






'''simple docstring'''



from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
      from PIL import Image

      from ..image_utils import load_image

if is_tf_available():
      import tensorflow as tf

      from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
      from ..tf_utils import stable_softmax

if is_torch_available():
      from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

SCREAMING_SNAKE_CASE						=	logging.get_logger(__name__)
@add_end_docstrings(__A				)
class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      def __init__( self			:		Optional[Any]     ,      *UpperCAmelCase			:		Tuple     ,      **UpperCAmelCase			:		Optional[Any]		)  ->  int:


       '''simple docstring'''

       super().__init__(*UpperCAmelCase     ,      **UpperCAmelCase		)
       requires_backends(self     ,      '''vision'''		)
       self.check_model_type(
           TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
           if self.framework == '''tf'''
           else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING		)






      def 				A__      ( self			:		List[str]     ,      UpperCAmelCase			:		Any=None		)  ->  Optional[int]:


       '''simple docstring'''

       lowercase					:   Tuple				  ={}
       if top_k is not None:
        lowercase					:   Optional[Any]				  =top_k
       return {}, {}, postprocess_params






      def __call__( self			:		Dict     ,      UpperCAmelCase			:		Union[str, List[str], "Image.Image", List["Image.Image"]]     ,      **UpperCAmelCase			:		Optional[Any]		)  ->  List[str]:


       '''simple docstring'''

       return super().__call__(UpperCAmelCase     ,      **UpperCAmelCase		)






      def 				A__      ( self			:		Optional[int]     ,      UpperCAmelCase			:		Optional[Any]		)  ->  List[str]:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =load_image(UpperCAmelCase		)
       lowercase					:   Tuple				  =self.image_processor(images=UpperCAmelCase     ,      return_tensors=self.framework		)
       return model_inputs






      def 				A__      ( self			:		Dict     ,      UpperCAmelCase			:		Union[str, Any]		)  ->  int:


       '''simple docstring'''

       lowercase					:   Optional[int]				  =self.model(**UpperCAmelCase		)
       return model_outputs






      def 				A__      ( self			:		Tuple     ,      UpperCAmelCase			:		Tuple     ,      UpperCAmelCase			:		List[Any]=5		)  ->  Optional[Any]:


       '''simple docstring'''

       if top_k > self.model.config.num_labels:
        lowercase					:   int				  =self.model.config.num_labels

       if self.framework == "pt":
        lowercase					:   Dict				  =model_outputs.logits.softmax(-1		)[0]
        lowercase  ,		lowercase					:   Tuple				  =probs.topk(UpperCAmelCase		)
       elif self.framework == "tf":
        lowercase					:   Dict				  =stable_softmax(model_outputs.logits     ,      axis=-1		)[0]
        lowercase					:   Dict				  =tf.math.top_k(UpperCAmelCase     ,      k=UpperCAmelCase		)
        lowercase  ,		lowercase					:   Tuple				  =topk.values.numpy(), topk.indices.numpy()
       else:
        raise ValueError(f'Unsupported framework: {self.framework}'		)

       lowercase					:   Optional[Any]				  =scores.tolist()
       lowercase					:   Optional[Any]				  =ids.tolist()
       return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(UpperCAmelCase     ,      UpperCAmelCase		)]











'''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]}""")



