
      self.out_channels = out_channels
      self.strides = strides
      self.num_block_repeats = num_block_repeats
      self.expand_ratios = expand_ratios
      self.is_training = is_training
      self.hidden_act = hidden_act
      self.num_labels = num_labels
      self.use_labels = use_labels
  
imports: import unittest
  from transformers import EfficientNetConfig
  from transformers.testing_utils import is_pipeline_test, 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 EfficientNetModelTester object  with example: obj = EfficientNetModelTester(parent, batch_size, image_size, num_channels, kernel_sizes, in_channels, out_channels, strides, num_block_repeats, expand_ratios, is_training, use_labels, intermediate_size, hidden_act, num_labels)