





import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np





def   lowerCamelCase__       (       UpperCamelCase__     :    bytes    ,      UpperCamelCase__     :    int  )     ->	np.array:



     '''simple docstring'''




     _snake_case													=			F'''{sampling_rate}'''
     _snake_case													=			'1'
     _snake_case													=			'f32le'
     _snake_case													=			[
         'ffmpeg',
         '-i',
         'pipe:0',
         '-ac',
         ac,
         '-ar',
         ar,
         '-f',
         format_for_conversion,
         '-hide_banner',
         '-loglevel',
         'quiet',
         'pipe:1',
     ]

     try:
          with subprocess.Popen(snake_case_    ,      stdin=subprocess.PIPE    ,      stdout=subprocess.PIPE  ) as ffmpeg_process:
               _snake_case													=			ffmpeg_process.communicate(snake_case_  )
     except FileNotFoundError as error:
          raise ValueError('ffmpeg was not found but is required to load audio files from filename'  ) from error
     _snake_case													=			output_stream[0]
     _snake_case													=			np.frombuffer(snake_case_    ,      np.floataa  )
     if audio.shape[0] == 0:
          raise ValueError('Malformed soundfile'  )
     return audio





def   lowerCamelCase__       (       UpperCamelCase__     :    int    ,      UpperCamelCase__     :    float    ,      UpperCamelCase__     :    str = "f32le"    ,      )     ->	Union[str, Any]:



     '''simple docstring'''




     _snake_case													=			F'''{sampling_rate}'''
     _snake_case													=			'1'
     if format_for_conversion == "s16le":
          _snake_case													=			2
     elif format_for_conversion == "f32le":
          _snake_case													=			4
     else:
          raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''  )

     _snake_case													=			platform.system()
     if system == "Linux":
          _snake_case													=			'alsa'
          _snake_case													=			'default'
     elif system == "Darwin":
          _snake_case													=			'avfoundation'
          _snake_case													=			':0'
     elif system == "Windows":
          _snake_case													=			'dshow'
          _snake_case													=			'default'

     _snake_case													=			[
         'ffmpeg',
         '-f',
         format_,
         '-i',
         input_,
         '-ac',
         ac,
         '-ar',
         ar,
         '-f',
         format_for_conversion,
         '-fflags',
         'nobuffer',
         '-hide_banner',
         '-loglevel',
         'quiet',
         'pipe:1',
     ]
     _snake_case													=			int(round(sampling_rate * chunk_length_s  )  ) * size_of_sample
     _snake_case													=			_ffmpeg_stream(snake_case_    ,      snake_case_  )
     for item in iterator:
          yield item





def   lowerCamelCase__       (       UpperCamelCase__     :    int    ,      UpperCamelCase__     :    float    ,      UpperCamelCase__     :    Optional[int] = None    ,      UpperCamelCase__     :    Optional[Union[Tuple[float, float], float]] = None    ,      UpperCamelCase__     :    str = "f32le"    ,      )     ->	List[Any]:



     '''simple docstring'''




     if stream_chunk_s is not None:
          _snake_case													=			stream_chunk_s
     else:
          _snake_case													=			chunk_length_s

     _snake_case													=			ffmpeg_microphone(snake_case_    ,      snake_case_    ,      format_for_conversion=snake_case_  )
     if format_for_conversion == "s16le":
          _snake_case													=			np.intaa
          _snake_case													=			2
     elif format_for_conversion == "f32le":
          _snake_case													=			np.floataa
          _snake_case													=			4
     else:
          raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''  )

     if stride_length_s is None:
          _snake_case													=			chunk_length_s / 6
     _snake_case													=			int(round(sampling_rate * chunk_length_s  )  ) * size_of_sample
     if isinstance(snake_case_    ,      (int, float)  ):
          _snake_case													=			[stride_length_s, stride_length_s]

     _snake_case													=			int(round(sampling_rate * stride_length_s[0]  )  ) * size_of_sample
     _snake_case													=			int(round(sampling_rate * stride_length_s[1]  )  ) * size_of_sample
     _snake_case													=			datetime.datetime.now()
     _snake_case													=			datetime.timedelta(seconds=snake_case_  )
     for item in chunk_bytes_iter(snake_case_    ,      snake_case_    ,      stride=(stride_left, stride_right)    ,      stream=snake_case_  ):
          # Put everything back in numpy scale
          _snake_case													=			np.frombuffer(item['raw']    ,      dtype=snake_case_  )
          _snake_case													=			(
              item['stride'][0] // size_of_sample,
              item['stride'][1] // size_of_sample,
          )
          _snake_case													=			sampling_rate
          audio_time += delta
          if datetime.datetime.now() > audio_time + 10 * delta:
               # We're late !! SKIP
               continue
          yield item





def   lowerCamelCase__       (       UpperCamelCase__     :    Optional[int]    ,      UpperCamelCase__     :    int    ,      UpperCamelCase__     :    Tuple[int, int]    ,      UpperCamelCase__     :    bool = False  )     ->	Tuple:



     '''simple docstring'''




     _snake_case													=			b''
     _snake_case							,       _snake_case													=			stride
     if stride_left + stride_right >= chunk_len:
          raise ValueError(
              F'''Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}'''  )
     _snake_case													=			0
     for raw in iterator:
          acc += raw
          if stream and len(snake_case_  ) < chunk_len:
               _snake_case													=			(_stride_left, 0)
               yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
          else:
               while len(snake_case_  ) >= chunk_len:
                    # We are flushing the accumulator
                    _snake_case													=			(_stride_left, stride_right)
                    _snake_case													=			{'raw': acc[:chunk_len], 'stride': stride}
                    if stream:
                         _snake_case													=			False
                    yield item
                    _snake_case													=			stride_left
                    _snake_case													=			acc[chunk_len - stride_left - stride_right :]
    # Last chunk
     if len(snake_case_  ) > stride_left:
          _snake_case													=			{'raw': acc, 'stride': (_stride_left, 0)}
          if stream:
               _snake_case													=			False
          yield item





def   lowerCamelCase__       (       UpperCamelCase__     :    Dict    ,      UpperCamelCase__     :    int  )     ->	int:



     '''simple docstring'''




     _snake_case													=			2**24  # 16Mo
     try:
          with subprocess.Popen(snake_case_    ,      stdout=subprocess.PIPE    ,      bufsize=snake_case_  ) as ffmpeg_process:
               while True:
                    _snake_case													=			ffmpeg_process.stdout.read(snake_case_  )
                    if raw == b"":
                         break
                    yield raw
     except FileNotFoundError as error:
          raise ValueError('ffmpeg was not found but is required to stream audio files from filename'  ) from error










import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


UpperCAmelCase_ 							=       logging.get_logger(__name__)
class      UpperCamelCase_						(					_lowerCamelCase   ):




					def __init__(						self			,  *lowerCAmelCase_			,  **lowerCAmelCase_					)						->							None:
										warnings.warn(
										    'The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use FlavaImageProcessor instead.'			,  lowerCAmelCase_			,  )
										super().__init__(*lowerCAmelCase_			,  **lowerCAmelCase_					)



