code: 
  
  
  
  
  
  
  """simple docstring"""
  
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
      is_vision_available,
  )
  
  
  A_			  =    {
      "configuration_mobilevitv2": [
          "MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "MobileViTV2Config",
          "MobileViTV2OnnxConfig",
      ],
  }
  
  
  try:
  				if not is_torch_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				A_			  =    [
  				    "MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST",
  				    "MobileViTV2ForImageClassification",
  				    "MobileViTV2ForSemanticSegmentation",
  				    "MobileViTV2Model",
  				    "MobileViTV2PreTrainedModel",
  				]
  
  if TYPE_CHECKING:
  				from .configuration_mobilevitva import (
  				    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
  				    MobileViTVaConfig,
  				    MobileViTVaOnnxConfig,
  				)
  
  				try:
  								if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  				except OptionalDependencyNotAvailable:
  								pass
  				else:
  								from .modeling_mobilevitva import (
  								    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
  								    MobileViTVaForImageClassification,
  								    MobileViTVaForSemanticSegmentation,
  								    MobileViTVaModel,
  								    MobileViTVaPreTrainedModel,
  								)
  
  else:
  				import sys
  
  				A_			  =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  
  
  
  
  
  import unittest
  from dataclasses import dataclass
  from typing import List, Union
  
  import numpy as np
  import PIL.Image
  
  from diffusers.utils.outputs import BaseOutput
  @dataclass
  class 						__lowerCAmelCase   (			UpperCAmelCase       ):
  
  
  
  
  
  
  
    '''simple docstring'''
  
  
    __lowerCamelCase       :    Union[List[PIL.Image.Image], np.ndarray]
  
  
  
  
  class 						__lowerCAmelCase   (			unittest.TestCase       ):
  
  
  
  
  
  
  
    '''simple docstring'''
  
  
    def 					UpperCamelCase__   (      self:		Tuple					):
       UpperCamelCase_     =CustomOutput(images=np.random.rand(1				,			3				,			4				,			4					)					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			np.ndarray					)
       assert outputs.images.shape == (1, 3, 4, 4)
       assert isinstance(outputs["images"]				,			np.ndarray					)
       assert outputs["images"].shape == (1, 3, 4, 4)
       assert isinstance(outputs[0]				,			np.ndarray					)
       assert outputs[0].shape == (1, 3, 4, 4)
  
       # test with a non-tensor attribute
       UpperCamelCase_     =CustomOutput(images=[PIL.Image.new("RGB"				,			(4, 4)					)]					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			UpperCamelCase_					)
       assert isinstance(outputs.images[0]				,			PIL.Image.Image					)
       assert isinstance(outputs["images"]				,			UpperCamelCase_					)
       assert isinstance(outputs["images"][0]				,			PIL.Image.Image					)
       assert isinstance(outputs[0]				,			UpperCamelCase_					)
       assert isinstance(outputs[0][0]				,			PIL.Image.Image					)
  
  
  
  
  
    def 					UpperCamelCase__   (      self:		Optional[int]					):
       # test output reinitialization with a `dict` for compatibility with `accelerate`
       UpperCamelCase_     =CustomOutput({"images": np.random.rand(1				,			3				,			4				,			4					)}					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			np.ndarray					)
       assert outputs.images.shape == (1, 3, 4, 4)
       assert isinstance(outputs["images"]				,			np.ndarray					)
       assert outputs["images"].shape == (1, 3, 4, 4)
       assert isinstance(outputs[0]				,			np.ndarray					)
       assert outputs[0].shape == (1, 3, 4, 4)
  
       # test with a non-tensor attribute
       UpperCamelCase_     =CustomOutput({"images": [PIL.Image.new("RGB"				,			(4, 4)					)]}					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			UpperCamelCase_					)
       assert isinstance(outputs.images[0]				,			PIL.Image.Image					)
       assert isinstance(outputs["images"]				,			UpperCamelCase_					)
       assert isinstance(outputs["images"][0]				,			PIL.Image.Image					)
       assert isinstance(outputs[0]				,			UpperCamelCase_					)
       assert isinstance(outputs[0][0]				,			PIL.Image.Image					)
  