
import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


UpperCamelCase_						:     str	       =							logging.get_logger(__name__)


UpperCamelCase_						:     Union[str, Any]	       =							{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

UpperCamelCase_						:     Optional[Any]	       =							{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

UpperCamelCase_						:     Tuple	       =							{"""facebook/blenderbot_small-90M""": 512}



def 		UpperCamelCase     (       _UpperCAmelCase  :   List[str]  )   ->			int:






						'''simple docstring'''

						_lowercase       :	Dict           =   set()
						_lowercase       :	Any           =   word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)  )
												_lowercase       :	Optional[int]           =   char

						_lowercase       :	Union[str, Any]           =   set(SCREAMING_SNAKE_CASE_  )
						return pairs




class   __lowercase						(						__snake_case       ):
	_A       =   VOCAB_FILES_NAMES
	_A       =   PRETRAINED_VOCAB_FILES_MAP
	_A       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       =   ["""input_ids""", """attention_mask"""]






	def __init__(self				: Union[str, Any]      ,	snake_case				: str      ,	snake_case				: List[str]      ,	snake_case				: List[Any]="__start__"      ,	snake_case				: Optional[Any]="__end__"      ,	snake_case				: Dict="__unk__"      ,	snake_case				: int="__null__"      ,	**snake_case				: Any      ,	) ->			Optional[Any]:
							super().__init__(unk_token=_lowercase      ,	bos_token=_lowercase      ,	eos_token=_lowercase      ,	pad_token=_lowercase      ,	**_lowercase    )

							with open(_lowercase      ,	encoding="utf-8"    ) as vocab_handle:
													_lowercase       :	Optional[Any]           =   json.load(_lowercase    )
							_lowercase       :	List[str]           =   {v: k for k, v in self.encoder.items()}
							with open(_lowercase      ,	encoding="utf-8"    ) as merges_handle:
													_lowercase       :	Any           =   merges_handle.read().split("\n"    )[1:-1]
							_lowercase       :	Union[str, Any]           =   [tuple(merge.split()    ) for merge in merges]
							_lowercase       :	Any           =   dict(zip(_lowercase      ,	range(len(_lowercase    )    )    )    )
							_lowercase       :	Tuple           =   {}






	@property
	def       _a(self				: Any    ) ->			int:
							return len(self.encoder    )






	def       _a(self				: Tuple    ) ->			Dict:
							return dict(self.encoder      ,	**self.added_tokens_encoder    )






	def       _a(self				: Any      ,	snake_case				: Union[str, Any]    ) ->			str:
							if token in self.cache:
													return self.cache[token]
							_lowercase       :	Optional[Any]           =   re.sub("([.,!?()])"      ,	R" \1"      ,	_lowercase    )
							_lowercase       :	Optional[int]           =   re.sub("(')"      ,	R" \1 "      ,	_lowercase    )
							_lowercase       :	Optional[Any]           =   re.sub(R"\s{2,}"      ,	" "      ,	_lowercase    )
							if "\n" in token:
													_lowercase       :	str           =   token.replace("\n"      ,	" __newln__"    )

							_lowercase       :	Any           =   token.split(" "    )
							_lowercase       :	List[Any]           =   []
							for token in tokens:
													if not len(_lowercase    ):
																			continue

													_lowercase       :	List[str]           =   token.lower()
													_lowercase       :	Tuple           =   tuple(_lowercase    )
													_lowercase       :	Tuple           =   tuple(list(word[:-1]    ) + [word[-1] + "</w>"]    )
													_lowercase       :	int           =   get_pairs(_lowercase    )

													if not pairs:
																			words.append(_lowercase    )
																			continue

													while True:
																			_lowercase       :	Optional[Any]           =   min(_lowercase      ,	key=lambda snake_case    : self.bpe_ranks.get(_lowercase      ,	float("inf"    )    )    )
																			if bigram not in self.bpe_ranks:
																									break
																			_lowercase      ,    _lowercase       :	List[str]           =   bigram
																			_lowercase       :	str           =   []
																			_lowercase       :	List[str]           =   0

																			while i < len(_lowercase    ):
																									try:
																															_lowercase       :	str           =   word.index(_lowercase      ,	_lowercase    )
																															new_word.extend(word[i:j]    )
																															_lowercase       :	Union[str, Any]           =   j
																									except ValueError:
																															new_word.extend(word[i:]    )
																															break

																									if word[i] == first and i < len(_lowercase    ) - 1 and word[i + 1] == second:
																															new_word.append(first + second    )
																															i += 2
																									else:
																															new_word.append(word[i]    )
																															i += 1
																			_lowercase       :	Optional[int]           =   tuple(_lowercase    )
																			_lowercase       :	Any           =   new_word
																			if len(_lowercase    ) == 1:
																									break
																			else:
																									_lowercase       :	Union[str, Any]           =   get_pairs(_lowercase    )
													_lowercase       :	Tuple           =   "@@ ".join(_lowercase    )
													_lowercase       :	List[str]           =   word[:-4]

													_lowercase       :	Any           =   word
													words.append(_lowercase    )
							return " ".join(_lowercase    )






	def       _a(self				: Dict      ,	snake_case				: List[str]    ) ->			List[str]:
							_lowercase       :	Union[str, Any]           =   []

							_lowercase       :	List[str]           =   re.findall(R"\S+\n?"      ,	_lowercase    )

							for token in words:
													split_tokens.extend(list(self.bpe(_lowercase    ).split(" "    )    )    )
							return split_tokens






	def       _a(self				: Optional[int]      ,	snake_case				: Optional[Any]    ) ->			int:
							_lowercase       :	Optional[Any]           =   token.lower()
							return self.encoder.get(_lowercase      ,	self.encoder.get(self.unk_token    )    )






	def       _a(self				: int      ,	snake_case				: Union[str, Any]    ) ->			str:
							return self.decoder.get(_lowercase      ,	self.unk_token    )






	def       _a(self				: str      ,	snake_case				: int    ) ->			str:
							_lowercase       :	Optional[int]           =   " ".join(_lowercase    ).replace("@@ "      ,	""    ).strip()
							return out_string






	def       _a(self				: Any      ,	snake_case				: Dict      ,	snake_case				: Optional[Any] = None    ) ->			Tuple[str]:
							if not os.path.isdir(_lowercase    ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
													return
							_lowercase       :	List[Any]           =   os.path.join(
							    _lowercase      ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]    )
							_lowercase       :	Tuple           =   os.path.join(
							    _lowercase      ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]    )

							with open(_lowercase      ,	"w"      ,	encoding="utf-8"    ) as f:
													f.write(json.dumps(self.encoder      ,	indent=2      ,	sort_keys=_lowercase      ,	ensure_ascii=_lowercase    ) + "\n"    )

							_lowercase       :	Optional[int]           =   0
							with open(_lowercase      ,	"w"      ,	encoding="utf-8"    ) as writer:
													writer.write("#version: 0.2\n"    )
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      ,	key=lambda snake_case    : kv[1]    ):
																			if index != token_index:
																									logger.warning(
																									    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																									    " Please check that the tokenizer is not corrupted!"    )
																									_lowercase       :	List[str]           =   token_index
																			writer.write(" ".join(_lowercase    ) + "\n"    )
																			index += 1

							return vocab_file, merge_file







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE		:Union[str, Any]						=     {
    """configuration_speecht5""": [
        """SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP""",
        """SpeechT5Config""",
        """SpeechT5HifiGanConfig""",
    ],
    """feature_extraction_speecht5""": ["""SpeechT5FeatureExtractor"""],
    """processing_speecht5""": ["""SpeechT5Processor"""],
}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Union[str, Any]						=     ["""SpeechT5Tokenizer"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Any						=     [
     """SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """SpeechT5ForSpeechToText""",
     """SpeechT5ForSpeechToSpeech""",
     """SpeechT5ForTextToSpeech""",
     """SpeechT5Model""",
     """SpeechT5PreTrainedModel""",
     """SpeechT5HifiGan""",
 ]

if TYPE_CHECKING:
 from .configuration_speechta import (
     SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
     SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
     SpeechTaConfig,
     SpeechTaHifiGanConfig,
 )
 from .feature_extraction_speechta import SpeechTaFeatureExtractor
 from .processing_speechta import SpeechTaProcessor

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_speechta import SpeechTaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speechta import (
      SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechTaForSpeechToSpeech,
      SpeechTaForSpeechToText,
      SpeechTaForTextToSpeech,
      SpeechTaHifiGan,
      SpeechTaModel,
      SpeechTaPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE		:List[str]						=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
