



from .integrations import (
    is_optuna_available,
    is_ray_available,
    is_sigopt_available,
    is_wandb_available,
    run_hp_search_optuna,
    run_hp_search_ray,
    run_hp_search_sigopt,
    run_hp_search_wandb,
)
from .trainer_utils import (
    HPSearchBackend,
    default_hp_space_optuna,
    default_hp_space_ray,
    default_hp_space_sigopt,
    default_hp_space_wandb,
)
from .utils import logging


a_								=    logging.get_logger(__name__)



class        __lowerCAmelCase   :
 lowerCAmelCase__				    =     42
 lowerCAmelCase__				    =     None




 @staticmethod
 def 				lowerCamelCase					(  ):



    '''simple docstring'''
    raise NotImplementedError




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    raise NotImplementedError




 def 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    raise NotImplementedError




 def 				lowerCamelCase					(  self ):



    '''simple docstring'''



    if not self.is_available():
       raise RuntimeError(
           F"""You picked the {self.name} backend, but it is not installed. Run {self.pip_install()}.""" )




 @classmethod
 def 				lowerCamelCase					(  cls ):



    '''simple docstring'''
    return F"""`pip install {cls.pip_package or cls.name}`"""



class        __lowerCAmelCase   (		_a      ):
 lowerCAmelCase__				    =     '''optuna'''




 @staticmethod
 def 				lowerCamelCase					(  ):



    '''simple docstring'''
    return is_optuna_available()




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    return run_hp_search_optuna(__UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase )




 def 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    return default_hp_space_optuna(__UpperCAmelCase )



class        __lowerCAmelCase   (		_a      ):
 lowerCAmelCase__				    =     '''ray'''
 lowerCAmelCase__				    =     '''\'ray[tune]\''''




 @staticmethod
 def 				lowerCamelCase					(  ):



    '''simple docstring'''
    return is_ray_available()




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    return run_hp_search_ray(__UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase )




 def 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    return default_hp_space_ray(__UpperCAmelCase )



class        __lowerCAmelCase   (		_a      ):
 lowerCAmelCase__				    =     '''sigopt'''




 @staticmethod
 def 				lowerCamelCase					(  ):



    '''simple docstring'''
    return is_sigopt_available()




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    return run_hp_search_sigopt(__UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase )




 def 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    return default_hp_space_sigopt(__UpperCAmelCase )



class        __lowerCAmelCase   (		_a      ):
 lowerCAmelCase__				    =     '''wandb'''




 @staticmethod
 def 				lowerCamelCase					(  ):



    '''simple docstring'''
    return is_wandb_available()




 def 				lowerCamelCase					(  self		, __UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase ):



    '''simple docstring'''
    return run_hp_search_wandb(__UpperCAmelCase		, __UpperCAmelCase		, __UpperCAmelCase		, **__UpperCAmelCase )




 def 				lowerCamelCase					(  self		, __UpperCAmelCase ):



    '''simple docstring'''
    return default_hp_space_wandb(__UpperCAmelCase )



a_								=    {
    HPSearchBackend(backend.name): backend for backend in [OptunaBackend, RayTuneBackend, SigOptBackend, WandbBackend]
}





def 						a__	(						):
   __lowerCamelCase  							=			[backend for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values() if backend.is_available()]
   if len(_UpperCamelCase							) > 0:
      __lowerCamelCase  							=			available_backends[0].name
      if len(_UpperCamelCase							) > 1:
         logger.info(
             F"""{len(_UpperCamelCase							)} hyperparameter search backends available. Using {name} as the default."""							)
      return name
   raise RuntimeError(
       '''No hyperparameter search backend available.\n'''
       + '''\n'''.join(
           F""" - To install {backend.name} run {backend.pip_install()}"""
           for backend in ALL_HYPERPARAMETER_SEARCH_BACKENDS.values()							)							)













import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class 					__lowerCAmelCase       (			_a,     unittest.TestCase     ):
			lowerCamelCase_     :     Any       			=      BioGptTokenizer
			lowerCamelCase_     :     Optional[Any]       			=      False






			def 			lowerCamelCase  (self    )     ->   List[Any]:


							'''simple docstring'''



							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							snake_case_						:    Optional[Any]				=  [
							    '''l''',
							    '''o''',
							    '''w''',
							    '''e''',
							    '''r''',
							    '''s''',
							    '''t''',
							    '''i''',
							    '''d''',
							    '''n''',
							    '''w</w>''',
							    '''r</w>''',
							    '''t</w>''',
							    '''lo''',
							    '''low''',
							    '''er</w>''',
							    '''low</w>''',
							    '''lowest</w>''',
							    '''newer</w>''',
							    '''wider</w>''',
							    '''<unk>''',
							]
							snake_case_						:    Union[str, Any]				=  dict(zip(__magic_name__					,							range(len(__magic_name__    )    )    )    )
							snake_case_						:    Union[str, Any]				=  ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

							snake_case_						:    Any				=  os.path.join(self.tmpdirname					,							VOCAB_FILES_NAMES['''vocab_file''']    )
							snake_case_						:    Dict				=  os.path.join(self.tmpdirname					,							VOCAB_FILES_NAMES['''merges_file''']    )
							with open(self.vocab_file					,							'''w'''    ) as fp:
											fp.write(json.dumps(__magic_name__    )    )
							with open(self.merges_file					,							'''w'''    ) as fp:
											fp.write('''\n'''.join(__magic_name__    )    )






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   int:


							'''simple docstring'''



							snake_case_						:    str				=  '''lower newer'''
							snake_case_						:    Dict				=  '''lower newer'''
							return input_text, output_text






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


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer(self.vocab_file					,							self.merges_file    )

							snake_case_						:    Union[str, Any]				=  '''lower'''
							snake_case_						:    Optional[int]				=  ['''low''', '''er</w>''']
							snake_case_						:    Any				=  tokenizer.tokenize(__magic_name__    )
							self.assertListEqual(__magic_name__					,							__magic_name__    )

							snake_case_						:    Optional[int]				=  tokens + ['''<unk>''']
							snake_case_						:    List[str]				=  [14, 15, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__    )					,							__magic_name__    )






			@slow
			def 			lowerCamelCase  (self    )     ->   Optional[Any]:


							'''simple docstring'''



							snake_case_						:    Optional[int]				=  BioGptTokenizer.from_pretrained('''microsoft/biogpt'''    )

							snake_case_						:    List[Any]				=  tokenizer.encode('''sequence builders'''					,							add_special_tokens=__magic_name__    )
							snake_case_						:    str				=  tokenizer.encode('''multi-sequence build'''					,							add_special_tokens=__magic_name__    )

							snake_case_						:    str				=  tokenizer.build_inputs_with_special_tokens(__magic_name__    )
							snake_case_						:    List[str]				=  tokenizer.build_inputs_with_special_tokens(__magic_name__					,							__magic_name__    )

							self.assertTrue(encoded_sentence == [2] + text    )
							self.assertTrue(encoded_pair == [2] + text + [2] + text_a    )
