





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase_					:   int 							=						logging.get_logger(__name__)

UpperCAmelCase_					:   List[str] 							=						{"""vocab_file""": """spm_char.model"""}

UpperCAmelCase_					:   str 							=						{
    """vocab_file""": {
        """microsoft/speecht5_asr""": """https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model""",
        """microsoft/speecht5_tts""": """https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model""",
        """microsoft/speecht5_vc""": """https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model""",
    }
}

UpperCAmelCase_					:   Optional[int] 							=						{
    """microsoft/speecht5_asr""": 10_24,
    """microsoft/speecht5_tts""": 10_24,
    """microsoft/speecht5_vc""": 10_24,
}





class      lowercase__    (							__A  ):
  __UpperCamelCase	     =  VOCAB_FILES_NAMES
  __UpperCamelCase	     =  PRETRAINED_VOCAB_FILES_MAP
  __UpperCamelCase	     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __UpperCamelCase	     =  ["""input_ids""", """attention_mask"""]







  def __init__(	self    ,						_lowercase    ,						_lowercase="<s>"    ,						_lowercase="</s>"    ,						_lowercase="<unk>"    ,						_lowercase="<pad>"    ,						_lowercase = None    ,						**_lowercase    ,						):
       lowerCAmelCase_					:       Optional[int]    =		{} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=_lowercase    ,						eos_token=_lowercase    ,						unk_token=_lowercase    ,						pad_token=_lowercase    ,						sp_model_kwargs=self.sp_model_kwargs    ,						**_lowercase    ,						)

       lowerCAmelCase_					:       List[str]    =		vocab_file

       lowerCAmelCase_					:       Tuple    =		spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(_lowercase						)







  @property
  def 	UpperCAmelCase__		(	self						):
       return self.sp_model.get_piece_size()







  def 	UpperCAmelCase__		(	self						):
       lowerCAmelCase_					:       Dict    =		{self.convert_ids_to_tokens(_lowercase						): i for i in range(self.vocab_size						)}
       vocab.update(self.added_tokens_encoder						)
       return vocab







  def __getstate__(	self						):
       lowerCAmelCase_					:       int    =		self.__dict__.copy()
       lowerCAmelCase_					:       List[str]    =		None
       return state







  def __setstate__(	self    ,						_lowercase						):
       lowerCAmelCase_					:       List[str]    =		d

       # for backward compatibility
       if not hasattr(self    ,						"""sp_model_kwargs"""						):
            lowerCAmelCase_					:       Tuple    =		{}

       lowerCAmelCase_					:       Dict    =		spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(self.vocab_file						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       return self.sp_model.encode(_lowercase    ,						out_type=_lowercase						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       return self.sp_model.piece_to_id(_lowercase						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       lowerCAmelCase_					:       List[Any]    =		self.sp_model.IdToPiece(_lowercase						)
       return token







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       lowerCAmelCase_					:       Dict    =		[]
       lowerCAmelCase_					:       Union[str, Any]    =		""""""
       for token in tokens:
            # make sure that special tokens are not decoded using sentencepiece model
            if token in self.all_special_tokens:
                 out_string += self.sp_model.decode(_lowercase						) + token
                 lowerCAmelCase_					:       Union[str, Any]    =		[]
            else:
                 current_sub_tokens.append(_lowercase						)
       out_string += self.sp_model.decode(_lowercase						)
       return out_string.strip()







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase=None						):
       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    ,						_lowercase    ,						_lowercase = None    ,						_lowercase = False						):
       if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=_lowercase    ,						token_ids_a=_lowercase    ,						already_has_special_tokens=_lowercase						)

       lowerCAmelCase_					:       Any    =		[1]
       if token_ids_a is None:
            return ([0] * len(_lowercase						)) + suffix_ones
       return ([0] * len(_lowercase						)) + ([0] * len(_lowercase						)) + suffix_ones







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase = None						):
       if not os.path.isdir(_lowercase						):
            logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
            return
       lowerCAmelCase_					:       List[str]    =		os.path.join(
           _lowercase    ,						(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)

       if os.path.abspath(self.vocab_file						) != os.path.abspath(_lowercase						) and os.path.isfile(self.vocab_file						):
            copyfile(self.vocab_file    ,						_lowercase						)
       elif not os.path.isfile(self.vocab_file						):
            with open(_lowercase    ,						"""wb"""						) as fi:
                 lowerCAmelCase_					:       Tuple    =		self.sp_model.serialized_model_proto()
                 fi.write(_lowercase						)

       return (out_vocab_file,)







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


UpperCAmelCase_					:   Tuple 							=						logging.get_logger(__name__)

UpperCAmelCase_					:   List[str] 							=						{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}





class      lowercase__    (							__A  ):
  __UpperCamelCase	     =  """fnet"""







  def __init__(	self    ,						_lowercase=32_000    ,						_lowercase=768    ,						_lowercase=12    ,						_lowercase=3_072    ,						_lowercase="gelu_new"    ,						_lowercase=0.1    ,						_lowercase=512    ,						_lowercase=4    ,						_lowercase=0.02    ,						_lowercase=1e-12    ,						_lowercase=False    ,						_lowercase=512    ,						_lowercase=3    ,						_lowercase=1    ,						_lowercase=2    ,						**_lowercase    ,						):
       super().__init__(pad_token_id=_lowercase    ,						bos_token_id=_lowercase    ,						eos_token_id=_lowercase    ,						**_lowercase						)

       lowerCAmelCase_					:       Optional[Any]    =		vocab_size
       lowerCAmelCase_					:       List[str]    =		max_position_embeddings
       lowerCAmelCase_					:       str    =		hidden_size
       lowerCAmelCase_					:       Any    =		num_hidden_layers
       lowerCAmelCase_					:       Optional[int]    =		intermediate_size
       lowerCAmelCase_					:       int    =		hidden_act
       lowerCAmelCase_					:       List[str]    =		hidden_dropout_prob
       lowerCAmelCase_					:       Tuple    =		initializer_range
       lowerCAmelCase_					:       int    =		type_vocab_size
       lowerCAmelCase_					:       str    =		layer_norm_eps
       lowerCAmelCase_					:       Optional[Any]    =		use_tpu_fourier_optimizations
       lowerCAmelCase_					:       Union[str, Any]    =		tpu_short_seq_length
