



'''simple docstring'''
import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
     from PIL import Image


class   SCREAMING_SNAKE_CASE__				(   unittest.TestCase     ,			snake_case_					):
 """simple docstring"""


 def      a__ (		self			) ->							Union[str, Any]:
    A:      Any														=   load_tool("""image-question-answering"""			)
    self.tool.setup()
    A:      Optional[Any]														=   load_tool("""image-question-answering"""					,   remote=A			)


 def      a__ (		self			) ->							List[str]:
    A:      Dict														=   Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""			)			) / """000000039769.png"""			)
    A:      List[str]														=   self.tool(A					,   """How many cats are sleeping on the couch?"""			)
    self.assertEqual(A					,   """2"""			)


 def      a__ (		self			) ->							Tuple:
    A:      List[str]														=   Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""			)			) / """000000039769.png"""			)
    A:      List[str]														=   self.remote_tool(A					,   """How many cats are sleeping on the couch?"""			)
    self.assertEqual(A					,   """2"""			)


 def      a__ (		self			) ->							Dict:
    A:      List[Any]														=   Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""			)			) / """000000039769.png"""			)
    A:      List[Any]														=   self.tool(image=A					,   question="""How many cats are sleeping on the couch?"""			)
    self.assertEqual(A					,   """2"""			)





 def      a__ (		self			) ->							Optional[int]:
    A:      Optional[Any]														=   Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""			)			) / """000000039769.png"""			)
    A:      int														=   self.remote_tool(image=A					,   question="""How many cats are sleeping on the couch?"""			)
    self.assertEqual(A					,   """2"""			)










'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__SCREAMING_SNAKE_CASE :      Dict             ={
    'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE :      Dict             =[
					    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'NystromformerForMaskedLM',
					    'NystromformerForMultipleChoice',
					    'NystromformerForQuestionAnswering',
					    'NystromformerForSequenceClassification',
					    'NystromformerForTokenClassification',
					    'NystromformerLayer',
					    'NystromformerModel',
					    'NystromformerPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_nystromformer import (
										    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    NystromformerForMaskedLM,
										    NystromformerForMultipleChoice,
										    NystromformerForQuestionAnswering,
										    NystromformerForSequenceClassification,
										    NystromformerForTokenClassification,
										    NystromformerLayer,
										    NystromformerModel,
										    NystromformerPreTrainedModel,
										)


else:
					import sys

					__SCREAMING_SNAKE_CASE :      Dict             =_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





