





"""simple docstring"""
import os
from collections.abc import Iterator

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str = "."			):
 for dir_path, dir_names, filenames in os.walk(_UpperCAmelCase			):
  lowerCAmelCase    				= [d for d in dir_names if d != 'scripts' and d[0] not in '._']
  for filename in filenames:
   if filename == "__init__.py":
    continue
   if os.path.splitext(_UpperCAmelCase			)[1] in (".py", ".ipynb"):
    yield os.path.join(_UpperCAmelCase  ,     _UpperCAmelCase			).lstrip('./'			)

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Union[str, Any]			):
 return F'{i * "  "}*' if i else "\n##"

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str  ,     _UpperCAmelCase					:    str			):
 lowerCAmelCase    				= old_path.split(os.sep			)
 for i, new_part in enumerate(new_path.split(os.sep			)			):
  if (i + 1 > len(_UpperCAmelCase			) or old_parts[i] != new_part) and new_part:
   print(F'{md_prefix(_UpperCAmelCase			)} {new_part.replace("_"  ,     " "			).title()}'			)
 return new_path

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str = "."			):
 lowerCAmelCase    				= ''
 for filepath in sorted(good_file_paths(_UpperCAmelCase			)			):
  lowerCAmelCase				,lowerCAmelCase    				= os.path.split(_UpperCAmelCase			)
  if filepath != old_path:
   lowerCAmelCase    				= print_path(_UpperCAmelCase  ,     _UpperCAmelCase			)
  lowerCAmelCase    				= (filepath.count(os.sep			) + 1) if filepath else 0
  lowerCAmelCase    				= F'{filepath}/{filename}'.replace(' '  ,     '%20'			)
  lowerCAmelCase    				= os.path.splitext(filename.replace('_'  ,     ' '			).title()			)[0]
  print(F'{md_prefix(_UpperCAmelCase			)} [{filename}]({url})'			)


if __name__ == "__main__":
       print_directory_md('''.''')








from collections import UserDict
from typing import Union

import numpy as np
import requests

from ..utils import (
    add_end_docstrings,
    logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline


lowercase_   							=  logging.get_logger(__name__)





@add_end_docstrings(SCREAMING_SNAKE_CASE				)
class 					__lowerCAmelCase	(   SCREAMING_SNAKE_CASE				):




  def __init__(							self				,  **lowerCAmelCase   )    ->					Tuple:
        '''simple docstring'''






        super().__init__(**lowerCAmelCase   )

        if self.framework != "pt":
              raise ValueError(F'''The {self.__class__} is only available in PyTorch.'''   )
        # No specific FOR_XXX available yet




  def __call__(							self				,  lowerCAmelCase				,  **lowerCAmelCase   )    ->					int:
        '''simple docstring'''






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




  def     A__	(							self				,  **lowerCAmelCase   )    ->					Optional[Any]:
        '''simple docstring'''






        _lowercase      			={}
        if "candidate_labels" in kwargs:
              _lowercase      			=kwargs['candidate_labels']
        if "hypothesis_template" in kwargs:
              _lowercase      			=kwargs['hypothesis_template']

        return preprocess_params, {}, {}




  def     A__	(							self				,  lowerCAmelCase				,  lowerCAmelCase=None				,  lowerCAmelCase="This is a sound of {}."   )    ->					Tuple:
        '''simple docstring'''






        if isinstance(lowerCAmelCase				,  lowerCAmelCase   ):
              if audio.startswith('http://'   ) or audio.startswith('https://'   ):
                    # We need to actually check for a real protocol, otherwise it's impossible to use a local file
                    # like http_huggingface_co.png
                    _lowercase      			=requests.get(lowerCAmelCase   ).content
              else:
                    with open(lowerCAmelCase				,  'rb'   ) as f:
                          _lowercase      			=f.read()

        if isinstance(lowerCAmelCase				,  lowerCAmelCase   ):
              _lowercase      			=ffmpeg_read(lowerCAmelCase				,  self.feature_extractor.sampling_rate   )

        if not isinstance(lowerCAmelCase				,  np.ndarray   ):
              raise ValueError('We expect a numpy ndarray as input'   )
        if len(audio.shape   ) != 1:
              raise ValueError('We expect a single channel audio input for ZeroShotAudioClassificationPipeline'   )

        _lowercase      			=self.feature_extractor(
            [audio]				,  sampling_rate=self.feature_extractor.sampling_rate				,  return_tensors='pt'   )
        _lowercase      			=candidate_labels
        _lowercase      			=[hypothesis_template.format(lowerCAmelCase   ) for x in candidate_labels]
        _lowercase      			=self.tokenizer(lowerCAmelCase				,  return_tensors=self.framework				,  padding=lowerCAmelCase   )
        _lowercase      			=[text_inputs]
        return inputs




  def     A__	(							self				,  lowerCAmelCase   )    ->					Dict:
        '''simple docstring'''






        _lowercase      			=model_inputs.pop('candidate_labels'   )
        _lowercase      			=model_inputs.pop('text_inputs'   )
        if isinstance(text_inputs[0]				,  lowerCAmelCase   ):
              _lowercase      			=text_inputs[0]
        else:
              # Batching case.
              _lowercase      			=text_inputs[0][0]

        _lowercase      			=self.model(**lowerCAmelCase				,  **lowerCAmelCase   )

        _lowercase      			={
            'candidate_labels': candidate_labels,
            'logits': outputs.logits_per_audio,
        }
        return model_outputs




  def     A__	(							self				,  lowerCAmelCase   )    ->					Tuple:
        '''simple docstring'''






        _lowercase      			=model_outputs.pop('candidate_labels'   )
        _lowercase      			=model_outputs['logits'][0]

        if self.framework == "pt":
              _lowercase      			=logits.softmax(dim=0   )
              _lowercase      			=probs.tolist()
        else:
              raise ValueError('`tf` framework not supported.'   )

        _lowercase      			=[
            {'score': score, 'label': candidate_label}
            for score, candidate_label in sorted(zip(lowerCAmelCase				,  lowerCAmelCase   )				,  key=lambda lowerCAmelCase   : -x[0]   )
        ]
        return result


