



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__      :				List[Any]   	=			None


a__      :				Any   	=			logging.get_logger(__name__)


a__      :				int   	=			"▁"

a__      :				Any   	=			{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

a__      :				List[Any]   	=			{
    "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__      :				Optional[int]   	=			{
    "google/pegasus-xsum": 5_12,
}



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   A    :  Any       				=    VOCAB_FILES_NAMES
   A    :  List[str]       				=    PRETRAINED_VOCAB_FILES_MAP
   A    :  str       				=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A    :  Optional[Any]       				=    PegasusTokenizer
   A    :  List[str]       				=    ["input_ids", "attention_mask"]


   def __init__(						self  :			List[str]			,				lowerCAmelCase  :			Dict=None			,				lowerCAmelCase  :			Dict=None			,				lowerCAmelCase  :			Optional[Any]="<pad>"			,				lowerCAmelCase  :			str="</s>"			,				lowerCAmelCase  :			Union[str, Any]="<unk>"			,				lowerCAmelCase  :			Tuple="<mask_2>"			,				lowerCAmelCase  :			int="<mask_1>"			,				lowerCAmelCase  :			str=None			,				lowerCAmelCase  :			List[str]=1_03			,				**lowerCAmelCase  :			int			,				)	->				Optional[int]:




         """simple docstring"""

         lowercase__     =  offset

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

               lowercase__     =  (
                   ([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(UpperCAmelCase__)			,				self.offset - 1)
               ]

               if len(set(UpperCAmelCase__)) != len(UpperCAmelCase__):
                     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}.''')
               lowercase__     =  additional_special_tokens_extended
         else:
               lowercase__     =  [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__(
             UpperCAmelCase__			,				tokenizer_file=UpperCAmelCase__			,				pad_token=UpperCAmelCase__			,				eos_token=UpperCAmelCase__			,				unk_token=UpperCAmelCase__			,				mask_token=UpperCAmelCase__			,				mask_token_sent=UpperCAmelCase__			,				offset=UpperCAmelCase__			,				additional_special_tokens=UpperCAmelCase__			,				**UpperCAmelCase__			,				)
         lowercase__     =  vocab_file
         lowercase__     =  False if not self.vocab_file else True


   def 			UpperCAmelCase		(						self  :			List[str]			,				lowerCAmelCase  :			Tuple)	->				Optional[Any]:




         """simple docstring"""

         lowercase__     =  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 			UpperCAmelCase		(						self  :			int			,				lowerCAmelCase  :			List			,				lowerCAmelCase  :			Optional[List] = None			,				lowerCAmelCase  :			bool = False)	->				List[int]:




         """simple docstring"""

         if already_has_special_tokens:
               return self._special_token_mask(UpperCAmelCase__)
         elif token_ids_a is None:
               return self._special_token_mask(UpperCAmelCase__) + [1]
         else:
               return self._special_token_mask(token_ids_a + token_ids_a) + [1]


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




         """simple docstring"""

         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 			UpperCAmelCase		(						self  :			Dict			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Optional[str] = None)	->				Tuple[str]:




         """simple docstring"""

         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(UpperCAmelCase__):
               logger.error(f'''Vocabulary path ({save_directory}) should be a directory''')
               return
         lowercase__     =  os.path.join(
             UpperCAmelCase__			,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

         return (out_vocab_file,)





from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__      :				Dict   	=			logging.get_logger(__name__)

a__      :				List[Any]   	=			{
    "facebook/s2t-small-librispeech-asr": (
        "https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json"
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   A    :  int       				=    "speech_to_text"
   A    :  Optional[Any]       				=    ["past_key_values"]
   A    :  Optional[int]       				=    {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


   def __init__(						self  :			Optional[int]			,				lowerCAmelCase  :			Tuple=1_00_00			,				lowerCAmelCase  :			int=12			,				lowerCAmelCase  :			int=20_48			,				lowerCAmelCase  :			Union[str, Any]=4			,				lowerCAmelCase  :			str=6			,				lowerCAmelCase  :			Dict=20_48			,				lowerCAmelCase  :			Dict=4			,				lowerCAmelCase  :			Optional[int]=0.0			,				lowerCAmelCase  :			Union[str, Any]=0.0			,				lowerCAmelCase  :			int=True			,				lowerCAmelCase  :			Optional[Any]=True			,				lowerCAmelCase  :			Dict="relu"			,				lowerCAmelCase  :			Tuple=2_56			,				lowerCAmelCase  :			Dict=0.1			,				lowerCAmelCase  :			Optional[Any]=0.0			,				lowerCAmelCase  :			List[Any]=0.0			,				lowerCAmelCase  :			Any=0.02			,				lowerCAmelCase  :			List[Any]=2			,				lowerCAmelCase  :			Tuple=True			,				lowerCAmelCase  :			Tuple=1			,				lowerCAmelCase  :			List[str]=0			,				lowerCAmelCase  :			Union[str, Any]=2			,				lowerCAmelCase  :			Any=60_00			,				lowerCAmelCase  :			Optional[int]=10_24			,				lowerCAmelCase  :			Optional[Any]=2			,				lowerCAmelCase  :			Optional[Any]=(5, 5)			,				lowerCAmelCase  :			Union[str, Any]=10_24			,				lowerCAmelCase  :			List[Any]=80			,				lowerCAmelCase  :			List[str]=1			,				**lowerCAmelCase  :			List[str]			,				)	->				Dict:




         """simple docstring"""

         lowercase__     =  vocab_size
         lowercase__     =  d_model
         lowercase__     =  encoder_ffn_dim
         lowercase__     =  encoder_layers
         lowercase__     =  encoder_attention_heads
         lowercase__     =  decoder_ffn_dim
         lowercase__     =  decoder_layers
         lowercase__     =  decoder_attention_heads
         lowercase__     =  dropout
         lowercase__     =  attention_dropout
         lowercase__     =  activation_dropout
         lowercase__     =  activation_function
         lowercase__     =  init_std
         lowercase__     =  encoder_layerdrop
         lowercase__     =  decoder_layerdrop
         lowercase__     =  use_cache
         lowercase__     =  encoder_layers
         lowercase__     =  scale_embedding  # scale factor will be sqrt(d_model) if True
         lowercase__     =  max_source_positions
         lowercase__     =  max_target_positions
         lowercase__     =  num_conv_layers
         lowercase__     =  list(lowerCAmelCase)
         lowercase__     =  conv_channels
         lowercase__     =  input_feat_per_channel
         lowercase__     =  input_channels

         if len(self.conv_kernel_sizes) != self.num_conv_layers:
               raise ValueError(
                   'Configuration for convolutional module is incorrect. '
                   'It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '
                   f'''but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes)}`, '''
                   f'''`config.num_conv_layers = {self.num_conv_layers}`.''')

         super().__init__(
             pad_token_id=lowerCAmelCase			,				bos_token_id=lowerCAmelCase			,				eos_token_id=lowerCAmelCase			,				is_encoder_decoder=lowerCAmelCase			,				decoder_start_token_id=lowerCAmelCase			,				**lowerCAmelCase			,				)
