

"""simple docstring"""


import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__A						       =      logging.get_logger(__name__)


__A						       =      {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all BART models at https://huggingface.co/models?filter=bart
__A						       =      {
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
}

__A						       =      {
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






@lru_cache()
def    a__   (   )     ->     Optional[Any]:
		__lowerCAmelCase:	Tuple   				=      (
		    list(range(ord("!"			) ,			ord("~"			) + 1			)			) + list(range(ord("¡"			) ,			ord("¬"			) + 1			)			) + list(range(ord("®"			) ,			ord("ÿ"			) + 1			)			)
		)
		__lowerCAmelCase:	Optional[Any]   				=      bs[:]
		__lowerCAmelCase:	Tuple   				=      0
		for b in range(2**8			):
				if b not in bs:
						bs.append(__SCREAMING_SNAKE_CASE			)
						cs.append(2**8 + n			)
						n += 1
		__lowerCAmelCase:	Optional[int]   				=      [chr(__SCREAMING_SNAKE_CASE			) for n in cs]
		return dict(zip(__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE			)			)






def    a__   (   __SCREAMING_SNAKE_CASE			)     ->     Tuple:
		__lowerCAmelCase:	Optional[int]   				=      set()
		__lowerCAmelCase:	List[str]   				=      word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)			)
				__lowerCAmelCase:	Optional[int]   				=      char
		return pairs





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Union[str, Any]       				=  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_       :				List[Any]       				=  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_       :				Any       				=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_       :				int       				=  ["""input_ids""", """attention_mask"""]

				def __init__(     self							:    List[Any]					,  UpperCamelCase__							:    Optional[int]					,  UpperCamelCase__							:    List[Any]					,  UpperCamelCase__							:    List[str]="replace"					,  UpperCamelCase__							:    Union[str, Any]="<s>"					,  UpperCamelCase__							:    Tuple="</s>"					,  UpperCamelCase__							:    Dict="</s>"					,  UpperCamelCase__							:    Dict="<s>"					,  UpperCamelCase__							:    str="<unk>"					,  UpperCamelCase__							:    str="<pad>"					,  UpperCamelCase__							:    Dict="<mask>"					,  UpperCamelCase__							:    Tuple=False					,  **UpperCamelCase__							:    Any					,  )->       List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:	List[Any]   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else bos_token
						__lowerCAmelCase:	str   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else eos_token
						__lowerCAmelCase:	Optional[int]   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else sep_token
						__lowerCAmelCase:	List[str]   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else cls_token
						__lowerCAmelCase:	Tuple   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else unk_token
						__lowerCAmelCase:	Any   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else pad_token

						# Mask token behave like a normal word, i.e. include the space before it
						__lowerCAmelCase:	List[str]   				=      AddedToken(UpperCamelCase__					,  lstrip=UpperCamelCase__					,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__					,  UpperCamelCase__) else mask_token

						super().__init__(
						    errors=UpperCamelCase__					,  bos_token=UpperCamelCase__					,  eos_token=UpperCamelCase__					,  unk_token=UpperCamelCase__					,  sep_token=UpperCamelCase__					,  cls_token=UpperCamelCase__					,  pad_token=UpperCamelCase__					,  mask_token=UpperCamelCase__					,  add_prefix_space=UpperCamelCase__					,  **UpperCamelCase__					,  )

						with open(UpperCamelCase__					,  encoding="utf-8") as vocab_handle:
								__lowerCAmelCase:	Optional[Any]   				=      json.load(UpperCamelCase__)
						__lowerCAmelCase:	Any   				=      {v: k for k, v in self.encoder.items()}
						__lowerCAmelCase:	Optional[Any]   				=      errors  # how to handle errors in decoding
						__lowerCAmelCase:	int   				=      bytes_to_unicode()
						__lowerCAmelCase:	List[str]   				=      {v: k for k, v in self.byte_encoder.items()}
						with open(UpperCamelCase__					,  encoding="utf-8") as merges_handle:
								__lowerCAmelCase:	List[str]   				=      merges_handle.read().split("\n")[1:-1]
						__lowerCAmelCase:	Dict   				=      [tuple(merge.split()) for merge in bpe_merges]
						__lowerCAmelCase:	int   				=      dict(zip(UpperCamelCase__					,  range(len(UpperCamelCase__))))
						__lowerCAmelCase:	List[Any]   				=      {}
						__lowerCAmelCase:	Optional[int]   				=      add_prefix_space

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						__lowerCAmelCase:	Union[str, Any]   				=      re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+")

				@property
				def 							lowercase_					(     self							:    Optional[int])->       str:



						'''simple docstring'''


						return len(self.encoder)

				def 							lowercase_					(     self							:    Dict)->       Optional[Any]:



						'''simple docstring'''


						return dict(self.encoder					,  **self.added_tokens_encoder)

				def 							lowercase_					(     self							:    List[str]					,  UpperCamelCase__							:    Any)->       Union[str, Any]:



						'''simple docstring'''


						if token in self.cache:
								return self.cache[token]
						__lowerCAmelCase:	Any   				=      tuple(UpperCamelCase__)
						__lowerCAmelCase:	str   				=      get_pairs(UpperCamelCase__)

						if not pairs:
								return token

						while True:
								__lowerCAmelCase:	Optional[int]   				=      min(UpperCamelCase__					,  key=lambda UpperCamelCase__: self.bpe_ranks.get(UpperCamelCase__					,  float("inf")))
								if bigram not in self.bpe_ranks:
										break
								__lowerCAmelCase				,			__lowerCAmelCase:	int   				=      bigram
								__lowerCAmelCase:	int   				=      []
								__lowerCAmelCase:	Union[str, Any]   				=      0
								while i < len(UpperCamelCase__):
										try:
												__lowerCAmelCase:	Tuple   				=      word.index(UpperCamelCase__					,  UpperCamelCase__)
										except ValueError:
												new_word.extend(word[i:])
												break
										else:
												new_word.extend(word[i:j])
												__lowerCAmelCase:	Tuple   				=      j

										if word[i] == first and i < len(UpperCamelCase__) - 1 and word[i + 1] == second:
												new_word.append(first + second)
												i += 2
										else:
												new_word.append(word[i])
												i += 1
								__lowerCAmelCase:	Optional[Any]   				=      tuple(UpperCamelCase__)
								__lowerCAmelCase:	Tuple   				=      new_word
								if len(UpperCamelCase__) == 1:
										break
								else:
										__lowerCAmelCase:	Any   				=      get_pairs(UpperCamelCase__)
						__lowerCAmelCase:	Optional[Any]   				=      " ".join(UpperCamelCase__)
						__lowerCAmelCase:	Dict   				=      word
						return word

				def 							lowercase_					(     self							:    int					,  UpperCamelCase__							:    List[str])->       Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase:	Dict   				=      []
						for token in re.findall(self.pat					,  UpperCamelCase__):
								__lowerCAmelCase:	List[str]   				=      "".join(
								    self.byte_encoder[b] for b in token.encode("utf-8"))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
								bpe_tokens.extend(bpe_token for bpe_token in self.bpe(UpperCamelCase__).split(" "))
						return bpe_tokens

				def 							lowercase_					(     self							:    Optional[Any]					,  UpperCamelCase__							:    Dict)->       int:



						'''simple docstring'''


						return self.encoder.get(UpperCamelCase__					,  self.encoder.get(self.unk_token))

				def 							lowercase_					(     self							:    Optional[int]					,  UpperCamelCase__							:    int)->       List[Any]:



						'''simple docstring'''


						return self.decoder.get(UpperCamelCase__)

				def 							lowercase_					(     self							:    int					,  UpperCamelCase__							:    Tuple)->       Tuple:



						'''simple docstring'''


						__lowerCAmelCase:	Union[str, Any]   				=      "".join(UpperCamelCase__)
						__lowerCAmelCase:	Tuple   				=      bytearray([self.byte_decoder[c] for c in text]).decode("utf-8"					,  errors=self.errors)
						return text

				def 							lowercase_					(     self							:    List[Any]					,  UpperCamelCase__							:    str					,  UpperCamelCase__							:    Optional[str] = None)->       Tuple[str]:



						'''simple docstring'''


						if not os.path.isdir(UpperCamelCase__):
								logger.error(f"Vocabulary path ({save_directory}) should be a directory")
								return
						__lowerCAmelCase:	Optional[int]   				=      os.path.join(
						    UpperCamelCase__					,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])
						__lowerCAmelCase:	List[Any]   				=      os.path.join(
						    UpperCamelCase__					,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"])

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

						__lowerCAmelCase:	Any   				=      0
						with open(UpperCamelCase__					,  "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 UpperCamelCase__: 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!")
												__lowerCAmelCase:	List[str]   				=      token_index
										writer.write(" ".join(UpperCamelCase__) + "\n")
										index += 1

						return vocab_file, merge_file

				def 							lowercase_					(     self							:    str					,  UpperCamelCase__							:    List[int]					,  UpperCamelCase__							:    Optional[List[int]] = None)->       List[int]:



						'''simple docstring'''


						if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						__lowerCAmelCase:	Union[str, Any]   				=      [self.cls_token_id]
						__lowerCAmelCase:	Optional[Any]   				=      [self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep

				def 							lowercase_					(     self							:    str					,  UpperCamelCase__							:    List[int]					,  UpperCamelCase__							:    Optional[List[int]] = None					,  UpperCamelCase__							:    bool = False)->       List[int]:



						'''simple docstring'''


						if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=UpperCamelCase__					,  token_ids_a=UpperCamelCase__					,  already_has_special_tokens=UpperCamelCase__)

						if token_ids_a is None:
								return [1] + ([0] * len(UpperCamelCase__)) + [1]
						return [1] + ([0] * len(UpperCamelCase__)) + [1, 1] + ([0] * len(UpperCamelCase__)) + [1]

				def 							lowercase_					(     self							:    List[Any]					,  UpperCamelCase__							:    List[int]					,  UpperCamelCase__							:    Optional[List[int]] = None)->       List[int]:



						'''simple docstring'''


						__lowerCAmelCase:	str   				=      [self.sep_token_id]
						__lowerCAmelCase:	Dict   				=      [self.cls_token_id]

						if token_ids_a is None:
								return len(cls + token_ids_a + sep) * [0]
						return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]




				def 							lowercase_					(     self							:    int					,  UpperCamelCase__							:    str					,  UpperCamelCase__							:    int=False					,  **UpperCamelCase__							:    List[str])->       Any:



						'''simple docstring'''


						__lowerCAmelCase:	Dict   				=      kwargs.pop("add_prefix_space"					,  self.add_prefix_space)
						if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase__) > 0 and not text[0].isspace()):
								__lowerCAmelCase:	Optional[int]   				=      " " + text
						return (text, kwargs)





"""simple docstring"""


from typing import TYPE_CHECKING

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


__A						       =      {
    "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:
			__A						       =      ["SpeechT5Tokenizer"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A						       =      [
			    "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

			__A						       =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


