


import unittest

from datasets import load_dataset

from transformers import load_tool

from .test_tools_common import ToolTesterMixin



class 			a      (      unittest.TestCase      ,UpperCamelCase_   ):






		def       lowerCAmelCase_  (  self							)->			Tuple:
						'''simple docstring'''


						A__     :							Optional[int]   				=load_tool('''document-question-answering'''							)
						self.tool.setup()
						A__     :							str   				=load_tool('''document-question-answering'''	,     remote=__UpperCamelCase							)






		def       lowerCAmelCase_  (  self							)->			Tuple:
						'''simple docstring'''


						A__     :							Dict   				=load_dataset('''hf-internal-testing/example-documents'''	,     split='''test'''							)
						A__     :							List[str]   				=dataset[0]['''image''']

						A__     :							Tuple   				=self.tool(__UpperCamelCase	,     '''When is the coffee break?'''							)
						self.assertEqual(__UpperCamelCase	,     '''11-14 to 11:39 a.m.'''							)






		def       lowerCAmelCase_  (  self							)->			List[str]:
						'''simple docstring'''


						A__     :							str   				=load_dataset('''hf-internal-testing/example-documents'''	,     split='''test'''							)
						A__     :							str   				=dataset[0]['''image''']

						A__     :							Tuple   				=self.remote_tool(__UpperCamelCase	,     '''When is the coffee break?'''							)
						self.assertEqual(__UpperCamelCase	,     '''11-14 to 11:39 a.m.'''							)






		def       lowerCAmelCase_  (  self							)->			Tuple:
						'''simple docstring'''


						A__     :							Tuple   				=load_dataset('''hf-internal-testing/example-documents'''	,     split='''test'''							)
						A__     :							Optional[int]   				=dataset[0]['''image''']

						self.tool(document=__UpperCamelCase	,     question='''When is the coffee break?'''							)






		def       lowerCAmelCase_  (  self							)->			Optional[int]:
						'''simple docstring'''


						A__     :							Optional[int]   				=load_dataset('''hf-internal-testing/example-documents'''	,     split='''test'''							)
						A__     :							List[Any]   				=dataset[0]['''image''']

						A__     :							Tuple   				=self.remote_tool(document=__UpperCamelCase	,     question='''When is the coffee break?'''							)
						self.assertEqual(__UpperCamelCase	,     '''11-14 to 11:39 a.m.'''							)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowerCamelCase       :       str				   =			{
    "configuration_align": [
        "ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AlignConfig",
        "AlignTextConfig",
        "AlignVisionConfig",
    ],
    "processing_align": ["AlignProcessor"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase       :       Dict				   =			[
						    "ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "AlignModel",
						    "AlignPreTrainedModel",
						    "AlignTextModel",
						    "AlignVisionModel",
						]

if TYPE_CHECKING:
						from .configuration_align import (
						    ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    AlignConfig,
						    AlignTextConfig,
						    AlignVisionConfig,
						)
						from .processing_align import AlignProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_align import (
												    ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
												    AlignModel,
												    AlignPreTrainedModel,
												    AlignTextModel,
												    AlignVisionModel,
												)

else:
						import sys

						__lowerCamelCase       :       List[str]				   =			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



