import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property



@unittest.skipUnless(os.path.exists(__lowercase )   ,  'Tatoeba directory does not exist.' )
class  UpperCamelCase				( unittest.TestCase ):

     '''simple docstring'''

     @cached_property
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           _lowerCamelCase			    =				tempfile.mkdtemp()
           return TatoebaConverter(save_dir=A_						)



     @slow
     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           self.resolver.convert_models(['''heb-eng''']						)





     @slow
     def 		UpperCamelCase_						(					self						) ->				Tuple:






           """simple docstring"""
           _lowerCamelCase    ,					_lowerCamelCase			    =				self.resolver.write_model_card('''opus-mt-he-en'''				,				dry_run=A_						)
           assert mmeta["long_pair"] == "heb-eng"
import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


snake_case__				= logging.get_logger(__name__)



class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     def __init__(					self				,				*A_				,				**A_						) ->				None:






           """simple docstring"""
           warnings.warn(
               '''The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
               ''' use DPTImageProcessor instead.'''				,				A_				,				)
           super().__init__(*A_				,				**A_						)