
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 						lowercase       (  unittest.TestCase	,		__UpperCamelCase					):
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[int]				      =			load_tool('''image-segmentation'''    )
								self.tool.setup()
								lowerCAmelCase__ :    Optional[Any]				      =			load_tool('''image-segmentation''' ,	remote=SCREAMING_SNAKE_CASE__    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[int]				      =			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
								lowerCAmelCase__ :    Any				      =			self.tool(SCREAMING_SNAKE_CASE__ ,	'''cat'''    )
								self.assertTrue(isinstance(SCREAMING_SNAKE_CASE__ ,	Image.Image    )    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[int]				      =			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
								lowerCAmelCase__ :    int				      =			self.remote_tool(SCREAMING_SNAKE_CASE__ ,	'''cat'''    )
								self.assertTrue(isinstance(SCREAMING_SNAKE_CASE__ ,	Image.Image    )    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Dict				      =			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
								lowerCAmelCase__ :    Union[str, Any]				      =			self.tool(image=SCREAMING_SNAKE_CASE__ ,	label='''cat'''    )
								self.assertTrue(isinstance(SCREAMING_SNAKE_CASE__ ,	Image.Image    )    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[int]				      =			Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''    )    ) / '''000000039769.png'''    )
								lowerCAmelCase__ :    List[str]				      =			self.remote_tool(image=SCREAMING_SNAKE_CASE__ ,	label='''cat'''    )
								self.assertTrue(isinstance(SCREAMING_SNAKE_CASE__ ,	Image.Image    )    )





from typing import TYPE_CHECKING

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


A__       :   Union[str, Any]   						=					{"""configuration_cvt""": ["""CVT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CvtConfig"""]}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__       :   Union[str, Any]   						=					[
							    """CVT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """CvtForImageClassification""",
							    """CvtModel""",
							    """CvtPreTrainedModel""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__       :   str   						=					[
							    """TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFCvtForImageClassification""",
							    """TFCvtModel""",
							    """TFCvtPreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_cvt import (
														    CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CvtForImageClassification,
														    CvtModel,
														    CvtPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_cvt import (
														    TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFCvtForImageClassification,
														    TFCvtModel,
														    TFCvtPreTrainedModel,
														)


else:
							import sys

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



