






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_	:	Any				=				logging.get_logger(__name__)

A_	:	Tuple				=				{
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}




class        _lowerCAmelCase( UpperCAmelCase_      ):





							"""simple docstring"""







							a       :	List[Any]								='''electra'''





							def __init__(      self						,    _lowerCamelCase=3_0_5_2_2						,    _lowerCamelCase=1_2_8						,    _lowerCamelCase=2_5_6						,    _lowerCamelCase=1_2						,    _lowerCamelCase=4						,    _lowerCamelCase=1_0_2_4						,    _lowerCamelCase="gelu"						,    _lowerCamelCase=0.1						,    _lowerCamelCase=0.1						,    _lowerCamelCase=5_1_2						,    _lowerCamelCase=2						,    _lowerCamelCase=0.0_2						,    _lowerCamelCase=1e-12						,    _lowerCamelCase="first"						,    _lowerCamelCase=True						,    _lowerCamelCase="gelu"						,    _lowerCamelCase=0.1						,    _lowerCamelCase=0						,    _lowerCamelCase="absolute"						,    _lowerCamelCase=True						,    _lowerCamelCase=None						,    **_lowerCamelCase						,    ):
									super().__init__(pad_token_id=_lowerCamelCase						,    **_lowerCamelCase							)

									UpperCamelCase_:      Union[str, Any]					   =       vocab_size
									UpperCamelCase_:      Tuple					   =       embedding_size
									UpperCamelCase_:      Optional[Any]					   =       hidden_size
									UpperCamelCase_:      int					   =       num_hidden_layers
									UpperCamelCase_:      Optional[Any]					   =       num_attention_heads
									UpperCamelCase_:      Union[str, Any]					   =       intermediate_size
									UpperCamelCase_:      Optional[int]					   =       hidden_act
									UpperCamelCase_:      Optional[int]					   =       hidden_dropout_prob
									UpperCamelCase_:      Tuple					   =       attention_probs_dropout_prob
									UpperCamelCase_:      List[Any]					   =       max_position_embeddings
									UpperCamelCase_:      Tuple					   =       type_vocab_size
									UpperCamelCase_:      int					   =       initializer_range
									UpperCamelCase_:      Any					   =       layer_norm_eps

									UpperCamelCase_:      Any					   =       summary_type
									UpperCamelCase_:      Union[str, Any]					   =       summary_use_proj
									UpperCamelCase_:      List[Any]					   =       summary_activation
									UpperCamelCase_:      str					   =       summary_last_dropout
									UpperCamelCase_:      Tuple					   =       position_embedding_type
									UpperCamelCase_:      Dict					   =       use_cache
									UpperCamelCase_:      List[str]					   =       classifier_dropout







class        _lowerCAmelCase( UpperCAmelCase_      ):





							"""simple docstring"""







							@property
							def     _a					(      self							):







									if self.task == "multiple-choice":
											UpperCamelCase_:      int					   =       {0: 'batch', 1: 'choice', 2: 'sequence'}
									else:
											UpperCamelCase_:      Optional[int]					   =       {0: 'batch', 1: 'sequence'}
									return OrderedDict(
									    [
									        ('input_ids', dynamic_axis),
									        ('attention_mask', dynamic_axis),
									        ('token_type_ids', dynamic_axis),
									    ]							)







from datetime import date

import requests

A_	:	Any				=				'https://api.carbonintensity.org.uk/intensity'

def 						snake_case      () ->       str:
  UpperCamelCase_:      Any					   =       requests.get(UpperCAmelCase__						).json()['data'][0]
  return last_half_hour["intensity"]["actual"]

def 						snake_case      (UpperCAmelCase__			,					UpperCAmelCase__						) ->       list:
  return requests.get(F'''{BASE_URL}/{start}/{end}'''						).json()["data"]


if __name__ == "__main__":
   for entry in fetch_from_to(start=date(2020, 10, 1), end=date(2020, 10, 3)):
      print('from {from} to {to}: {intensity[actual]}'.format(**entry))
   print(F'''{fetch_last_half_hour() = }''')