


import json
import os
import re
import sys
import urllib.request

import requests
from bsa import BeautifulSoup

SCREAMING_SNAKE_CASE__					:     int       =     {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
    ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582'
}




def    a__    (		snake_case__					:							str = "dhaka"						,   snake_case__					:							int = 5     ):
  _UpperCAmelCase		:							List[str]							=     min(snake_case__						,   50     )  # Prevent abuse!
  _UpperCAmelCase		:							Tuple							=     {
      """q""": query,
      """tbm""": """isch""",
      """hl""": """en""",
      """ijn""": """0""",
  }

  _UpperCAmelCase		:							List[str]							=     requests.get("""https://www.google.com/search"""						,   params=snake_case__						,   headers=snake_case__     )
  _UpperCAmelCase		:							Dict							=     BeautifulSoup(html.text						,   """html.parser"""     )
  _UpperCAmelCase		:							int							=     """""".join(
      re.findall(r"""AF_initDataCallback\(([^<]+)\);"""						,   str(soup.select("""script"""     )     )     )     )

  _UpperCAmelCase		:							List[str]							=     json.dumps(snake_case__     )
  _UpperCAmelCase		:							int							=     json.loads(snake_case__     )

  _UpperCAmelCase		:							Any							=     re.findall(
      r"""\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\","""						,   snake_case__						,   )
  if not matched_google_image_data:
    return 0

  _UpperCAmelCase		:							Any							=     re.sub(
      r"""\[\"(https\:\/\/encrypted-tbn0\.gstatic\.com\/images\?.*?)\",\d+,\d+\]"""						,   """"""						,   str(snake_case__     )						,   )

  _UpperCAmelCase		:							Any							=     re.findall(
      r"""(?:'|,),\[\"(https:|http.*?)\",\d+,\d+\]"""						,   snake_case__						,   )
  for index, fixed_full_res_image in enumerate(snake_case__     ):
    if index >= max_images:
      return index
    _UpperCAmelCase		:							List[Any]							=     bytes(snake_case__						,   """ascii"""     ).decode(
        """unicode-escape"""     )
    _UpperCAmelCase		:							List[str]							=     bytes(snake_case__						,   """ascii"""     ).decode(
        """unicode-escape"""     )
    _UpperCAmelCase		:							int							=     urllib.request.build_opener()
    _UpperCAmelCase		:							Optional[int]							=     [
        (
            """User-Agent""",
            """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"""
            """ (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582""",
        )
    ]
    urllib.request.install_opener(snake_case__     )
    _UpperCAmelCase		:							int							=     f'''query_{query.replace(" "						,   "_"     )}'''
    if not os.path.exists(snake_case__     ):
      os.makedirs(snake_case__     )
    urllib.request.urlretrieve(  # noqa: S310
        snake_case__						,   f'''{path_name}/original_size_img_{index}.jpg'''     )
  return index


if __name__ == "__main__":
 try:
  SCREAMING_SNAKE_CASE__					:     Optional[int]       =     download_images_from_google_query(sys.argv[1])
  print(F'{image_count} images were downloaded to disk.')
 except IndexError:
  print('Please provide a search term.')
  raise









from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__					:     Optional[int]       =     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__					:     List[str]       =     {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class 		_SCREAMING_SNAKE_CASE     (						A     ):
     __SCREAMING_SNAKE_CASE     					=    '''camembert'''


     def __init__(  self							,					A_=3_05_22							,					A_=7_68							,					A_=12							,					A_=12							,					A_=30_72							,					A_="gelu"							,					A_=0.1							,					A_=0.1							,					A_=5_12							,					A_=2							,					A_=0.0_2							,					A_=1e-12							,					A_=1							,					A_=0							,					A_=2							,					A_="absolute"							,					A_=True							,					A_=None							,					**A_							,					):
       super().__init__(pad_token_id=A_							,					bos_token_id=A_							,					eos_token_id=A_							,					**A_    )

       _UpperCAmelCase		:							Optional[Any]							=     vocab_size
       _UpperCAmelCase		:							int							=     hidden_size
       _UpperCAmelCase		:							Any							=     num_hidden_layers
       _UpperCAmelCase		:							Optional[Any]							=     num_attention_heads
       _UpperCAmelCase		:							Dict							=     hidden_act
       _UpperCAmelCase		:							str							=     intermediate_size
       _UpperCAmelCase		:							str							=     hidden_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     attention_probs_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     max_position_embeddings
       _UpperCAmelCase		:							Union[str, Any]							=     type_vocab_size
       _UpperCAmelCase		:							List[Any]							=     initializer_range
       _UpperCAmelCase		:							Optional[Any]							=     layer_norm_eps
       _UpperCAmelCase		:							int							=     position_embedding_type
       _UpperCAmelCase		:							Tuple							=     use_cache
       _UpperCAmelCase		:							Any							=     classifier_dropout


class 		_SCREAMING_SNAKE_CASE     (						A     ):


     @property
     def        __snake_case(  self    ):
       if self.task == "multiple-choice":
         _UpperCAmelCase		:							Any							=     {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
         _UpperCAmelCase		:							List[Any]							=     {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]    )





