


import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format
class 	lowerCamelCase_       :



					'''simple docstring'''







					__UpperCAmelCase            =				None






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







								'''simple docstring'''

								__lowercase 					=   self.feature_extraction_class(**self.feat_extract_dict						)
								__lowercase 					=   json.loads(feat_extract.to_json_string()						)
								for key, value in self.feat_extract_dict.items():
											self.assertEqual(obj[key] ,       snake_case_						)






					def A      (				self						)   ->			Union[str, Any]:







								'''simple docstring'''

								__lowercase 					=   self.feature_extraction_class(**self.feat_extract_dict						)

								with tempfile.TemporaryDirectory() as tmpdirname:
											__lowercase 					=   os.path.join(snake_case_ ,       '''feat_extract.json'''						)
											feat_extract_first.to_json_file(snake_case_						)
											__lowercase 					=   self.feature_extraction_class.from_json_file(snake_case_						)

								self.assertEqual(feat_extract_second.to_dict() ,       feat_extract_first.to_dict()						)






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







								'''simple docstring'''

								__lowercase 					=   self.feature_extraction_class(**self.feat_extract_dict						)

								with tempfile.TemporaryDirectory() as tmpdirname:
											__lowercase 					=   feat_extract_first.save_pretrained(snake_case_						)[0]
											check_json_file_has_correct_format(snake_case_						)
											__lowercase 					=   self.feature_extraction_class.from_pretrained(snake_case_						)

								self.assertEqual(feat_extract_second.to_dict() ,       feat_extract_first.to_dict()						)






					def A      (				self						)   ->			int:







								'''simple docstring'''

								__lowercase 					=   self.feature_extraction_class()
								self.assertIsNotNone(snake_case_						)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a : List[str]		=				{
    '''configuration_table_transformer''': [
        '''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TableTransformerConfig''',
        '''TableTransformerOnnxConfig''',
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a : Union[str, Any]		=				[
	    '''TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TableTransformerForObjectDetection''',
	    '''TableTransformerModel''',
	    '''TableTransformerPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_table_transformer import (
	    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TableTransformerConfig,
	    TableTransformerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_table_transformer import (
		    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TableTransformerForObjectDetection,
		    TableTransformerModel,
		    TableTransformerPreTrainedModel,
		)

else:
	import sys

	a : Any		=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


