



"""simple docstring"""


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

import requests
from bsa import BeautifulSoup

__A   :							Dict										=   {
    "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  lowercase	(      _SCREAMING_SNAKE_CASE   :						str = "dhaka"					,     _SCREAMING_SNAKE_CASE   :						int = 5				):






				'''simple docstring'''



				_UpperCAmelCase					=    min(_SCREAMING_SNAKE_CASE					,     50				)  # Prevent abuse!
				_UpperCAmelCase					=    {
				    '''q''': query,
				    '''tbm''': '''isch''',
				    '''hl''': '''en''',
				    '''ijn''': '''0''',
				}

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

				_UpperCAmelCase					=    json.dumps(_SCREAMING_SNAKE_CASE				)
				_UpperCAmelCase					=    json.loads(_SCREAMING_SNAKE_CASE				)

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

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

				_UpperCAmelCase					=    re.findall(
				    r'''(?:\'|,),\[\"(https:|http.*?)\",\d+,\d+\]'''					,     _SCREAMING_SNAKE_CASE					,     )
				for index, fixed_full_res_image in enumerate(_SCREAMING_SNAKE_CASE				):
								if index >= max_images:
												return index
								_UpperCAmelCase					=    bytes(_SCREAMING_SNAKE_CASE					,     '''ascii'''				).decode(
								    '''unicode-escape'''				)
								_UpperCAmelCase					=    bytes(_SCREAMING_SNAKE_CASE					,     '''ascii'''				).decode(
								    '''unicode-escape'''				)
								_UpperCAmelCase					=    urllib.request.build_opener()
								_UpperCAmelCase					=    [
								    (
								        '''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(_SCREAMING_SNAKE_CASE				)
								_UpperCAmelCase					=    f'query_{query.replace(" "					,     "_"				)}'
								if not os.path.exists(_SCREAMING_SNAKE_CASE				):
												os.makedirs(_SCREAMING_SNAKE_CASE				)
								urllib.request.urlretrieve(  # noqa: S310
								    _SCREAMING_SNAKE_CASE					,     f'{path_name}/original_size_img_{index}.jpg'				)
				return index


if __name__ == "__main__":
					try:
										__A   :							Dict										=   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








"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


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

__A   :							Optional[Any]										=   {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}
class 			_a (					lowerCAmelCase			,							lowerCAmelCase):
			"""simple docstring"""
			UpperCamelCase__			      =	"""bit"""
			UpperCamelCase__			      =	["""preactivation""", """bottleneck"""]
			UpperCamelCase__			      =	["""SAME""", """VALID"""]



			def __init__(		self     :    List[Any]				,   __UpperCamelCase     :    Optional[int]=3				,   __UpperCamelCase     :    Optional[int]=6_4				,   __UpperCamelCase     :    List[Any]=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8]				,   __UpperCamelCase     :    Any=[3, 4, 6, 3]				,   __UpperCamelCase     :    str="preactivation"				,   __UpperCamelCase     :    Union[str, Any]="relu"				,   __UpperCamelCase     :    str=None				,   __UpperCamelCase     :    Dict=3_2				,   __UpperCamelCase     :    List[str]=0.0				,   __UpperCamelCase     :    Any=False				,   __UpperCamelCase     :    Union[str, Any]=3_2				,   __UpperCamelCase     :    List[str]=1				,   __UpperCamelCase     :    List[str]=None				,   __UpperCamelCase     :    Optional[Any]=None				,   **__UpperCamelCase     :    List[str]				,   )->List[Any]:
							super().__init__(**__UpperCamelCase   )
							if layer_type not in self.layer_types:
											raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types   )}'   )
							if global_padding is not None:
											if global_padding.upper() in self.supported_padding:
															_UpperCAmelCase					=    global_padding.upper()
											else:
															raise ValueError(F'Padding strategy {global_padding} not supported'   )
							_UpperCAmelCase					=    num_channels
							_UpperCAmelCase					=    embedding_size
							_UpperCAmelCase					=    hidden_sizes
							_UpperCAmelCase					=    depths
							_UpperCAmelCase					=    layer_type
							_UpperCAmelCase					=    hidden_act
							_UpperCAmelCase					=    global_padding
							_UpperCAmelCase					=    num_groups
							_UpperCAmelCase					=    drop_path_rate
							_UpperCAmelCase					=    embedding_dynamic_padding
							_UpperCAmelCase					=    output_stride
							_UpperCAmelCase					=    width_factor

							_UpperCAmelCase					=    ['''stem'''] + [F'stage{idx}' for idx in range(1				,   len(__UpperCamelCase   ) + 1   )]
							_UpperCAmelCase		,						_UpperCAmelCase					=    get_aligned_output_features_output_indices(
							    out_features=__UpperCamelCase				,   out_indices=__UpperCamelCase				,   stage_names=self.stage_names   )



