






import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format

class 				lowerCAmelCase_	:
				_UpperCamelCase					:       Dict							       = None


				def 						__a					(					self      ):
											_lowercase							:   Dict 							=   self.feature_extraction_class(**self.feat_extract_dict      )
											_lowercase							:   Dict 							=   json.loads(feat_extract.to_json_string()      )
											for key, value in self.feat_extract_dict.items():
																		self.assertEqual(obj[key] ,						_lowerCAmelCase      )


				def 						__a					(					self      ):
											_lowercase							:   str 							=   self.feature_extraction_class(**self.feat_extract_dict      )

											with tempfile.TemporaryDirectory() as tmpdirname:
																		_lowercase							:   Tuple 							=   os.path.join(_lowerCAmelCase ,						'feat_extract.json'      )
																		feat_extract_first.to_json_file(_lowerCAmelCase      )
																		_lowercase							:   str 							=   self.feature_extraction_class.from_json_file(_lowerCAmelCase      )

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


				def 						__a					(					self      ):
											_lowercase							:   Union[str, Any] 							=   self.feature_extraction_class(**self.feat_extract_dict      )

											with tempfile.TemporaryDirectory() as tmpdirname:
																		_lowercase							:   int 							=   feat_extract_first.save_pretrained(_lowerCAmelCase      )[0]
																		check_json_file_has_correct_format(_lowerCAmelCase      )
																		_lowercase							:   int 							=   self.feature_extraction_class.from_pretrained(_lowerCAmelCase      )

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


				def 						__a					(					self      ):
											_lowercase							:   Any 							=   self.feature_extraction_class()
											self.assertIsNotNone(_lowerCAmelCase      )





'''simple docstring'''






import os
from pathlib import Path





def  _SCREAMING_SNAKE_CASE		(      ):
     from torch.utils.cpp_extension import load

     _A    		=  Path(__snake_case				).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
     _A    		=  [
         root / filename
         for filename in [
             'vision.cpp',
             os.path.join('cpu'   ,		'ms_deform_attn_cpu.cpp'				),
             os.path.join('cuda'   ,		'ms_deform_attn_cuda.cu'				),
         ]
     ]

     load(
         'MultiScaleDeformableAttention'   ,		__snake_case   ,		with_cuda=__snake_case   ,		extra_include_paths=[str(__snake_case				)]   ,		extra_cflags=['-DWITH_CUDA=1']   ,		extra_cuda_cflags=[
             '-DCUDA_HAS_FP16=1',
             '-D__CUDA_NO_HALF_OPERATORS__',
             '-D__CUDA_NO_HALF_CONVERSIONS__',
             '-D__CUDA_NO_HALF2_OPERATORS__',
         ]   ,		)

     import MultiScaleDeformableAttention as MSDA

     return MSDA



