






"""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


lowercase__          = logging.get_logger(__name__)


lowercase__          = {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

lowercase__          = {
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
}

lowercase__          = {
    'allenai/longformer-base-4096': 4096,
    'allenai/longformer-large-4096': 4096,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4096,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4096,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4096,
}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 		__lowerCamelCase	(  )						->    Optional[int]:

		"""simple docstring"""







		lowerCAmelCase_   :							List[str]									=			(
		    list(range(ord("!"       )      ,       ord("~"       ) + 1       )       ) + list(range(ord("¡"       )      ,       ord("¬"       ) + 1       )       ) + list(range(ord("®"       )      ,       ord("ÿ"       ) + 1       )       )
		)
		lowerCAmelCase_   :							Tuple									=			bs[:]
		lowerCAmelCase_   :							Any									=			0
		for b in range(2**8       ):
				if b not in bs:
						bs.append(lowercase__       )
						cs.append(2**8 + n       )
						n += 1
		lowerCAmelCase_   :							Dict									=			[chr(lowercase__       ) for n in cs]
		return dict(zip(lowercase__      ,       lowercase__       )       )

def 		__lowerCamelCase	(  __UpperCamelCase       )						->    Dict:

		"""simple docstring"""







		lowerCAmelCase_   :							Dict									=			set()
		lowerCAmelCase_   :							List[Any]									=			word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)       )
				lowerCAmelCase_   :							List[str]									=			char
		return pairs



class 		__lowerCamelCase				( A__			):





		'''simple docstring'''






		a_	:				Optional[Any]            =							VOCAB_FILES_NAMES
		a_	:				Any            =							PRETRAINED_VOCAB_FILES_MAP
		a_	:				Dict            =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a_	:				Union[str, Any]            =							['''input_ids''', '''attention_mask''']





		def __init__(   self							:	str						,			a_							:	List[str]						,			a_							:	Any						,			a_							:	List[Any]="replace"						,			a_							:	Union[str, Any]="<s>"						,			a_							:	str="</s>"						,			a_							:	str="</s>"						,			a_							:	Any="<s>"						,			a_							:	Optional[Any]="<unk>"						,			a_							:	Tuple="<pad>"						,			a_							:	Optional[Any]="<mask>"						,			a_							:	Any=False						,			**a_							:	str						,			):
				lowerCAmelCase_   :							Optional[Any]									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else bos_token
				lowerCAmelCase_   :							Optional[int]									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else eos_token
				lowerCAmelCase_   :							Any									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else sep_token
				lowerCAmelCase_   :							List[Any]									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else cls_token
				lowerCAmelCase_   :							Optional[Any]									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else unk_token
				lowerCAmelCase_   :							Optional[int]									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else pad_token

				# Mask token behave like a normal word, i.e. include the space before it
				lowerCAmelCase_   :							Any									=			AddedToken(lowerCAmelCase__						,			lstrip=lowerCAmelCase__						,			rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__						,			lowerCAmelCase__	) else mask_token

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

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

				# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
				lowerCAmelCase_   :							Optional[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    lowerCamelCase       (   self							:	Tuple	):
				return len(self.encoder	)





		def    lowerCamelCase       (   self							:	Dict	):
				return dict(self.encoder						,			**self.added_tokens_encoder	)





		def    lowerCamelCase       (   self							:	Union[str, Any]						,			a_							:	Any	):
				if token in self.cache:
						return self.cache[token]
				lowerCAmelCase_   :							Optional[int]									=			tuple(lowerCAmelCase__	)
				lowerCAmelCase_   :							Optional[int]									=			get_pairs(lowerCAmelCase__	)

				if not pairs:
						return token

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

								if word[i] == first and i < len(lowerCAmelCase__	) - 1 and word[i + 1] == second:
										new_word.append(first + second	)
										i += 2
								else:
										new_word.append(word[i]	)
										i += 1
						lowerCAmelCase_   :							Union[str, Any]									=			tuple(lowerCAmelCase__	)
						lowerCAmelCase_   :							Optional[Any]									=			new_word
						if len(lowerCAmelCase__	) == 1:
								break
						else:
								lowerCAmelCase_   :							Optional[Any]									=			get_pairs(lowerCAmelCase__	)
				lowerCAmelCase_   :							Dict									=			''' '''.join(lowerCAmelCase__	)
				lowerCAmelCase_   :							Optional[Any]									=			word
				return word





		def    lowerCamelCase       (   self							:	Tuple						,			a_							:	List[Any]	):
				lowerCAmelCase_   :							Optional[int]									=			[]
				for token in re.findall(self.pat						,			lowerCAmelCase__	):
						lowerCAmelCase_   :							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(lowerCAmelCase__	).split(" "	)	)
				return bpe_tokens





		def    lowerCamelCase       (   self							:	Dict						,			a_							:	Dict	):
				return self.encoder.get(lowerCAmelCase__						,			self.encoder.get(self.unk_token	)	)





		def    lowerCamelCase       (   self							:	int						,			a_							:	List[str]	):
				return self.decoder.get(lowerCAmelCase__	)





		def    lowerCamelCase       (   self							:	str						,			a_							:	str	):
				lowerCAmelCase_   :							Dict									=			''''''.join(lowerCAmelCase__	)
				lowerCAmelCase_   :							Union[str, Any]									=			bytearray([self.byte_decoder[c] for c in text]	).decode("utf-8"						,			errors=self.errors	)
				return text





		def    lowerCamelCase       (   self							:	Optional[int]						,			a_							:	str						,			a_							:	Optional[str] = None	):
				if not os.path.isdir(lowerCAmelCase__	):
						logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
						return
				lowerCAmelCase_   :							Any									=			os.path.join(
				    lowerCAmelCase__						,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
				lowerCAmelCase_   :							Dict									=			os.path.join(
				    lowerCAmelCase__						,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]	)

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

				lowerCAmelCase_   :							Optional[Any]									=			0
				with open(lowerCAmelCase__						,			"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 a_	: 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_   :							Tuple									=			token_index
								writer.write(" ".join(lowerCAmelCase__	) + "\n"	)
								index += 1

				return vocab_file, merge_file





		def    lowerCamelCase       (   self							:	Any						,			a_							:	List[int]						,			a_							:	Optional[List[int]] = None	):
				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[int]									=			[self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep





		def    lowerCamelCase       (   self							:	str						,			a_							:	List[int]						,			a_							:	Optional[List[int]] = None						,			a_							:	bool = False	):
				if already_has_special_tokens:
						return super().get_special_tokens_mask(
						    token_ids_a=lowerCAmelCase__						,			token_ids_a=lowerCAmelCase__						,			already_has_special_tokens=lowerCAmelCase__	)

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





		def    lowerCamelCase       (   self							:	Union[str, Any]						,			a_							:	List[int]						,			a_							:	Optional[List[int]] = None	):
				lowerCAmelCase_   :							Optional[Any]									=			[self.sep_token_id]
				lowerCAmelCase_   :							Optional[Any]									=			[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    lowerCamelCase       (   self							:	str						,			a_							:	Union[str, Any]						,			a_							:	List[str]=False						,			**a_							:	Any	):
				lowerCAmelCase_   :							Tuple									=			kwargs.pop("add_prefix_space"						,			self.add_prefix_space	)
				if (is_split_into_words or add_prefix_space) and (len(lowerCAmelCase__	) > 0 and not text[0].isspace()):
						lowerCAmelCase_   :							int									=			''' ''' + text
				return (text, kwargs)




import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class        _lowercase      (			unittest.TestCase       ):






				'''simple docstring'''



				def 		__magic_name__(       self			:Union[str, Any]	)		->			Tuple:
										__SCREAMING_SNAKE_CASE						:     str					=		'''ylacombe/bark-small'''
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		tempfile.mkdtemp()
										__SCREAMING_SNAKE_CASE						:     str					=		'''en_speaker_1'''
										__SCREAMING_SNAKE_CASE						:     Any					=		'''This is a test string'''
										__SCREAMING_SNAKE_CASE						:     int					=		'''speaker_embeddings_path.json'''
										__SCREAMING_SNAKE_CASE						:     int					=		'''speaker_embeddings'''


				def 		__magic_name__(       self			:List[str]			,			**lowerCAmelCase__			:Union[str, Any]	)		->			Any:
										return AutoTokenizer.from_pretrained(self.checkpoint			,			**lowerCAmelCase__	)


				def 		__magic_name__(       self			:List[str]	)		->			int:
										shutil.rmtree(self.tmpdirname	)


				def 		__magic_name__(       self			:Dict	)		->			str:
										__SCREAMING_SNAKE_CASE						:     Dict					=		self.get_tokenizer()

										__SCREAMING_SNAKE_CASE						:     Tuple					=		BarkProcessor(tokenizer=lowerCAmelCase__	)

										processor.save_pretrained(self.tmpdirname	)
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		BarkProcessor.from_pretrained(self.tmpdirname	)

										self.assertEqual(processor.tokenizer.get_vocab()			,			tokenizer.get_vocab()	)


				@slow
				def 		__magic_name__(       self			:Tuple	)		->			List[Any]:
										__SCREAMING_SNAKE_CASE						:     Dict					=		BarkProcessor.from_pretrained(
										    pretrained_processor_name_or_path=self.checkpoint			,			speaker_embeddings_dict_path=self.speaker_embeddings_dict_path			,			)
										processor.save_pretrained(
										    self.tmpdirname			,			speaker_embeddings_dict_path=self.speaker_embeddings_dict_path			,			speaker_embeddings_directory=self.speaker_embeddings_directory			,			)

										__SCREAMING_SNAKE_CASE						:     Dict					=		self.get_tokenizer(bos_token='''(BOS)'''			,			eos_token='''(EOS)'''	)

										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		BarkProcessor.from_pretrained(
										    self.tmpdirname			,			self.speaker_embeddings_dict_path			,			bos_token='''(BOS)'''			,			eos_token='''(EOS)'''			,			)

										self.assertEqual(processor.tokenizer.get_vocab()			,			tokenizer_add_kwargs.get_vocab()	)


				def 		__magic_name__(       self			:List[str]	)		->			Tuple:
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		BarkProcessor.from_pretrained(
										    pretrained_processor_name_or_path=self.checkpoint			,			speaker_embeddings_dict_path=self.speaker_embeddings_dict_path			,			)

										__SCREAMING_SNAKE_CASE						:     str					=		35
										__SCREAMING_SNAKE_CASE						:     str					=		2
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		8

										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		{
										    '''semantic_prompt''': np.ones(lowerCAmelCase__	),
										    '''coarse_prompt''': np.ones((nb_codebooks_coarse, seq_len)	),
										    '''fine_prompt''': np.ones((nb_codebooks_total, seq_len)	),
										}

										# test providing already loaded voice_preset
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		processor(text=self.input_string			,			voice_preset=lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     List[str]					=		inputs['''history_prompt''']
										for key in voice_preset:
																self.assertListEqual(voice_preset[key].tolist()			,			processed_voice_preset.get(lowerCAmelCase__			,			np.array([]	)	).tolist()	)

										# test loading voice preset from npz file
										__SCREAMING_SNAKE_CASE						:     str					=		os.path.join(self.tmpdirname			,			'''file.npz'''	)
										np.savez(lowerCAmelCase__			,			**lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[Any]					=		processor(text=self.input_string			,			voice_preset=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		inputs['''history_prompt''']

										for key in voice_preset:
																self.assertListEqual(voice_preset[key].tolist()			,			processed_voice_preset.get(lowerCAmelCase__			,			np.array([]	)	).tolist()	)

										# test loading voice preset from the hub
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		processor(text=self.input_string			,			voice_preset=self.voice_preset	)



				def 		__magic_name__(       self			:Tuple	)		->			Optional[Any]:
										__SCREAMING_SNAKE_CASE						:     Tuple					=		self.get_tokenizer()

										__SCREAMING_SNAKE_CASE						:     Any					=		BarkProcessor(tokenizer=lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		processor(text=self.input_string	)

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer(
										    self.input_string			,			padding='''max_length'''			,			max_length=256			,			add_special_tokens=lowerCAmelCase__			,			return_attention_mask=lowerCAmelCase__			,			return_token_type_ids=lowerCAmelCase__			,			)

										for key in encoded_tok.keys():
																self.assertListEqual(encoded_tok[key]			,			encoded_processor[key].squeeze().tolist()	)
