'''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''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/vocab.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/vocab.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/vocab.json''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/merges.txt''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/merges.txt''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/merges.txt''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'''
        ),
    },
}

lowercase_  		=			{
    '''roberta-base''': 512,
    '''roberta-large''': 512,
    '''roberta-large-mnli''': 512,
    '''distilroberta-base''': 512,
    '''roberta-base-openai-detector''': 512,
    '''roberta-large-openai-detector''': 512,
}



@lru_cache()
def 				UpperCamelCase__      (      ):


						'''simple docstring'''






						_lowerCAmelCase					    =(
						    list(range(ord('!'   )      ,   ord('~'   ) + 1   )   ) + list(range(ord('¡'   )      ,   ord('¬'   ) + 1   )   ) + list(range(ord('®'   )      ,   ord('ÿ'   ) + 1   )   )
						)
						_lowerCAmelCase					    =bs[:]
						_lowerCAmelCase					    =0
						for b in range(2**8   ):
												if b not in bs:
																		bs.append(a__   )
																		cs.append(2**8 + n   )
																		n += 1
						_lowerCAmelCase					    =[chr(a__   ) for n in cs]
						return dict(zip(a__      ,   a__   )   )



def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						_lowerCAmelCase					    =set()
						_lowerCAmelCase					    =word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)   )
												_lowerCAmelCase					    =char
						return pairs


class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   Any							=				VOCAB_FILES_NAMES
		lowercase :   Union[str, Any]							=				PRETRAINED_VOCAB_FILES_MAP
		lowercase :   Union[str, Any]							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase :   Optional[int]							=				['input_ids', 'attention_mask']






		def __init__( self		,    __A		,    __A		,    __A="replace"		,    __A="<s>"		,    __A="</s>"		,    __A="</s>"		,    __A="<s>"		,    __A="<unk>"		,    __A="<pad>"		,    __A="<mask>"		,    __A=False		,    **__A		,    )			->  Union[str, Any]:
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else bos_token
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else eos_token
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else sep_token
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else cls_token
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else unk_token
								_lowerCAmelCase					    =AddedToken(__A		,    lstrip=__A		,    rstrip=__A					) if isinstance(__A		,    __A					) else pad_token

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

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

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

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






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






		def 		UpperCamelCase__							( self					)			->  Optional[Any]:
								return dict(self.encoder		,    **self.added_tokens_encoder					)






		def 		UpperCamelCase__							( self		,    __A					)			->  Any:
								if token in self.cache:
														return self.cache[token]
								_lowerCAmelCase					    =tuple(__A					)
								_lowerCAmelCase					    =get_pairs(__A					)

								if not pairs:
														return token

								while True:
														_lowerCAmelCase					    =min(__A		,    key=lambda __A					: self.bpe_ranks.get(__A		,    float('inf'					)					)					)
														if bigram not in self.bpe_ranks:
																				break
														_lowerCAmelCase    ,					_lowerCAmelCase					    =bigram
														_lowerCAmelCase					    =[]
														_lowerCAmelCase					    =0
														while i < len(__A					):
																				try:
																										_lowerCAmelCase					    =word.index(__A		,    __A					)
																				except ValueError:
																										new_word.extend(word[i:]					)
																										break
																				else:
																										new_word.extend(word[i:j]					)
																										_lowerCAmelCase					    =j

																				if word[i] == first and i < len(__A					) - 1 and word[i + 1] == second:
																										new_word.append(first + second					)
																										i += 2
																				else:
																										new_word.append(word[i]					)
																										i += 1
														_lowerCAmelCase					    =tuple(__A					)
														_lowerCAmelCase					    =new_word
														if len(__A					) == 1:
																				break
														else:
																				_lowerCAmelCase					    =get_pairs(__A					)
								_lowerCAmelCase					    =' '.join(__A					)
								_lowerCAmelCase					    =word
								return word






		def 		UpperCamelCase__							( self		,    __A					)			->  List[Any]:
								_lowerCAmelCase					    =[]
								for token in re.findall(self.pat		,    __A					):
														_lowerCAmelCase					    =''.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(__A					).split(' '					)					)
								return bpe_tokens






		def 		UpperCamelCase__							( self		,    __A					)			->  Dict:
								return self.encoder.get(__A		,    self.encoder.get(self.unk_token					)					)






		def 		UpperCamelCase__							( self		,    __A					)			->  Union[str, Any]:
								return self.decoder.get(__A					)






		def 		UpperCamelCase__							( self		,    __A					)			->  str:
								_lowerCAmelCase					    =''.join(__A					)
								_lowerCAmelCase					    =bytearray([self.byte_decoder[c] for c in text]					).decode('utf-8'		,    errors=self.errors					)
								return text






		def 		UpperCamelCase__							( self		,    __A		,    __A = None					)			->  Tuple[str]:
								if not os.path.isdir(__A					):
														logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
														return
								_lowerCAmelCase					    =os.path.join(
								    __A		,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)
								_lowerCAmelCase					    =os.path.join(
								    __A		,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']					)

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

								_lowerCAmelCase					    =0
								with open(__A		,    '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					    =token_index
																				writer.write(' '.join(__A					) + '\n'					)
																				index += 1

								return vocab_file, merge_file






		def 		UpperCamelCase__							( self		,    __A		,    __A = None					)			->  List[int]:
								if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								_lowerCAmelCase					    =[self.cls_token_id]
								_lowerCAmelCase					    =[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep






		def 		UpperCamelCase__							( self		,    __A		,    __A = None		,    __A = False					)			->  List[int]:
								if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=__A		,    token_ids_a=__A		,    already_has_special_tokens=__A					)

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






		def 		UpperCamelCase__							( self		,    __A		,    __A = None					)			->  List[int]:
								_lowerCAmelCase					    =[self.sep_token_id]
								_lowerCAmelCase					    =[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 		UpperCamelCase__							( self		,    __A		,    __A=False		,    **__A					)			->  List[str]:
								_lowerCAmelCase					    =kwargs.pop('add_prefix_space'		,    self.add_prefix_space					)
								if (is_split_into_words or add_prefix_space) and (len(__A					) > 0 and not text[0].isspace()):
														_lowerCAmelCase					    =' ' + text
								return (text, kwargs)






'''simple docstring'''

import copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


lowercase_  		=			logging.get_logger(__name__)
class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   Any							=				'semantic'






		def __init__( self		,    __A=1_0000		,    __A=True		,    __A=768		,    __A=False		,    __A=False		,    __A=False		,    __A=False		,    __A=0.7		,    __A=True		,    __A=1_0048		,    __A=12_9595		,    __A=12_9599		,    __A=1_0000		,    __A=256		,    __A=49.9		,    **__A		,    )			->  Any:
								super().__init__(
								    temperature=__A		,    do_sample=__A		,    eos_token_id=__A		,    renormalize_logits=__A		,    max_new_tokens=__A		,    output_scores=__A		,    return_dict_in_generate=__A		,    output_hidden_states=__A		,    output_attentions=__A		,    **__A		,    )

								_lowerCAmelCase					    =text_encoding_offset
								_lowerCAmelCase					    =text_pad_token
								_lowerCAmelCase					    =eos_token_id
								_lowerCAmelCase					    =semantic_infer_token
								_lowerCAmelCase					    =semantic_vocab_size
								_lowerCAmelCase					    =max_input_semantic_length
								_lowerCAmelCase					    =semantic_rate_hz

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   Any							=				'coarse_acoustics'






		def __init__( self		,    __A=True		,    __A=False		,    __A=False		,    __A=False		,    __A=False		,    __A=0.7		,    __A=True		,    __A=1_2048		,    __A=75		,    __A=2		,    __A=1_2050		,    __A=256		,    __A = 630		,    __A = 60		,    **__A		,    )			->  Union[str, Any]:
								super().__init__(
								    temperature=__A		,    do_sample=__A		,    renormalize_logits=__A		,    output_scores=__A		,    return_dict_in_generate=__A		,    output_hidden_states=__A		,    output_attentions=__A		,    **__A		,    )

								_lowerCAmelCase					    =coarse_semantic_pad_token
								_lowerCAmelCase					    =coarse_rate_hz
								_lowerCAmelCase					    =n_coarse_codebooks
								_lowerCAmelCase					    =coarse_infer_token
								_lowerCAmelCase					    =max_coarse_input_length
								_lowerCAmelCase					    =max_coarse_history
								_lowerCAmelCase					    =sliding_window_len

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   str							=				'fine_acoustics'






		def __init__( self		,    __A=0.5		,    __A=512		,    __A=1024		,    __A=8		,    **__A		,    )			->  int:
								super().__init__(temperature=__A					)

								_lowerCAmelCase					    =max_fine_history_length
								_lowerCAmelCase					    =max_fine_input_length
								_lowerCAmelCase					    =n_fine_codebooks

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   int							=				'bark'
		lowercase :   Optional[Any]							=				True






		def __init__( self		,    __A = None		,    __A = None		,    __A = None		,    __A=2_4000		,    __A=1024		,    **__A		,    )			->  Optional[int]:
								if semantic_config is None:
														_lowerCAmelCase					    ={}
														logger.info('semantic_config is None. initializing the semantic model with default values.'					)

								if coarse_acoustics_config is None:
														_lowerCAmelCase					    ={}
														logger.info('coarse_acoustics_config is None. initializing the coarse model with default values.'					)

								if fine_acoustics_config is None:
														_lowerCAmelCase					    ={}
														logger.info('fine_acoustics_config is None. initializing the fine model with default values.'					)

								_lowerCAmelCase					    =BarkSemanticGenerationConfig(**__A					)
								_lowerCAmelCase					    =BarkCoarseGenerationConfig(**__A					)
								_lowerCAmelCase					    =BarkFineGenerationConfig(**__A					)

								_lowerCAmelCase					    =sample_rate
								_lowerCAmelCase					    =codebook_size






		@classmethod
		def 		UpperCamelCase__							( cls		,    __A		,    __A		,    __A		,    **__A		,    )			->  List[Any]:
								return cls(
								    semantic_config=semantic_config.to_dict()		,    coarse_acoustics_config=coarse_acoustics_config.to_dict()		,    fine_acoustics_config=fine_acoustics_config.to_dict()		,    **__A		,    )






		def 		UpperCamelCase__							( self					)			->  Optional[int]:
								_lowerCAmelCase					    =copy.deepcopy(self.__dict__					)

								_lowerCAmelCase					    =self.semantic_config.to_dict()
								_lowerCAmelCase					    =self.coarse_acoustics_config.to_dict()
								_lowerCAmelCase					    =self.fine_acoustics_config.to_dict()

								_lowerCAmelCase					    =self.__class__.model_type
								return output





