from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase					:	Dict       =  logging.get_logger(__name__)

__lowerCamelCase					:	Union[str, Any]       =  {
    '''edbeeching/decision-transformer-gym-hopper-medium''': (
        '''https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json'''
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}






class 		a__						(					A__					):
					A	       =							'decision_transformer'
					A	       =							['past_key_values']
					A	       =							{
					    'max_position_embeddings': 'n_positions',
					    'num_attention_heads': 'n_head',
					    'num_hidden_layers': 'n_layer',
					}

					def __init__(    self      :       int,_A      :       Optional[int]=17,_A      :       List[str]=4,_A      :       Any=128,_A      :       Optional[Any]=4096,_A      :       Tuple=True,_A      :       Any=1,_A      :       str=1024,_A      :       int=3,_A      :       Optional[Any]=1,_A      :       int=None,_A      :       List[str]="relu",_A      :       List[str]=0.1,_A      :       Any=0.1,_A      :       Optional[Any]=0.1,_A      :       Union[str, Any]=1E-5,_A      :       Tuple=0.02,_A      :       int=True,_A      :       List[str]=True,_A      :       List[Any]=5_0256,_A      :       Any=5_0256,_A      :       Optional[Any]=False,_A      :       str=False,**_A      :       str,):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]				      =    state_dim
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    act_dim
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    hidden_size
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    max_ep_len
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    action_tanh
							SCREAMING_SNAKE_CASE_  :		Any				      =    vocab_size
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    n_positions
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    n_layer
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    n_head
							SCREAMING_SNAKE_CASE_  :		str				      =    n_inner
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    activation_function
							SCREAMING_SNAKE_CASE_  :		int				      =    resid_pdrop
							SCREAMING_SNAKE_CASE_  :		Dict				      =    embd_pdrop
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    attn_pdrop
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    layer_norm_epsilon
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    initializer_range
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    scale_attn_weights
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    use_cache
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    scale_attn_by_inverse_layer_idx
							SCREAMING_SNAKE_CASE_  :		int				      =    reorder_and_upcast_attn

							SCREAMING_SNAKE_CASE_  :		Any				      =    bos_token_id
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    eos_token_id

							super().__init__(bos_token_id=_A,eos_token_id=_A,**_A    )




"""simple docstring"""



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

import requests
from bsa import BeautifulSoup

__snake_case   			=    {
    """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   __lowerCAmelCase						(						lowercase  :  str = "dhaka"						,							lowercase  :  int = 5 )	->						int:


    """simple docstring"""





    snake_case    :      List[Any]      					=    min(lowercase						,							50 )  # Prevent abuse!
    snake_case    :      Optional[Any]      					=    {
        "q": query,
        "tbm": "isch",
        "hl": "en",
        "ijn": "0",
    }

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

    snake_case    :      Optional[Any]      					=    json.dumps(lowercase )
    snake_case    :      str      					=    json.loads(lowercase )

    snake_case    :      List[str]      					=    re.findall(
        R"\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\","						,							lowercase						,							)
    if not matched_google_image_data:
        return 0

    snake_case    :      List[str]      					=    re.sub(
        R"\[\"(https\:\/\/encrypted-tbn0\.gstatic\.com\/images\?.*?)\",\d+,\d+\]"						,							""						,							str(lowercase )						,							)

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


if __name__ == "__main__":
  try:
    __snake_case   			=    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





