




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

import regex as re

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


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation

__A        =    logging.get_logger(__name__)


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

__A        =    {
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

__A        =    {"facebook/blenderbot-3B": 1_28}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 			lowerCamelCase_		(       )     ->       Dict:





				"""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(UpperCamelCase__      )
												cs.append(2**8 + n      )
												n += 1
				__lowerCamelCase		       =    [chr(UpperCamelCase__      ) for n in cs]
				return dict(zip(UpperCamelCase__ ,     UpperCamelCase__      )      )







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[Any]      )     ->       int:





				"""simple docstring"""


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







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







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


			def __init__(      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__="replace"			,						lowerCamelCase__="<s>"			,						lowerCamelCase__="</s>"			,						lowerCamelCase__="</s>"			,						lowerCamelCase__="<s>"			,						lowerCamelCase__="<unk>"			,						lowerCamelCase__="<pad>"			,						lowerCamelCase__="<mask>"			,						lowerCamelCase__=False			,						**lowerCamelCase__			,						)    ->      Optional[Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else bos_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else eos_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else sep_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else cls_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else unk_token
							__lowerCamelCase		       =    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		       =    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		       =    json.load(lowerCamelCase__							)
							__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(lowerCamelCase__			,						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(lowerCamelCase__			,						range(len(lowerCamelCase__							)							)							)							)
							__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
			# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
			def       lowercase_    (      self							)    ->      Any:



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


			def       lowercase_    (      self							)    ->      str:



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


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Dict:



							'''simple docstring'''
							if token in self.cache:
											return self.cache[token]
							__lowerCamelCase		       =    tuple(lowerCamelCase__							)
							__lowerCamelCase		       =    get_pairs(lowerCamelCase__							)

							if not pairs:
											return token

							while True:
											__lowerCamelCase		       =    min(lowerCamelCase__			,						key=lambda lowerCamelCase__							: self.bpe_ranks.get(lowerCamelCase__			,						float('inf'							)							)							)
											if bigram not in self.bpe_ranks:
															break
											__lowerCamelCase       ,						__lowerCamelCase		       =    bigram
											__lowerCamelCase		       =    []
											__lowerCamelCase		       =    0
											while i < len(lowerCamelCase__							):
															try:
																			__lowerCamelCase		       =    word.index(lowerCamelCase__			,						lowerCamelCase__							)
															except ValueError:
																			new_word.extend(word[i:]							)
																			break
															else:
																			new_word.extend(word[i:j]							)
																			__lowerCamelCase		       =    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		       =    tuple(lowerCamelCase__							)
											__lowerCamelCase		       =    new_word
											if len(lowerCamelCase__							) == 1:
															break
											else:
															__lowerCamelCase		       =    get_pairs(lowerCamelCase__							)
							__lowerCamelCase		       =    ' '.join(lowerCamelCase__							)
							__lowerCamelCase		       =    word
							return word


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Dict:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for token in re.findall(self.pat			,						lowerCamelCase__							):
											__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(lowerCamelCase__							).split(' '							)							)
							return bpe_tokens


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Any:



							'''simple docstring'''
							return self.encoder.get(lowerCamelCase__			,						self.encoder.get(self.unk_token							)							)


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



							'''simple docstring'''
							return self.decoder.get(lowerCamelCase__							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    ''.join(lowerCamelCase__							)
							__lowerCamelCase		       =    bytearray([self.byte_decoder[c] for c in text]							).decode('utf-8'			,						errors=self.errors							)
							return text


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      Tuple[str]:



							'''simple docstring'''
							if not os.path.isdir(lowerCamelCase__							):
											logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
											return
							__lowerCamelCase		       =    os.path.join(
							    lowerCamelCase__			,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']							)
							__lowerCamelCase		       =    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		       =    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 lowerCamelCase__							: 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(lowerCamelCase__							) + '\n'							)
															index += 1

							return vocab_file, merge_file


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = False							)    ->      List[int]:



							'''simple docstring'''
							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       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      List[int]:



							'''simple docstring'''
							__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       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__=False			,						**lowerCamelCase__							)    ->      Dict:



							'''simple docstring'''
							__lowerCamelCase		       =    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		       =    ' ' + text
							return (text, kwargs)


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      Any:



							'''simple docstring'''
							return token_ids_a + [self.eos_token_id]






			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[int]:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for is_user, text in conversation.iter_texts():
											if is_user:
															# We need to space prefix as it's being done within blenderbot
															inputs.append(' ' + text							)
											else:
															# Generated responses should contain them already.
															inputs.append(lowerCamelCase__							)

							__lowerCamelCase		       =    '  '.join(lowerCamelCase__							)
							__lowerCamelCase		       =    self.encode(lowerCamelCase__							)
							if len(lowerCamelCase__							) > self.model_max_length:
											__lowerCamelCase		       =    input_ids[-self.model_max_length :]
											logger.warning(f"""Trimmed input from conversation as it was longer than {self.model_max_length} tokens."""							)
							return input_ids








import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[Any] ,     UpperCamelCase__				:      Optional[int] ,     UpperCamelCase__				:      str ,     UpperCamelCase__				:      Any=1024      )     ->       Dict:





				"""simple docstring"""


				__lowerCamelCase       ,						__lowerCamelCase		       =    [], []

				__lowerCamelCase		       =    list(zip(UpperCamelCase__ ,     UpperCamelCase__      )      )
				__lowerCamelCase       ,						__lowerCamelCase		       =    sorted_examples[0]

				def is_too_big(UpperCamelCase__				:      List[str]      ):
								return tok(UpperCamelCase__ ,     return_tensors='pt'      ).input_ids.shape[1] > max_tokens

				for src, tgt in tqdm(sorted_examples[1:]      ):
								__lowerCamelCase		       =    new_src + ' ' + src
								__lowerCamelCase		       =    new_tgt + ' ' + tgt
								if is_too_big(UpperCamelCase__      ) or is_too_big(UpperCamelCase__      ):  # cant fit, finalize example
												finished_src.append(UpperCamelCase__      )
												finished_tgt.append(UpperCamelCase__      )
												__lowerCamelCase       ,						__lowerCamelCase		       =    src, tgt
								else:  # can fit, keep adding
												__lowerCamelCase       ,						__lowerCamelCase		       =    cand_src, cand_tgt

    # cleanup
				if new_src:
								assert new_tgt
								finished_src.append(UpperCamelCase__      )
								finished_tgt.append(UpperCamelCase__      )
				return finished_src, finished_tgt







def 			lowerCamelCase_		(       UpperCamelCase__				:      str ,     UpperCamelCase__				:      Path ,     UpperCamelCase__				:      Optional[int] ,     UpperCamelCase__				:      str      )     ->       Optional[int]:





				"""simple docstring"""


				__lowerCamelCase		       =    Path(UpperCamelCase__      )
				save_path.mkdir(exist_ok=UpperCamelCase__      )
				for split in ["train"]:
								__lowerCamelCase       ,						__lowerCamelCase		       =    data_dir / F"""{split}.source""", data_dir / F"""{split}.target"""
								__lowerCamelCase		       =    [x.rstrip() for x in Path(UpperCamelCase__      ).open().readlines()]
								__lowerCamelCase		       =    [x.rstrip() for x in Path(UpperCamelCase__      ).open().readlines()]
								__lowerCamelCase       ,						__lowerCamelCase		       =    pack_examples(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								print(F"""packed {split} split from {len(UpperCamelCase__      )} examples -> {len(UpperCamelCase__      )}."""      )
								Path(save_path / F"""{split}.source"""      ).open('w'      ).write('\n'.join(UpperCamelCase__      )      )
								Path(save_path / F"""{split}.target"""      ).open('w'      ).write('\n'.join(UpperCamelCase__      )      )
				for split in ["val", "test"]:
								__lowerCamelCase       ,						__lowerCamelCase		       =    data_dir / F"""{split}.source""", data_dir / F"""{split}.target"""
								shutil.copyfile(UpperCamelCase__ ,     save_path / F"""{split}.source"""      )
								shutil.copyfile(UpperCamelCase__ ,     save_path / F"""{split}.target"""      )







def 			lowerCamelCase_		(       )     ->       List[str]:





				"""simple docstring"""


				__lowerCamelCase		       =    argparse.ArgumentParser()
				parser.add_argument('--tok_name' ,     type=UpperCamelCase__ ,     help='like facebook/bart-large-cnn,t5-base, etc.'      )
				parser.add_argument('--max_seq_len' ,     type=UpperCamelCase__ ,     default=128      )
				parser.add_argument('--data_dir' ,     type=UpperCamelCase__      )
				parser.add_argument('--save_path' ,     type=UpperCamelCase__      )
				__lowerCamelCase		       =    parser.parse_args()
				__lowerCamelCase		       =    AutoTokenizer.from_pretrained(args.tok_name      )
				return pack_data_dir(UpperCamelCase__ ,     Path(args.data_dir      ) ,     args.max_seq_len ,     args.save_path      )


if __name__ == "__main__":
					packer_cli()


