




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:
	__A						:		List[Any]          =						False


if is_vision_available():
	from PIL import Image
else:

	class 		lowercase_       :




						@staticmethod
						def     _lowercase						(   *_lowercase:		List[Any],     **_lowercase:		Optional[Any]):


										'''simple docstring'''


										pass

@is_pipeline_test
@require_vision
class 		lowercase_       (	unittest.TestCase				):
					__UpperCamelCase     	= MODEL_FOR_VISION_2_SEQ_MAPPING
					__UpperCamelCase     	= TF_MODEL_FOR_VISION_2_SEQ_MAPPING




					def     _lowercase						(   self:		Optional[Any],     _lowercase:		Union[str, Any],     _lowercase:		List[str],     _lowercase:		List[Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model=_lowercase,     tokenizer=_lowercase,     image_processor=_lowercase)
									__lowerCAmelCase					=  [
									    Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""),
									    """./tests/fixtures/tests_samples/COCO/000000039769.png""",
									]
									return pipe, examples




					def     _lowercase						(   self:		str,     _lowercase:		int,     _lowercase:		int):


									'''simple docstring'''


									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(
									    _lowercase,     [
									        [{"""generated_text""": ANY(_lowercase)}],
									        [{"""generated_text""": ANY(_lowercase)}],
									    ],     )




					@require_tf
					def     _lowercase						(   self:		Optional[Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""hf-internal-testing/tiny-random-vit-gpt2""",     framework="""tf""")
									__lowerCAmelCase					=  """./tests/fixtures/tests_samples/COCO/000000039769.png"""

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(
									    _lowercase,     [
									        {
									            """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									        },
									    ],     )

									__lowerCAmelCase					=  pipe([image, image])
									self.assertEqual(
									    _lowercase,     [
									        [
									            {
									                """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									            }
									        ],
									        [
									            {
									                """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									            }
									        ],
									    ],     )

									__lowerCAmelCase					=  pipe(_lowercase,     max_new_tokens=1)
									self.assertEqual(
									    _lowercase,     [{"""generated_text""": """growth"""}],     )




					@require_torch
					def     _lowercase						(   self:		Any):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""hf-internal-testing/tiny-random-vit-gpt2""")
									__lowerCAmelCase					=  """./tests/fixtures/tests_samples/COCO/000000039769.png"""

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(
									    _lowercase,     [
									        {
									            """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									        },
									    ],     )

									__lowerCAmelCase					=  pipe([image, image])
									self.assertEqual(
									    _lowercase,     [
									        [
									            {
									                """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									            }
									        ],
									        [
									            {
									                """generated_text""": """growthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthgrowthGOGO"""
									            }
									        ],
									    ],     )




					@require_torch
					def     _lowercase						(   self:		Dict):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""hf-internal-testing/tiny-random-BlipForConditionalGeneration""")
									__lowerCAmelCase					=  """./tests/fixtures/tests_samples/COCO/000000039769.png"""
									__lowerCAmelCase					=  """a photo of"""

									__lowerCAmelCase					=  pipe(_lowercase,     prompt=_lowercase)
									self.assertTrue(outputs[0]["""generated_text"""].startswith(_lowercase))




					@slow
					@require_torch
					def     _lowercase						(   self:		List[Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""ydshieh/vit-gpt2-coco-en""")
									__lowerCAmelCase					=  """./tests/fixtures/tests_samples/COCO/000000039769.png"""

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a cat laying on a blanket next to a cat laying on a bed """}])

									__lowerCAmelCase					=  pipe([image, image])
									self.assertEqual(
									    _lowercase,     [
									        [{"""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     _lowercase						(   self:		Any):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""Salesforce/blip-image-captioning-base""")
									__lowerCAmelCase					=  """https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/pokemon.png"""
									__lowerCAmelCase					=  Image.open(requests.get(_lowercase,     stream=_lowercase).raw)

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a pink pokemon pokemon with a blue shirt and a blue shirt"""}])




					@slow
					@require_torch
					def     _lowercase						(   self:		Union[str, Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""microsoft/git-base-coco""")
									__lowerCAmelCase					=  """https://huggingface.co/datasets/sayakpaul/sample-datasets/resolve/main/pokemon.png"""
									__lowerCAmelCase					=  Image.open(requests.get(_lowercase,     stream=_lowercase).raw)

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a cartoon of a purple character."""}])




					@slow
					@require_torch
					def     _lowercase						(   self:		Tuple):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""Salesforce/blip-image-captioning-base""")
									__lowerCAmelCase					=  """https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"""
									__lowerCAmelCase					=  Image.open(requests.get(_lowercase,     stream=_lowercase).raw)

									__lowerCAmelCase					=  """a photography of"""

									__lowerCAmelCase					=  pipe(_lowercase,     prompt=_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a photography of a volcano"""}])

									with self.assertRaises(_lowercase):
													__lowerCAmelCase					=  pipe([image, image],     prompt=[prompt, prompt])




					@slow
					@require_torch
					def     _lowercase						(   self:		List[str]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""microsoft/git-base-coco""")
									__lowerCAmelCase					=  """https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"""
									__lowerCAmelCase					=  Image.open(requests.get(_lowercase,     stream=_lowercase).raw)

									__lowerCAmelCase					=  """a photo of a"""

									__lowerCAmelCase					=  pipe(_lowercase,     prompt=_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a photo of a tent with a tent and a tent in the background."""}])

									with self.assertRaises(_lowercase):
													__lowerCAmelCase					=  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     _lowercase						(   self:		Union[str, Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""google/pix2struct-ai2d-base""")
									__lowerCAmelCase					=  """https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"""
									__lowerCAmelCase					=  Image.open(requests.get(_lowercase,     stream=_lowercase).raw)

									__lowerCAmelCase					=  """What does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud"""

									__lowerCAmelCase					=  pipe(_lowercase,     prompt=_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """ash cloud"""}])

									with self.assertRaises(_lowercase):
													__lowerCAmelCase					=  pipe([image, image],     prompt=[prompt, prompt])







					@slow
					@require_tf
					def     _lowercase						(   self:		Any):


									'''simple docstring'''


									__lowerCAmelCase					=  pipeline("""image-to-text""",     model="""ydshieh/vit-gpt2-coco-en""",     framework="""tf""")
									__lowerCAmelCase					=  """./tests/fixtures/tests_samples/COCO/000000039769.png"""

									__lowerCAmelCase					=  pipe(_lowercase)
									self.assertEqual(_lowercase,     [{"""generated_text""": """a cat laying on a blanket next to a cat laying on a bed """}])

									__lowerCAmelCase					=  pipe([image, image])
									self.assertEqual(
									    _lowercase,     [
									        [{"""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 """}],
									    ],     )







from __future__ import annotations

from typing import Any

class        UpperCamelCase__:

	"""simple docstring"""

	def __init__(      self				:			Dict							,			snake_case__				:			Any							,			snake_case__				:			Any ):  # noqa: A002
			"""simple docstring"""





			A				=item
			A				=next


class        UpperCamelCase__:

	"""simple docstring"""

	def __init__(      self				:			Optional[Any] ):
			"""simple docstring"""





			A				=None
			A				=0







	def        _a					(      self				:			str							,			snake_case__				:			Any ):
			"""simple docstring"""





			A				=Node(snake_case__							,			self.head )
			self.size += 1







	def        _a					(      self				:			Dict ):
			"""simple docstring"""





			if self.head is None:
					return None
			else:
					A				=self.head.item
					A				=self.head.next
					self.size -= 1
					return item







	def        _a					(      self				:			Any ):
			"""simple docstring"""





			return self.head is None







	def __str__(      self				:			Dict ):
			"""simple docstring"""





			if self.is_empty():
					return ""
			else:
					A				=self.head
					A				=""
					A				=[]
					while iterate:
							item_list.append(str(iterate.item ) )
							A				=iterate.next

					A				=" --> ".join(snake_case__ )

					return item_str







	def __len__(      self				:			Union[str, Any] ):
			"""simple docstring"""





			return self.size




