


from typing import TYPE_CHECKING

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


_snake_case					=					{
    '''configuration_donut_swin''': ['''DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DonutSwinConfig'''],
    '''processing_donut''': ['''DonutProcessor'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''DonutSwinModel''',
       '''DonutSwinPreTrainedModel''',
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					['''DonutFeatureExtractor''']
   _snake_case					=					['''DonutImageProcessor''']


if TYPE_CHECKING:
   from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
   from .processing_donut import DonutProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_donut_swin import (
          DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
          DonutSwinModel,
          DonutSwinPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_donut import DonutFeatureExtractor
      from .image_processing_donut import DonutImageProcessor

else:
   import sys

   _snake_case					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







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      UpperCAmelCase_ ( unittest.TestCase		,			UpperCamelCase   ):

   '''simple docstring'''




   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[Any]   =    load_tool("image-segmentation"			)
     self.tool.setup()
     lowerCamelCase			: Optional[Any]   =    load_tool("image-segmentation"						,    remote=__A			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[str]   =    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
     lowerCamelCase			: Dict   =    self.tool(__A						,    "cat"			)
     self.assertTrue(isinstance(__A						,    Image.Image			)			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: int   =    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
     lowerCamelCase			: int   =    self.remote_tool(__A						,    "cat"			)
     self.assertTrue(isinstance(__A						,    Image.Image			)			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Optional[int]   =    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
     lowerCamelCase			: Optional[Any]   =    self.tool(image=__A						,    label="cat"			)
     self.assertTrue(isinstance(__A						,    Image.Image			)			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: str   =    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"			)			) / "000000039769.png"			)
     lowerCamelCase			: Dict   =    self.remote_tool(image=__A						,    label="cat"			)
     self.assertTrue(isinstance(__A						,    Image.Image			)			)



