



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 						_snake_case					(	unittest.TestCase    ,a_ ):





 """simple docstring"""



 def lowercase_						(  self    )		->							Optional[int]:




   """simple docstring"""







   _A							=			load_tool('''image-segmentation'''    )
   self.tool.setup()
   _A							=			load_tool('''image-segmentation'''		,			remote=a    )
 def lowercase_						(  self    )		->							Optional[int]:




   """simple docstring"""







   _A							=			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
   _A							=			self.tool(a		,			'''cat'''    )
   self.assertTrue(isinstance(a		,			Image.Image    )    )
 def lowercase_						(  self    )		->							Union[str, Any]:




   """simple docstring"""







   _A							=			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
   _A							=			self.remote_tool(a		,			'''cat'''    )
   self.assertTrue(isinstance(a		,			Image.Image    )    )
 def lowercase_						(  self    )		->							Union[str, Any]:




   """simple docstring"""







   _A							=			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
   _A							=			self.tool(image=a		,			label='''cat'''    )
   self.assertTrue(isinstance(a		,			Image.Image    )    )



 def lowercase_						(  self    )		->							Optional[Any]:




   """simple docstring"""







   _A							=			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
   _A							=			self.remote_tool(image=a		,			label='''cat'''    )
   self.assertTrue(isinstance(a		,			Image.Image    )    )
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase							= {'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase							= [
     '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''NatForImageClassification''',
     '''NatModel''',
     '''NatPreTrainedModel''',
     '''NatBackbone''',
 ]

if TYPE_CHECKING:
 from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nat import (
      NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
      NatBackbone,
      NatForImageClassification,
      NatModel,
      NatPreTrainedModel,
  )

else:
 import sys

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



