






'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from packaging import version

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


SCREAMING_SNAKE_CASE						=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						=	{
    'microsoft/table-transformer-detection': (
        'https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json'
    ),
}
class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      UpperCamelCase_								=			'''table-transformer'''
      UpperCamelCase_								=			['''past_key_values''']
      UpperCamelCase_								=			{
          '''hidden_size''': '''d_model''',
          '''num_attention_heads''': '''encoder_attention_heads''',
      }






      def __init__( self			:		int     ,      UpperCAmelCase			:		Dict=True     ,      UpperCAmelCase			:		int=None     ,      UpperCAmelCase			:		List[Any]=3     ,      UpperCAmelCase			:		Dict=100     ,      UpperCAmelCase			:		Optional[int]=6     ,      UpperCAmelCase			:		int=2048     ,      UpperCAmelCase			:		List[Any]=8     ,      UpperCAmelCase			:		Any=6     ,      UpperCAmelCase			:		List[Any]=2048     ,      UpperCAmelCase			:		Union[str, Any]=8     ,      UpperCAmelCase			:		Dict=0.0     ,      UpperCAmelCase			:		Optional[Any]=0.0     ,      UpperCAmelCase			:		Optional[int]=True     ,      UpperCAmelCase			:		Optional[Any]="relu"     ,      UpperCAmelCase			:		List[str]=256     ,      UpperCAmelCase			:		List[Any]=0.1     ,      UpperCAmelCase			:		int=0.0     ,      UpperCAmelCase			:		List[str]=0.0     ,      UpperCAmelCase			:		Tuple=0.0_2     ,      UpperCAmelCase			:		str=1.0     ,      UpperCAmelCase			:		int=False     ,      UpperCAmelCase			:		List[str]="sine"     ,      UpperCAmelCase			:		Tuple="resnet50"     ,      UpperCAmelCase			:		int=True     ,      UpperCAmelCase			:		Union[str, Any]=False     ,      UpperCAmelCase			:		Dict=1     ,      UpperCAmelCase			:		Tuple=5     ,      UpperCAmelCase			:		Dict=2     ,      UpperCAmelCase			:		int=1     ,      UpperCAmelCase			:		Union[str, Any]=1     ,      UpperCAmelCase			:		int=5     ,      UpperCAmelCase			:		str=2     ,      UpperCAmelCase			:		Union[str, Any]=0.1     ,      **UpperCAmelCase			:		List[str]     ,      )  ->  str:


       '''simple docstring'''

       if backbone_config is not None and use_timm_backbone:
        raise ValueError('''You can\'t specify both `backbone_config` and `use_timm_backbone`.'''		)

       if not use_timm_backbone:
        if backbone_config is None:
         logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''		)
         lowercase					:   List[Any]				  =CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']		)
        elif isinstance(UpperCAmelCase     ,      UpperCAmelCase		):
         lowercase					:   Any				  =backbone_config.get('''model_type'''		)
         lowercase					:   Union[str, Any]				  =CONFIG_MAPPING[backbone_model_type]
         lowercase					:   Dict				  =config_class.from_dict(UpperCAmelCase		)
        # set timm attributes to None
        lowercase  ,		lowercase  ,		lowercase					:   Union[str, Any]				  =None, None, None

       lowercase					:   Optional[int]				  =use_timm_backbone
       lowercase					:   Tuple				  =backbone_config
       lowercase					:   int				  =num_channels
       lowercase					:   int				  =num_queries
       lowercase					:   List[str]				  =d_model
       lowercase					:   int				  =encoder_ffn_dim
       lowercase					:   Tuple				  =encoder_layers
       lowercase					:   Optional[Any]				  =encoder_attention_heads
       lowercase					:   Dict				  =decoder_ffn_dim
       lowercase					:   Optional[Any]				  =decoder_layers
       lowercase					:   List[Any]				  =decoder_attention_heads
       lowercase					:   Optional[int]				  =dropout
       lowercase					:   List[Any]				  =attention_dropout
       lowercase					:   str				  =activation_dropout
       lowercase					:   List[Any]				  =activation_function
       lowercase					:   str				  =init_std
       lowercase					:   int				  =init_xavier_std
       lowercase					:   str				  =encoder_layerdrop
       lowercase					:   Any				  =decoder_layerdrop
       lowercase					:   str				  =encoder_layers
       lowercase					:   Any				  =auxiliary_loss
       lowercase					:   Any				  =position_embedding_type
       lowercase					:   str				  =backbone
       lowercase					:   List[Any]				  =use_pretrained_backbone
       lowercase					:   str				  =dilation
       # Hungarian matcher
       lowercase					:   Union[str, Any]				  =class_cost
       lowercase					:   Tuple				  =bbox_cost
       lowercase					:   Optional[Any]				  =giou_cost
       # Loss coefficients
       lowercase					:   str				  =mask_loss_coefficient
       lowercase					:   List[Any]				  =dice_loss_coefficient
       lowercase					:   Any				  =bbox_loss_coefficient
       lowercase					:   Any				  =giou_loss_coefficient
       lowercase					:   str				  =eos_coefficient
       super().__init__(is_encoder_decoder=UpperCAmelCase     ,      **UpperCAmelCase		)






      @property
      def 				A__      ( self			:		Tuple		)  ->  int:


       '''simple docstring'''

       return self.encoder_attention_heads






      @property
      def 				A__      ( self			:		List[str]		)  ->  int:


       '''simple docstring'''

       return self.d_model





class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      UpperCamelCase_								=			version.parse('''1.11'''				)






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


       '''simple docstring'''

       return OrderedDict(
           [
               ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
               ('''pixel_mask''', {0: '''batch'''}),
           ]		)






      @property
      def 				A__      ( self			:		str		)  ->  float:


       '''simple docstring'''

       return 1e-5






      @property
      def 				A__      ( self			:		List[str]		)  ->  int:


       '''simple docstring'''

       return 12











'''simple docstring'''



from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

SCREAMING_SNAKE_CASE						=	'https://www.indeed.co.in/jobs?q=mobile+app+development&l='


def 							lowercase_				(    __A :       str = "mumbai"			)       ->      Generator[tuple[str, str], None, None]:



 """simple docstring"""




 lowercase					:   List[Any]				  =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'''}			):
  lowercase					:   List[str]				  =job.find('''a'''					,      attrs={'''data-tn-element''': '''jobTitle'''}			).text.strip()
  lowercase					:   Union[str, Any]				  =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]}""")



