




'''simple docstring'''






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


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

UpperCamelCase__:     Optional[int]										=    {
    "google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
    "google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/main/config.json"
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class        SCREAMING_SNAKE_CASE(							A__    ):







	"""simple docstring"""






	lowerCamelCase__    				= """fnet"""







	def __init__(		self    :  Union[str, Any]	,    __snake_case    :  Dict=32000	,    __snake_case    :  Tuple=768	,    __snake_case    :  Optional[int]=12	,    __snake_case    :  Dict=3072	,    __snake_case    :  Tuple="gelu_new"	,    __snake_case    :  int=0.1	,    __snake_case    :  Optional[int]=512	,    __snake_case    :  List[Any]=4	,    __snake_case    :  str=0.02	,    __snake_case    :  Optional[Any]=1E-12	,    __snake_case    :  Optional[int]=False	,    __snake_case    :  Any=512	,    __snake_case    :  List[Any]=3	,    __snake_case    :  Any=1	,    __snake_case    :  Union[str, Any]=2	,    **__snake_case    :  List[Any]	,    )    ->	str:
								super().__init__(pad_token_id=__snake_case	,    bos_token_id=__snake_case	,    eos_token_id=__snake_case	,    **__snake_case	)

								UpperCAmelCase				: Dict											=	vocab_size
								UpperCAmelCase				: Optional[int]											=	max_position_embeddings
								UpperCAmelCase				: Union[str, Any]											=	hidden_size
								UpperCAmelCase				: Optional[int]											=	num_hidden_layers
								UpperCAmelCase				: List[str]											=	intermediate_size
								UpperCAmelCase				: str											=	hidden_act
								UpperCAmelCase				: Union[str, Any]											=	hidden_dropout_prob
								UpperCAmelCase				: Union[str, Any]											=	initializer_range
								UpperCAmelCase				: List[Any]											=	type_vocab_size
								UpperCAmelCase				: int											=	layer_norm_eps
								UpperCAmelCase				: Any											=	use_tpu_fourier_optimizations
								UpperCAmelCase				: Optional[Any]											=	tpu_short_seq_length










'''simple docstring'''






from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

UpperCamelCase__:     Union[str, Any]										=    "https://www.indeed.co.in/jobs?q=mobile+app+development&l="


def 				snake_case_  (      _lowerCAmelCase						:		str = "mumbai"						)   ->     Generator[tuple[str, str], None, None]:
							UpperCAmelCase				: Optional[int]											=	BeautifulSoup(requests.get(url + location						).content     ,   '''html.parser'''						)
							# This attribute finds out all the specifics listed in a job
							for job in soup.find_all('''div'''     ,   attrs={'''data-tn-component''': '''organicJob'''}						):
														UpperCAmelCase				: Optional[Any]											=	job.find('''a'''     ,   attrs={'''data-tn-element''': '''jobTitle'''}						).text.strip()
														UpperCAmelCase				: int											=	job.find('''span'''     ,   {'''class''': '''company'''}						).text.strip()
														yield job_title, company_name


if __name__ == "__main__":
						for i, job in enumerate(fetch_jobs("Bangalore"), 1):
												print(F"Job {i:>2} is {job[0]} at {job[1]}")





