




'''simple docstring'''



from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


UpperCAmelCase_       :  Any      =		logging.get_logger(__name__)

UpperCAmelCase_       :  Tuple      =		{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase_       :  Optional[int]      =		{
    '''vocab_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/vocab.json'''},
    '''merges_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/merges.txt'''},
    '''tokenizer_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'''},
}

UpperCAmelCase_       :  Dict      =		{
    '''openai-gpt''': 5_1_2,
}





class     lowerCAmelCase   ( __lowerCAmelCase):
       __lowercase  :      str        =			VOCAB_FILES_NAMES
       __lowercase  :      Tuple        =			PRETRAINED_VOCAB_FILES_MAP
       __lowercase  :      str        =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase  :      List[str]        =			['''input_ids''', '''attention_mask''']
       __lowercase  :      Union[str, Any]        =			OpenAIGPTTokenizer


       def __init__(   self    ,  __SCREAMING_SNAKE_CASE=None    ,  __SCREAMING_SNAKE_CASE=None    ,  __SCREAMING_SNAKE_CASE=None    ,  __SCREAMING_SNAKE_CASE="<unk>"    ,  **__SCREAMING_SNAKE_CASE  )      ->  List[Any]:



            '''simple docstring'''




            super().__init__(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  tokenizer_file=__SCREAMING_SNAKE_CASE    ,  unk_token=__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )


       @property
       def       lowerCAmelCase      (   self  )      ->  int:



            '''simple docstring'''




            return True




       def       lowerCAmelCase      (   self    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE = None  )      ->  Tuple[str]:



            '''simple docstring'''




            __snake_case    					=  self._tokenizer.model.save(__SCREAMING_SNAKE_CASE    ,  name=__SCREAMING_SNAKE_CASE  )
            return tuple(__SCREAMING_SNAKE_CASE  )





'''simple docstring'''



from datetime import date

import requests

UpperCAmelCase_       :  str      =		'''https://api.carbonintensity.org.uk/intensity'''







def 			_UpperCamelCase ()->   str:




     '''simple docstring'''





     __snake_case    					=  requests.get(_lowerCamelCase	).json()['''data'''][0]
     return last_half_hour["intensity"]["actual"]







def 			_UpperCamelCase (_lowerCamelCase							:     Dict   ,	_lowerCamelCase							:     List[Any]	)->   list:




     '''simple docstring'''





     return requests.get(f'''{BASE_URL}/{start}/{end}'''	).json()["data"]


if __name__ == "__main__":
     for entry in fetch_from_to(start=date(2_0_2_0, 1_0, 1), end=date(2_0_2_0, 1_0, 3)):
          print('''from {from} to {to}: {intensity[actual]}'''.format(**entry))
     print(F"""{fetch_last_half_hour() = }""")






