


import json
import os
from typing import Optional, Tuple

import regex as re

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


lowerCAmelCase__  :List[str]   			=							logging.get_logger(__name__)

lowerCAmelCase__  :List[str]   			=							{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCAmelCase__  :List[Any]   			=							{
    '''vocab_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json'''},
    '''merges_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt'''},
}

lowerCAmelCase__  :Tuple   			=							{
    '''ctrl''': 2_5_6,
}

lowerCAmelCase__  :int   			=							{
    '''Pregnancy''': 1_6_8_6_2_9,
    '''Christianity''': 7_6_7_5,
    '''Explain''': 1_0_6_4_2_3,
    '''Fitness''': 6_3_4_4_0,
    '''Saving''': 6_3_1_6_3,
    '''Ask''': 2_7_1_7_1,
    '''Ass''': 9_5_9_8_5,
    '''Joke''': 1_6_3_5_0_9,
    '''Questions''': 4_5_6_2_2,
    '''Thoughts''': 4_9_6_0_5,
    '''Retail''': 5_2_3_4_2,
    '''Feminism''': 1_6_4_3_3_8,
    '''Writing''': 1_1_9_9_2,
    '''Atheism''': 1_9_2_2_6_3,
    '''Netflix''': 4_8_6_1_6,
    '''Computing''': 3_9_6_3_9,
    '''Opinion''': 4_3_2_1_3,
    '''Alone''': 4_4_9_6_7,
    '''Funny''': 5_8_9_1_7,
    '''Gaming''': 4_0_3_5_8,
    '''Human''': 4_0_8_8,
    '''India''': 1_3_3_1,
    '''Joker''': 7_7_1_3_8,
    '''Diet''': 3_6_2_0_6,
    '''Legal''': 1_1_8_5_9,
    '''Norman''': 4_9_3_9,
    '''Tip''': 7_2_6_8_9,
    '''Weight''': 5_2_3_4_3,
    '''Movies''': 4_6_2_7_3,
    '''Running''': 2_3_4_2_5,
    '''Science''': 2_0_9_0,
    '''Horror''': 3_7_7_9_3,
    '''Confession''': 6_0_5_7_2,
    '''Finance''': 1_2_2_5_0,
    '''Politics''': 1_6_3_6_0,
    '''Scary''': 1_9_1_9_8_5,
    '''Support''': 1_2_6_5_4,
    '''Technologies''': 3_2_5_1_6,
    '''Teenage''': 6_6_1_6_0,
    '''Event''': 3_2_7_6_9,
    '''Learned''': 6_7_4_6_0,
    '''Notion''': 1_8_2_7_7_0,
    '''Wikipedia''': 3_7_5_8_3,
    '''Books''': 6_6_6_5,
    '''Extract''': 7_6_0_5_0,
    '''Confessions''': 1_0_2_7_0_1,
    '''Conspiracy''': 7_5_9_3_2,
    '''Links''': 6_3_6_7_4,
    '''Narcissus''': 1_5_0_4_2_5,
    '''Relationship''': 5_4_7_6_6,
    '''Relationships''': 1_3_4_7_9_6,
    '''Reviews''': 4_1_6_7_1,
    '''News''': 4_2_5_6,
    '''Translation''': 2_6_8_2_0,
    '''multilingual''': 1_2_8_4_0_6,
}

def        lowerCAmelCase__ (			a__:		List[str]       )  ->		str:


							'''simple docstring'''





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

							_UpperCAmelCase 		=			set(lowerCAmelCase__       )
							return pairs







class 		__a      (				__SCREAMING_SNAKE_CASE			):
		_a	:  Dict				=	VOCAB_FILES_NAMES
		_a	:  Dict				=	PRETRAINED_VOCAB_FILES_MAP
		_a	:  Dict				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_a	:  int				=	CONTROL_CODES
		def __init__(			self			,    _SCREAMING_SNAKE_CASE			,    _SCREAMING_SNAKE_CASE			,    _SCREAMING_SNAKE_CASE="<unk>"			,    **_SCREAMING_SNAKE_CASE						) ->       int:




									"""simple docstring"""





									super().__init__(unk_token=_a			,    **_a						)

									with open(_a			,    encoding='utf-8'						) as vocab_handle:
																_UpperCAmelCase 		=			json.load(_a						)
									_UpperCAmelCase 		=			{v: k for k, v in self.encoder.items()}
									with open(_a			,    encoding='utf-8'						) as merges_handle:
																_UpperCAmelCase 		=			merges_handle.read().split('\n'						)[1:-1]
									_UpperCAmelCase 		=			[tuple(merge.split()						) for merge in merges]
									_UpperCAmelCase 		=			dict(zip(_a			,    range(len(_a						)						)						)						)
									_UpperCAmelCase 		=			{}
		@property
		def 	UpperCAmelCase__				(			self						) ->       int:




									"""simple docstring"""





									return len(self.encoder						)
		def 	UpperCAmelCase__				(			self						) ->       int:




									"""simple docstring"""





									return dict(self.encoder			,    **self.added_tokens_encoder						)
		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE						) ->       Tuple:




									"""simple docstring"""





									if token in self.cache:
																return self.cache[token]
									_UpperCAmelCase 		=			tuple(_a						)
									_UpperCAmelCase 		=			tuple(list(word[:-1]						) + [word[-1] + '</w>']						)
									_UpperCAmelCase 		=			get_pairs(_a						)

									if not pairs:
																return token

									while True:
																_UpperCAmelCase 		=			min(_a			,    key=lambda _SCREAMING_SNAKE_CASE						: self.bpe_ranks.get(_a			,    float('inf'						)						)						)
																if bigram not in self.bpe_ranks:
																							break
																_UpperCAmelCase		,       _UpperCAmelCase 		=			bigram
																_UpperCAmelCase 		=			[]
																_UpperCAmelCase 		=			0
																while i < len(_a						):
																							try:
																														_UpperCAmelCase 		=			word.index(_a			,    _a						)
																							except ValueError:
																														new_word.extend(word[i:]						)
																														break
																							else:
																														new_word.extend(word[i:j]						)
																														_UpperCAmelCase 		=			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
																_UpperCAmelCase 		=			tuple(_a						)
																_UpperCAmelCase 		=			new_word
																if len(_a						) == 1:
																							break
																else:
																							_UpperCAmelCase 		=			get_pairs(_a						)
									_UpperCAmelCase 		=			'@@ '.join(_a						)
									_UpperCAmelCase 		=			word[:-4]
									_UpperCAmelCase 		=			word
									return word
		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE						) ->       Optional[int]:




									"""simple docstring"""





									_UpperCAmelCase 		=			[]

									_UpperCAmelCase 		=			re.findall(R'\S+\n?'			,    _a						)

									for token in words:
																split_tokens.extend(list(self.bpe(_a						).split(' '						)						)						)
									return split_tokens
		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE						) ->       Dict:




									"""simple docstring"""





									return self.encoder.get(_a			,    self.encoder.get(self.unk_token						)						)
		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE						) ->       List[Any]:




									"""simple docstring"""





									return self.decoder.get(_a			,    self.unk_token						)
		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE						) ->       Union[str, Any]:




									"""simple docstring"""





									_UpperCAmelCase 		=			' '.join(_a						).replace('@@ '			,    ''						).strip()
									return out_string






		def 	UpperCAmelCase__				(			self			,    _SCREAMING_SNAKE_CASE			,    _SCREAMING_SNAKE_CASE = None						) ->       Tuple:




									"""simple docstring"""





									if not os.path.isdir(_a						):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
																return
									_UpperCAmelCase 		=			os.path.join(
									    _a			,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)
									_UpperCAmelCase 		=			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'						)

									_UpperCAmelCase 		=			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 _SCREAMING_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!'						)
																														_UpperCAmelCase 		=			token_index
																							writer.write(' '.join(_a						) + '\n'						)
																							index += 1

									return vocab_file, merge_file

		# def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
		#     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
		#     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
		#     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
		#     return ''.join(tokens_generated_so_far)




"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowercase_			     =  {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			     =  [
				    "UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "UniSpeechForCTC",
				    "UniSpeechForPreTraining",
				    "UniSpeechForSequenceClassification",
				    "UniSpeechModel",
				    "UniSpeechPreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_unispeech import (
								    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
								    UniSpeechForCTC,
								    UniSpeechForPreTraining,
								    UniSpeechForSequenceClassification,
								    UniSpeechModel,
								    UniSpeechPreTrainedModel,
								)

else:
				import sys

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






