code: def __init__(
      self,
      parent,
      batch_size=13,
      image_size=32,
      patch_size=2,
      num_channels=3,
      last_hidden_size=640,
      num_attention_heads=4,
      hidden_act="silu",
      conv_kernel_size=3,
      output_stride=32,
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      classifier_dropout_prob=0.1,
      initializer_range=0.02,
      is_training=True,
      use_labels=True,
      num_labels=10,
      scope=None,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.image_size = image_size
      self.patch_size = patch_size
      self.num_channels = num_channels
      self.last_hidden_size = last_hidden_size
      self.num_attention_heads = num_attention_heads
      self.hidden_act = hidden_act
      self.conv_kernel_size = conv_kernel_size
      self.output_stride = output_stride
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.classifier_dropout_prob = classifier_dropout_prob
      self.use_labels = use_labels
      self.is_training = is_training
      self.num_labels = num_labels
      self.initializer_range = initializer_range
      self.scope = scope
  
imports: import inspect
  import unittest
  from transformers import MobileViTConfig
  from transformers.file_utils import is_tf_available, is_vision_available
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 1 to create a new TFMobileViTModelTester object  with example: obj = TFMobileViTModelTester(parent, batch_size, image_size, patch_size, num_channels, last_hidden_size, num_attention_heads, hidden_act, conv_kernel_size, output_stride, hidden_dropout_prob, attention_probs_dropout_prob, classifier_dropout_prob, initializer_range, is_training, use_labels, num_labels, scope)