





'''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 				_a   (unittest.TestCase,		a__  ):





     '''simple docstring'''



     def  snake_case_			(							self       )			->							int:
          snake_case :			int					   = load_tool("""image-question-answering"""       )
          self.tool.setup()
          snake_case :			Dict					   = load_tool("""image-question-answering"""       ,remote=__a       )







     def  snake_case_			(							self       )			->							Any:
          snake_case :			str					   = Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
          snake_case :			Tuple					   = self.tool(__a       ,"""How many cats are sleeping on the couch?"""       )
          self.assertEqual(__a       ,"""2"""       )







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







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







     def  snake_case_			(							self       )			->							Dict:
          snake_case :			Optional[Any]					   = Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
          snake_case :			str					   = 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_sentencepiece_available, is_torch_available


lowercase			:      Tuple			=					{"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      Tuple			=					["""BertGenerationTokenizer"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase			:      List[Any]			=					[
          """BertGenerationDecoder""",
          """BertGenerationEncoder""",
          """BertGenerationPreTrainedModel""",
          """load_tf_weights_in_bert_generation""",
      ]


if TYPE_CHECKING:
      from .configuration_bert_generation import BertGenerationConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_bert_generation import BertGenerationTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_bert_generation import (
                BertGenerationDecoder,
                BertGenerationEncoder,
                BertGenerationPreTrainedModel,
                load_tf_weights_in_bert_generation,
            )

else:
      import sys

      lowercase			:      Optional[Any]			=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



