




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase				:		Optional[Any]     =   logging.get_logger(__name__)

lowerCamelCase				:		Optional[int]     =   {
    "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
    "bert-large-uncased": "https://huggingface.co/bert-large-uncased/resolve/main/config.json",
    "bert-base-cased": "https://huggingface.co/bert-base-cased/resolve/main/config.json",
    "bert-large-cased": "https://huggingface.co/bert-large-cased/resolve/main/config.json",
    "bert-base-multilingual-uncased": "https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json",
    "bert-base-multilingual-cased": "https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json",
    "bert-base-chinese": "https://huggingface.co/bert-base-chinese/resolve/main/config.json",
    "bert-base-german-cased": "https://huggingface.co/bert-base-german-cased/resolve/main/config.json",
    "bert-large-uncased-whole-word-masking": (
        "https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"
    ),
    "bert-large-cased-whole-word-masking": (
        "https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"
    ),
    "bert-large-uncased-whole-word-masking-finetuned-squad": (
        "https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"
    ),
    "bert-large-cased-whole-word-masking-finetuned-squad": (
        "https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"
    ),
    "bert-base-cased-finetuned-mrpc": "https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json",
    "bert-base-german-dbmdz-cased": "https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json",
    "bert-base-german-dbmdz-uncased": "https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json",
    "cl-tohoku/bert-base-japanese": "https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json",
    "cl-tohoku/bert-base-japanese-whole-word-masking": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"
    ),
    "cl-tohoku/bert-base-japanese-char": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"
    ),
    "cl-tohoku/bert-base-japanese-char-whole-word-masking": (
        "https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"
    ),
    "TurkuNLP/bert-base-finnish-cased-v1": (
        "https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"
    ),
    "TurkuNLP/bert-base-finnish-uncased-v1": (
        "https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"
    ),
    "wietsedv/bert-base-dutch-cased": "https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json",
    # See all BERT models at https://huggingface.co/models?filter=bert
}







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						'''bert'''

 def __init__(				self					:  Union[str, Any]						,							A_					:  Any=30522						,							A_					:  List[str]=768						,							A_					:  Dict=12						,							A_					:  str=12						,							A_					:  List[str]=3072						,							A_					:  List[str]="gelu"						,							A_					:  Any=0.1						,							A_					:  Union[str, Any]=0.1						,							A_					:  List[Any]=512						,							A_					:  Dict=2						,							A_					:  Optional[Any]=0.02						,							A_					:  Union[str, Any]=1E-12						,							A_					:  Optional[Any]=0						,							A_					:  int="absolute"						,							A_					:  str=True						,							A_					:  Union[str, Any]=None						,							**A_					:  Dict						,							)   ->	List[str]:

       """simple docstring"""






       super().__init__(pad_token_id=A_						,							**A_  )

       lowerCamelCase_		     =    vocab_size
       lowerCamelCase_		     =    hidden_size
       lowerCamelCase_		     =    num_hidden_layers
       lowerCamelCase_		     =    num_attention_heads
       lowerCamelCase_		     =    hidden_act
       lowerCamelCase_		     =    intermediate_size
       lowerCamelCase_		     =    hidden_dropout_prob
       lowerCamelCase_		     =    attention_probs_dropout_prob
       lowerCamelCase_		     =    max_position_embeddings
       lowerCamelCase_		     =    type_vocab_size
       lowerCamelCase_		     =    initializer_range
       lowerCamelCase_		     =    layer_norm_eps
       lowerCamelCase_		     =    position_embedding_type
       lowerCamelCase_		     =    use_cache
       lowerCamelCase_		     =    classifier_dropout







class   A(						UpperCamelCase   ):



 '''simple docstring'''


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

       """simple docstring"""






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









from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
 lowerCamelCase				:		int     =   input("Enter image url: ").strip()
 print(F"""Downloading image from {url} ...""")
 lowerCamelCase				:		Tuple     =   BeautifulSoup(requests.get(url).content, "html.parser")
 # The image URL is in the content field of the first meta tag with property og:image
 lowerCamelCase				:		int     =   soup.find("meta", {"property": "og:image"})["content"]
 lowerCamelCase				:		Dict     =   requests.get(image_url).content
 lowerCamelCase				:		Optional[int]     =   F"""{datetime.now():%Y-%m-%d_%H:%M:%S}.jpg"""
 with open(file_name, "wb") as fp:
  fp.write(image_data)
 print(F"""Done. Image saved to disk as {file_name}.""")



