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


_SCREAMING_SNAKE_CASE:    str     						=							logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE:    Optional[int]     						=							{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

_SCREAMING_SNAKE_CASE:    Optional[Any]     						=							{
    '''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'''
        ),
    },
}

_SCREAMING_SNAKE_CASE:    int     						=							{
    '''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"""





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






def  UpperCAmelCase__(    lowerCamelCase_	):



			"""simple docstring"""





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







class 						_SCREAMING_SNAKE_CASE				(  _lowercase				):






		"""simple docstring"""







		A_    			=   VOCAB_FILES_NAMES
		A_    			=   PRETRAINED_VOCAB_FILES_MAP
		A_    			=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		A_    			=   ['''input_ids''', '''attention_mask''']



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






					"""simple docstring"""
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else bos_token
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else eos_token
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else sep_token
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else cls_token
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else unk_token
					_snake_case														=   AddedToken(__SCREAMING_SNAKE_CASE	,       lstrip=__SCREAMING_SNAKE_CASE	,       rstrip=__SCREAMING_SNAKE_CASE ) if isinstance(__SCREAMING_SNAKE_CASE	,       __SCREAMING_SNAKE_CASE ) else pad_token

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

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

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

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



		@property
		def 					_a					(      self     :					Optional[Any] ):






					"""simple docstring"""
					return len(self.encoder )



		def 					_a					(      self     :					List[str] ):






					"""simple docstring"""
					return dict(self.encoder	,       **self.added_tokens_encoder )



		def 					_a					(      self     :					Tuple	,       __SCREAMING_SNAKE_CASE     :					Tuple ):






					"""simple docstring"""
					if token in self.cache:
								return self.cache[token]
					_snake_case														=   tuple(__SCREAMING_SNAKE_CASE )
					_snake_case														=   get_pairs(__SCREAMING_SNAKE_CASE )

					if not pairs:
								return token

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

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



		def 					_a					(      self     :					Any	,       __SCREAMING_SNAKE_CASE     :					Optional[int] ):






					"""simple docstring"""
					_snake_case														=   []
					for token in re.findall(self.pat	,       __SCREAMING_SNAKE_CASE ):
								_snake_case														=   "".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(__SCREAMING_SNAKE_CASE ).split(" " ) )
					return bpe_tokens



		def 					_a					(      self     :					List[str]	,       __SCREAMING_SNAKE_CASE     :					List[str] ):






					"""simple docstring"""
					return self.encoder.get(__SCREAMING_SNAKE_CASE	,       self.encoder.get(self.unk_token ) )



		def 					_a					(      self     :					Dict	,       __SCREAMING_SNAKE_CASE     :					int ):






					"""simple docstring"""
					return self.decoder.get(__SCREAMING_SNAKE_CASE )



		def 					_a					(      self     :					List[Any]	,       __SCREAMING_SNAKE_CASE     :					Tuple ):






					"""simple docstring"""
					_snake_case														=   "".join(__SCREAMING_SNAKE_CASE )
					_snake_case														=   bytearray([self.byte_decoder[c] for c in text] ).decode("utf-8"	,       errors=self.errors )
					return text



		def 					_a					(      self     :					Tuple	,       __SCREAMING_SNAKE_CASE     :					str	,       __SCREAMING_SNAKE_CASE     :					Optional[str] = None ):






					"""simple docstring"""
					if not os.path.isdir(__SCREAMING_SNAKE_CASE ):
								logger.error(F'Vocabulary path ({save_directory}) should be a directory' )
								return
					_snake_case														=   os.path.join(
					    __SCREAMING_SNAKE_CASE	,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
					_snake_case														=   os.path.join(
					    __SCREAMING_SNAKE_CASE	,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"] )

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

					_snake_case														=   0
					with open(__SCREAMING_SNAKE_CASE	,       "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!" )
														_snake_case														=   token_index
											writer.write(" ".join(__SCREAMING_SNAKE_CASE ) + "\n" )
											index += 1

					return vocab_file, merge_file



		def 					_a					(      self     :					str	,       __SCREAMING_SNAKE_CASE     :					List[int]	,       __SCREAMING_SNAKE_CASE     :					Optional[List[int]] = None ):






					"""simple docstring"""
					if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_snake_case														=   [self.cls_token_id]
					_snake_case														=   [self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep



		def 					_a					(      self     :					Dict	,       __SCREAMING_SNAKE_CASE     :					List[int]	,       __SCREAMING_SNAKE_CASE     :					Optional[List[int]] = None	,       __SCREAMING_SNAKE_CASE     :					bool = False ):






					"""simple docstring"""
					if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=__SCREAMING_SNAKE_CASE	,       token_ids_a=__SCREAMING_SNAKE_CASE	,       already_has_special_tokens=__SCREAMING_SNAKE_CASE )

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



		def 					_a					(      self     :					str	,       __SCREAMING_SNAKE_CASE     :					List[int]	,       __SCREAMING_SNAKE_CASE     :					Optional[List[int]] = None ):






					"""simple docstring"""
					_snake_case														=   [self.sep_token_id]
					_snake_case														=   [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 					_a					(      self     :					List[str]	,       __SCREAMING_SNAKE_CASE     :					List[Any]	,       __SCREAMING_SNAKE_CASE     :					List[Any]=False	,       **__SCREAMING_SNAKE_CASE     :					Dict ):






					"""simple docstring"""
					_snake_case														=   kwargs.pop("add_prefix_space"	,       self.add_prefix_space )
					if (is_split_into_words or add_prefix_space) and (len(__SCREAMING_SNAKE_CASE ) > 0 and not text[0].isspace()):
								_snake_case														=   " " + text
					return (text, kwargs)


import sys

from transformers import AutoTokenizer


_SCREAMING_SNAKE_CASE:    Optional[int]     						=							sys.argv[1]
_SCREAMING_SNAKE_CASE:    int     						=							sys.argv[2]
_SCREAMING_SNAKE_CASE:    str     						=							int(sys.argv[3])

_SCREAMING_SNAKE_CASE:    Union[str, Any]     						=							0

_SCREAMING_SNAKE_CASE:    Any     						=							AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, '''rt''') as f_p:
			for line in f_p:
						_SCREAMING_SNAKE_CASE:    Any     						=							line.rstrip()

						if not line:
									print(line)
									_SCREAMING_SNAKE_CASE:    str     						=							0
									continue

						_SCREAMING_SNAKE_CASE:    Optional[int]     						=							line.split()[0]

						_SCREAMING_SNAKE_CASE:    Tuple     						=							len(tokenizer.tokenize(token))

						# Token contains strange control characters like \x96 or \x95
						# Just filter out the complete line
						if current_subwords_len == 0:
									continue

						if (subword_len_counter + current_subwords_len) > max_len:
									print('''''')
									print(line)
									_SCREAMING_SNAKE_CASE:    Any     						=							current_subwords_len
									continue

						subword_len_counter += current_subwords_len

						print(line)

