code: 
  
  
  '''simple docstring'''
  
  import unittest
  
  import requests
  
  from transformers import MODEL_FOR_VISION_2_SEQ_MAPPING, TF_MODEL_FOR_VISION_2_SEQ_MAPPING, is_vision_available
  from transformers.pipelines import pipeline
  from transformers.testing_utils import (
      is_pipeline_test,
      is_torch_available,
      require_tf,
      require_torch,
      require_vision,
      slow,
  )
  
  from .test_pipelines_common import ANY
  
  
  if is_torch_available():
   from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
  else:
   lowerCamelCase							:     Dict								=			False
  
  
  if is_vision_available():
   from PIL import Image
  else:
   class 						__lowerCAmelCase		:
  
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         @staticmethod
         def    UpperCamelCase__	(*UpperCamelCase					:					Any     ,		**UpperCamelCase					:					List[Any]				):
  
                '''simple docstring'''
  
  
  
  
  
  
  
                pass
  @is_pipeline_test
  @require_vision
  class 						__lowerCAmelCase		(unittest.TestCase  ):
  
  
  
  
  
        '''simple docstring'''
  
  
  
  
  
  
        lowerCAmelCase__      :  int						      =							MODEL_FOR_VISION_2_SEQ_MAPPING
        lowerCAmelCase__      :  int						      =							TF_MODEL_FOR_VISION_2_SEQ_MAPPING
  
  
  
        def    UpperCamelCase__	(self					:					int     ,		UpperCamelCase					:					Union[str, Any]     ,		UpperCamelCase					:					Optional[int]     ,		UpperCamelCase					:					Union[str, Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model=UpperCamelCase     ,		tokenizer=UpperCamelCase     ,		image_processor=UpperCamelCase				)
               lowercase__       =				[
                   Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''				),
                   './tests/fixtures/tests_samples/COCO/000000039769.png',
               ]
               return pipe, examples
  
  
  
        def    UpperCamelCase__	(self					:					List[Any]     ,		UpperCamelCase					:					Any     ,		UpperCamelCase					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       [{'''generated_text''': ANY(UpperCamelCase				)}],
                       [{'''generated_text''': ANY(UpperCamelCase				)}],
                   ]     ,		)
  
  
  
        @require_tf
        def    UpperCamelCase__	(self					:					Union[str, Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''hf-internal-testing/tiny-random-vit-gpt2'''     ,		framework='''tf'''				)
               lowercase__       =				'./tests/fixtures/tests_samples/COCO/000000039769.png'
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       {
                           '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                       },
                   ]     ,		)
  
               lowercase__       =				pipe([image, image]				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       [
                           {
                               '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                           }
                       ],
                       [
                           {
                               '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                           }
                       ],
                   ]     ,		)
  
               lowercase__       =				pipe(UpperCamelCase     ,		max_new_tokens=1				)
               self.assertEqual(
                   UpperCamelCase     ,		[{'''generated_text''': '''growth'''}]     ,		)
  
  
  
        @require_torch
        def    UpperCamelCase__	(self					:					Tuple				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''hf-internal-testing/tiny-random-vit-gpt2'''				)
               lowercase__       =				'./tests/fixtures/tests_samples/COCO/000000039769.png'
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       {
                           '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                       },
                   ]     ,		)
  
               lowercase__       =				pipe([image, image]				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       [
                           {
                               '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                           }
                       ],
                       [
                           {
                               '''generated_text''': '''growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO'''
                           }
                       ],
                   ]     ,		)
  
  
  
        @require_torch
        def    UpperCamelCase__	(self					:					Dict				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''hf-internal-testing/tiny-random-BlipForConditionalGeneration'''				)
               lowercase__       =				'./tests/fixtures/tests_samples/COCO/000000039769.png'
               lowercase__       =				'a photo of'
  
               lowercase__       =				pipe(UpperCamelCase     ,		prompt=UpperCamelCase				)
               self.assertTrue(outputs[0]['''generated_text'''].startswith(UpperCamelCase				)				)
  
  
  
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					Union[str, Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''ydshieh/vit-gpt2-coco-en'''				)
               lowercase__       =				'./tests/fixtures/tests_samples/COCO/000000039769.png'
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}]				)
  
               lowercase__       =				pipe([image, image]				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       [{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}],
                       [{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}],
                   ]     ,		)
  
  
  
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					List[Any]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''Salesforce/blip-image-captioning-base'''				)
               lowercase__       =				'https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/pokemon.png'
               lowercase__       =				Image.open(requests.get(UpperCamelCase     ,		stream=UpperCamelCase				).raw				)
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a pink pokemon pokemon with a blue shirt and a blue shirt'''}]				)
  
  
  
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''microsoft/git-base-coco'''				)
               lowercase__       =				'https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/pokemon.png'
               lowercase__       =				Image.open(requests.get(UpperCamelCase     ,		stream=UpperCamelCase				).raw				)
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a cartoon of a purple character.'''}]				)
  
  
  
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					List[str]				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''Salesforce/blip-image-captioning-base'''				)
               lowercase__       =				'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg'
               lowercase__       =				Image.open(requests.get(UpperCamelCase     ,		stream=UpperCamelCase				).raw				)
  
               lowercase__       =				'a photography of'
  
               lowercase__       =				pipe(UpperCamelCase     ,		prompt=UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a photography of a volcano'''}]				)
  
               with self.assertRaises(UpperCamelCase				):
                      lowercase__       =				pipe([image, image]     ,		prompt=[prompt, prompt]				)
  
  
  
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					int				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''microsoft/git-base-coco'''				)
               lowercase__       =				'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg'
               lowercase__       =				Image.open(requests.get(UpperCamelCase     ,		stream=UpperCamelCase				).raw				)
  
               lowercase__       =				'a photo of a'
  
               lowercase__       =				pipe(UpperCamelCase     ,		prompt=UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a photo of a tent with a tent and a tent in the background.'''}]				)
  
               with self.assertRaises(UpperCamelCase				):
                      lowercase__       =				pipe([image, image]     ,		prompt=[prompt, prompt]				)
  
  
  
        @unittest.skipIf(
            not is_torch_greater_or_equal_than_1_11     ,		reason='''`Pix2StructImageProcessor` requires `torch>=1.11.0`.'''				)
        @slow
        @require_torch
        def    UpperCamelCase__	(self					:					Any				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''google/pix2struct-ai2d-base'''				)
               lowercase__       =				'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg'
               lowercase__       =				Image.open(requests.get(UpperCamelCase     ,		stream=UpperCamelCase				).raw				)
  
               lowercase__       =				'What does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud'
  
               lowercase__       =				pipe(UpperCamelCase     ,		prompt=UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''ash cloud'''}]				)
  
               with self.assertRaises(UpperCamelCase				):
                      lowercase__       =				pipe([image, image]     ,		prompt=[prompt, prompt]				)
  
  
  
  
  
  
        @slow
        @require_tf
        def    UpperCamelCase__	(self					:					Dict				):
  
               '''simple docstring'''
  
  
  
  
  
  
  
               lowercase__       =				pipeline('''image-to-text'''     ,		model='''ydshieh/vit-gpt2-coco-en'''     ,		framework='''tf'''				)
               lowercase__       =				'./tests/fixtures/tests_samples/COCO/000000039769.png'
  
               lowercase__       =				pipe(UpperCamelCase				)
               self.assertEqual(UpperCamelCase     ,		[{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}]				)
  
               lowercase__       =				pipe([image, image]				)
               self.assertEqual(
                   UpperCamelCase     ,		[
                       [{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}],
                       [{'''generated_text''': '''a cat laying on a blanket next to a cat laying on a bed '''}],
                   ]     ,		)
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
      is_vision_available,
  )
  
  
  lowerCamelCase							:     Optional[Any]								=			{
      'configuration_mobilevitv2': [
          'MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP',
          'MobileViTV2Config',
          'MobileViTV2OnnxConfig',
      ],
  }
  
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   lowerCamelCase							:     Optional[int]								=			[
       '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
  
   lowerCamelCase							:     Dict								=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  