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

import numpy as np







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							List[str]       =      f'''{sampling_rate}'''
     UpperCAmelCase_      :							List[str]       =      '''1'''
     UpperCAmelCase_      :							List[str]       =      '''f32le'''
     UpperCAmelCase_      :							int       =      [
         '''ffmpeg''',
         '''-i''',
         '''pipe:0''',
         '''-ac''',
         ac,
         '''-ar''',
         ar,
         '''-f''',
         format_for_conversion,
         '''-hide_banner''',
         '''-loglevel''',
         '''quiet''',
         '''pipe:1''',
     ]

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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase = "f32le"			,						):

     '''simple docstring'''


     UpperCAmelCase_      :							Optional[int]       =      f'''{sampling_rate}'''
     UpperCAmelCase_      :							Union[str, Any]       =      '''1'''
     if format_for_conversion == "s16le":
          UpperCAmelCase_      :							Optional[Any]       =      2
     elif format_for_conversion == "f32le":
          UpperCAmelCase_      :							Dict       =      4
     else:
          raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''				)

     UpperCAmelCase_      :							int       =      platform.system()
     if system == "Linux":
          UpperCAmelCase_      :							Optional[Any]       =      '''alsa'''
          UpperCAmelCase_      :							List[str]       =      '''default'''
     elif system == "Darwin":
          UpperCAmelCase_      :							Tuple       =      '''avfoundation'''
          UpperCAmelCase_      :							int       =      ''':0'''
     elif system == "Windows":
          UpperCAmelCase_      :							Union[str, Any]       =      '''dshow'''
          UpperCAmelCase_      :							List[Any]       =      '''default'''

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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase = None			,						_lowercase = None			,						_lowercase = "f32le"			,						):

     '''simple docstring'''


     if stream_chunk_s is not None:
          UpperCAmelCase_      :							str       =      stream_chunk_s
     else:
          UpperCAmelCase_      :							List[str]       =      chunk_length_s

     UpperCAmelCase_      :							Tuple       =      ffmpeg_microphone(_lowercase			,						_lowercase			,						format_for_conversion=_lowercase				)
     if format_for_conversion == "s16le":
          UpperCAmelCase_      :							Optional[int]       =      np.intaa
          UpperCAmelCase_      :							int       =      2
     elif format_for_conversion == "f32le":
          UpperCAmelCase_      :							Tuple       =      np.floataa
          UpperCAmelCase_      :							Optional[int]       =      4
     else:
          raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''				)

     if stride_length_s is None:
          UpperCAmelCase_      :							Any       =      chunk_length_s / 6
     UpperCAmelCase_      :							Union[str, Any]       =      int(round(sampling_rate * chunk_length_s				)				) * size_of_sample
     if isinstance(_lowercase			,						(int, float)				):
          UpperCAmelCase_      :							Optional[int]       =      [stride_length_s, stride_length_s]

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







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase			,						_lowercase = False				):

     '''simple docstring'''


     UpperCAmelCase_      :							Dict       =      B''''''
     UpperCAmelCase_      :							Dict       =      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}'''				)
     UpperCAmelCase_      :							Optional[Any]       =      0
     for raw in iterator:
          acc += raw
          if stream and len(_lowercase				) < chunk_len:
               UpperCAmelCase_      :							Dict       =      (_stride_left, 0)
               yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
          else:
               while len(_lowercase				) >= chunk_len:
                    # We are flushing the accumulator
                    UpperCAmelCase_      :							int       =      (_stride_left, stride_right)
                    UpperCAmelCase_      :							List[str]       =      {'''raw''': acc[:chunk_len], '''stride''': stride}
                    if stream:
                         UpperCAmelCase_      :							List[str]       =      False
                    yield item
                    UpperCAmelCase_      :							Dict       =      stride_left
                    UpperCAmelCase_      :							List[str]       =      acc[chunk_len - stride_left - stride_right :]
    # Last chunk
     if len(_lowercase				) > stride_left:
          UpperCAmelCase_      :							int       =      {'''raw''': acc, '''stride''': (_stride_left, 0)}
          if stream:
               UpperCAmelCase_      :							Optional[int]       =      False
          yield item







def lowerCamelCase__       (      _lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Optional[Any]       =      2**24  # 16Mo
     try:
          with subprocess.Popen(_lowercase			,						stdout=subprocess.PIPE			,						bufsize=_lowercase				) as ffmpeg_process:
               while True:
                    UpperCAmelCase_      :							Union[str, Any]       =      ffmpeg_process.stdout.read(_lowercase				)
                    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 os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_pegasus import PegasusTokenizer
else:
     __a          =			None


__a          =			logging.get_logger(__name__)


__a          =			'▁'

__a          =			{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__a          =			{
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'},
    'tokenizer_file': {
        'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'
    },
}

__a          =			{
    'google/pegasus-xsum': 512,
}

class   __a(					_a       ):






    """simple docstring"""





    lowerCAmelCase        =				VOCAB_FILES_NAMES
    lowerCAmelCase        =				PRETRAINED_VOCAB_FILES_MAP
    lowerCAmelCase        =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCAmelCase        =				PegasusTokenizer
    lowerCAmelCase        =				['''input_ids''', '''attention_mask''']





    def __init__(				self       ,_SCREAMING_SNAKE_CASE=None       ,_SCREAMING_SNAKE_CASE=None       ,_SCREAMING_SNAKE_CASE="<pad>"       ,_SCREAMING_SNAKE_CASE="</s>"       ,_SCREAMING_SNAKE_CASE="<unk>"       ,_SCREAMING_SNAKE_CASE="<mask_2>"       ,_SCREAMING_SNAKE_CASE="<mask_1>"       ,_SCREAMING_SNAKE_CASE=None       ,_SCREAMING_SNAKE_CASE=103       ,**_SCREAMING_SNAKE_CASE       ,)			->		Optional[Any]:
         UpperCAmelCase_      :							Dict       =      offset

         if additional_special_tokens is not None:
              if not isinstance(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
                   raise TypeError(
                       f'''additional_special_tokens should be of type {type(_SCREAMING_SNAKE_CASE  )}, but is'''
                       f''' {type(_SCREAMING_SNAKE_CASE  )}'''  )

              UpperCAmelCase_      :							str       =      (
                  ([mask_token_sent] + additional_special_tokens)
                  if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
                  else additional_special_tokens
              )
              # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
              additional_special_tokens_extended += [
                  f'''<unk_{i}>''' for i in range(len(_SCREAMING_SNAKE_CASE  )       ,self.offset - 1  )
              ]

              if len(set(_SCREAMING_SNAKE_CASE  )  ) != len(_SCREAMING_SNAKE_CASE  ):
                   raise ValueError(
                       '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
                       f''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'''  )
              UpperCAmelCase_      :							int       =      additional_special_tokens_extended
         else:
              UpperCAmelCase_      :							Any       =      [mask_token_sent] if mask_token_sent is not None else []
              additional_special_tokens += [f'''<unk_{i}>''' for i in range(2       ,self.offset  )]

         super().__init__(
             _SCREAMING_SNAKE_CASE       ,tokenizer_file=_SCREAMING_SNAKE_CASE       ,pad_token=_SCREAMING_SNAKE_CASE       ,eos_token=_SCREAMING_SNAKE_CASE       ,unk_token=_SCREAMING_SNAKE_CASE       ,mask_token=_SCREAMING_SNAKE_CASE       ,mask_token_sent=_SCREAMING_SNAKE_CASE       ,offset=_SCREAMING_SNAKE_CASE       ,additional_special_tokens=_SCREAMING_SNAKE_CASE       ,**_SCREAMING_SNAKE_CASE       ,)
         UpperCAmelCase_      :							str       =      vocab_file
         UpperCAmelCase_      :							Dict       =      False if not self.vocab_file else True





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		Any:
         UpperCAmelCase_      :							Dict       =      set(self.all_special_ids  )  # call it once instead of inside list comp
         all_special_ids.remove(self.unk_token_id  )  # <unk> is only sometimes special

         if all_special_ids != set(range(len(self.additional_special_tokens  ) + 3  )  ):
              raise ValueError(
                  '''There should be 3 special tokens: mask_token, pad_token, and eos_token +'''
                  f''' {len(self.additional_special_tokens  )} additional_special_tokens, but got {all_special_ids}'''  )

         return [1 if x in all_special_ids else 0 for x in seq]





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE = None       ,_SCREAMING_SNAKE_CASE = False  )			->		List[int]:
         if already_has_special_tokens:
              return self._special_token_mask(_SCREAMING_SNAKE_CASE  )
         elif token_ids_a is None:
              return self._special_token_mask(_SCREAMING_SNAKE_CASE  ) + [1]
         else:
              return self._special_token_mask(token_ids_a + token_ids_a  ) + [1]





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE=None  )			->		List[int]:
         if token_ids_a is None:
              return token_ids_a + [self.eos_token_id]
         # We don't expect to process pairs, but leave the pair logic for API consistency
         return token_ids_a + token_ids_a + [self.eos_token_id]





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE = None  )			->		Tuple[str]:
         if not self.can_save_slow_tokenizer:
              raise ValueError(
                  '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                  '''tokenizer.'''  )

         if not os.path.isdir(_SCREAMING_SNAKE_CASE  ):
              logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
              return
         UpperCAmelCase_      :							Optional[int]       =      os.path.join(
             _SCREAMING_SNAKE_CASE       ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

         if os.path.abspath(self.vocab_file  ) != os.path.abspath(_SCREAMING_SNAKE_CASE  ):
              copyfile(self.vocab_file       ,_SCREAMING_SNAKE_CASE  )

         return (out_vocab_file,)