
"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


a		:					str    	=					logging.get_logger(__name__)

a		:					Optional[int]    	=					{
    'flaubert/flaubert_small_cased': 'https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json',
    'flaubert/flaubert_base_uncased': 'https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json',
    'flaubert/flaubert_base_cased': 'https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json',
    'flaubert/flaubert_large_cased': 'https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json',
}







class 						lowercase(_lowercase					):
     __snake_case:  Optional[int]  				=    'flaubert'
     __snake_case:  int  				=    {
         'hidden_size': 'emb_dim',
         'num_attention_heads': 'n_heads',
         'num_hidden_layers': 'n_layers',
         'n_words': 'vocab_size',  # For backward compatibility
     }



     def __init__(       self    ,							__SCREAMING_SNAKE_CASE=False    ,							__SCREAMING_SNAKE_CASE=0.0    ,							__SCREAMING_SNAKE_CASE=3_0_1_4_5    ,							__SCREAMING_SNAKE_CASE=2_0_4_8    ,							__SCREAMING_SNAKE_CASE=1_2    ,							__SCREAMING_SNAKE_CASE=1_6    ,							__SCREAMING_SNAKE_CASE=0.1    ,							__SCREAMING_SNAKE_CASE=0.1    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=False    ,							__SCREAMING_SNAKE_CASE=False    ,							__SCREAMING_SNAKE_CASE=False    ,							__SCREAMING_SNAKE_CASE=1    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=5_1_2    ,							__SCREAMING_SNAKE_CASE=2_0_4_8**-0.5    ,							__SCREAMING_SNAKE_CASE=1e-12    ,							__SCREAMING_SNAKE_CASE=0.02    ,							__SCREAMING_SNAKE_CASE=0    ,							__SCREAMING_SNAKE_CASE=1    ,							__SCREAMING_SNAKE_CASE=2    ,							__SCREAMING_SNAKE_CASE=3    ,							__SCREAMING_SNAKE_CASE=5    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE="first"    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=None    ,							__SCREAMING_SNAKE_CASE=True    ,							__SCREAMING_SNAKE_CASE=0.1    ,							__SCREAMING_SNAKE_CASE=5    ,							__SCREAMING_SNAKE_CASE=5    ,							__SCREAMING_SNAKE_CASE=0    ,							__SCREAMING_SNAKE_CASE=0    ,							__SCREAMING_SNAKE_CASE=2    ,							__SCREAMING_SNAKE_CASE=0    ,							**__SCREAMING_SNAKE_CASE    ,							)		->    Optional[int]:







         """simple docstring"""



         a__    = pre_norm
         a__    = layerdrop
         a__    = vocab_size
         a__    = emb_dim
         a__    = n_layers
         a__    = n_heads
         a__    = dropout
         a__    = attention_dropout
         a__    = gelu_activation
         a__    = sinusoidal_embeddings
         a__    = causal
         a__    = asm
         a__    = n_langs
         a__    = use_lang_emb
         a__    = layer_norm_eps
         a__    = bos_index
         a__    = eos_index
         a__    = pad_index
         a__    = unk_index
         a__    = mask_index
         a__    = is_encoder
         a__    = max_position_embeddings
         a__    = embed_init_std
         a__    = init_std
         a__    = summary_type
         a__    = summary_use_proj
         a__    = summary_activation
         a__    = summary_proj_to_labels
         a__    = summary_first_dropout
         a__    = start_n_top
         a__    = end_n_top
         a__    = mask_token_id
         a__    = lang_id

         if "n_words" in kwargs:
             a__    = kwargs['n_words']

         super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE    ,							bos_token_id=__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )







class 						lowercase(_lowercase					):



     @property
     def  lowercase__     (       self      )		->    Mapping[str, Mapping[int, str]]:







         """simple docstring"""



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




"""simple docstring"""




import shutil

import requests



def 						__magic_name__		(				UpperCamelCase    :		str       ,		UpperCamelCase    :		bool = False       ,		UpperCamelCase    :		str = "."    )    ->	dict:
    a__    = 'https://api.nasa.gov/planetary/apod'
    return requests.get(UpperCamelCase       ,		params={'api_key': api_key}    ).json()



def 						__magic_name__		(				UpperCamelCase    :		str       ,		UpperCamelCase    :		str = "."    )    ->	dict:
    a__    = get_apod_data(UpperCamelCase    )
    a__    = apod_data['url']
    a__    = img_url.split('/'    )[-1]
    a__    = requests.get(UpperCamelCase       ,		stream=UpperCamelCase    )

    with open(f'{path}/{img_name}'       ,		'wb+'    ) as img_file:
        shutil.copyfileobj(response.raw       ,		UpperCamelCase    )
    del response
    return apod_data



def 						__magic_name__		(				UpperCamelCase    :		str    )    ->	dict:
    a__    = 'https://images-api.nasa.gov/search'
    return requests.get(UpperCamelCase       ,		params={'q': query}    ).json()


if __name__ == "__main__":
    print(save_apod('YOUR API KEY'))
    a		:					List[Any]    	=					get_archive_data('apollo 2011')['collection']['items']
    print(apollo_aaaa_items[0]['data'][0]['description'])


