
"""simple docstring"""

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


UpperCamelCase     :    Union[str, Any]       =			logging.get_logger(__name__)

UpperCamelCase     :    List[str]       =			{"vocab_file": "sentencepiece.bpe.model"}

UpperCamelCase     :    Any       =			{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

UpperCamelCase     :    Optional[Any]       =			{
    "camembert-base": 5_1_2,
}

UpperCamelCase     :    List[str]       =			"▁"

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						VOCAB_FILES_NAMES
     lowercase						       =						PRETRAINED_VOCAB_FILES_MAP
     lowercase						       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase						       =						["input_ids", "attention_mask"]





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase="<s>"     ,					__UpperCAmelCase="</s>"     ,					__UpperCAmelCase="</s>"     ,					__UpperCAmelCase="<s>"     ,					__UpperCAmelCase="<unk>"     ,					__UpperCAmelCase="<pad>"     ,					__UpperCAmelCase="<mask>"     ,					__UpperCAmelCase=["<s>NOTUSED", "</s>NOTUSED"]     ,					__UpperCAmelCase = None     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	AddedToken(__UpperCAmelCase     ,					lstrip=__UpperCAmelCase     ,					rstrip=__UpperCAmelCase				) if isinstance(__UpperCAmelCase     ,					__UpperCAmelCase				) else mask_token

      __UpperCamelCase      =	{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__UpperCAmelCase     ,					eos_token=__UpperCAmelCase     ,					unk_token=__UpperCAmelCase     ,					sep_token=__UpperCAmelCase     ,					cls_token=__UpperCAmelCase     ,					pad_token=__UpperCAmelCase     ,					mask_token=__UpperCAmelCase     ,					additional_special_tokens=__UpperCAmelCase     ,					sp_model_kwargs=self.sp_model_kwargs     ,					**__UpperCAmelCase     ,					)
      __UpperCamelCase      =	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.Load(str(__UpperCAmelCase				)				)
      __UpperCamelCase      =	vocab_file
      # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
      # sentencepiece vocabulary (this is the case for <s> and </s>
      __UpperCamelCase      =	{'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
      __UpperCamelCase      =	len(self.fairseq_tokens_to_ids				)
      __UpperCamelCase      =	len(self.sp_model				) + len(self.fairseq_tokens_to_ids				)
      __UpperCamelCase      =	{v: k for k, v in self.fairseq_tokens_to_ids.items()}





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      __UpperCamelCase      =	[self.cls_token_id]
      __UpperCamelCase      =	[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=__UpperCAmelCase     ,					token_ids_a=__UpperCAmelCase     ,					already_has_special_tokens=__UpperCAmelCase				)

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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      __UpperCamelCase      =	[self.sep_token_id]
      __UpperCamelCase      =	[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]





     @property
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      return len(self.fairseq_tokens_to_ids				) + len(self.sp_model				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	{self.convert_ids_to_tokens(__UpperCAmelCase				): i for i in range(self.vocab_size				)}
      vocab.update(self.added_tokens_encoder				)
      return vocab





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return self.sp_model.encode(__UpperCAmelCase     ,					out_type=__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      if token in self.fairseq_tokens_to_ids:
       return self.fairseq_tokens_to_ids[token]
      elif self.sp_model.PieceToId(__UpperCAmelCase				) == 0:
       # Convert sentence piece unk token to fairseq unk token index
       return self.unk_token_id
      return self.fairseq_offset + self.sp_model.PieceToId(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      if index in self.fairseq_ids_to_tokens:
       return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(index - self.fairseq_offset				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	[]
      __UpperCamelCase      =	''
      __UpperCamelCase      =	False
      for token in tokens:
       # make sure that special tokens are not decoded using sentencepiece model
       if token in self.all_special_tokens:
        if not prev_is_special:
         out_string += " "
        out_string += self.sp_model.decode(__UpperCAmelCase				) + token
        __UpperCamelCase      =	True
        __UpperCamelCase      =	[]
       else:
        current_sub_tokens.append(__UpperCAmelCase				)
        __UpperCamelCase      =	False
      out_string += self.sp_model.decode(__UpperCAmelCase				)
      return out_string.strip()





     def __getstate__(     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.__dict__.copy()
      __UpperCamelCase      =	None
      return state





     def __setstate__(     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	d

      # for backward compatibility
      if not hasattr(self     ,					'sp_model_kwargs'				):
       __UpperCamelCase      =	{}

      __UpperCamelCase      =	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.Load(self.vocab_file				)







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




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

      if os.path.abspath(self.vocab_file				) != os.path.abspath(__UpperCAmelCase				) and os.path.isfile(self.vocab_file				):
       copyfile(self.vocab_file     ,					__UpperCAmelCase				)
      elif not os.path.isfile(self.vocab_file				):
       with open(__UpperCAmelCase     ,					'wb'				) as fi:
        __UpperCamelCase      =	self.sp_model.serialized_model_proto()
        fi.write(__UpperCAmelCase				)

      return (out_vocab_file,)





"""simple docstring"""

from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters






def 							A						(    )				->     Any:
 __UpperCamelCase      =	{
     'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
     'path': ['test_1.py', 'test_2.py', 'unit_test.py'],
     'content': ['a ' * 2_0, 'a ' * 3_0, 'b ' * 7],
 }
 __UpperCamelCase      =	Dataset.from_dict(snake_case		)
 return dataset





class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	get_dataset()
      __UpperCamelCase      =	make_duplicate_clusters(__UpperCAmelCase     ,					0.8_5				)
      self.assertEqual(len(duplicate_clusters[0]				)     ,					2				)







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	get_dataset()
      __UpperCamelCase  ,     __UpperCamelCase      =	deduplicate_dataset(__UpperCAmelCase				)
      self.assertEqual(len(__UpperCAmelCase				)     ,					2				)
      print(__UpperCAmelCase				)
      self.assertEqual(duplicate_clusters[0][0]['copies']     ,					2				)
      self.assertEqual(duplicate_clusters[0][0]['is_extreme']     ,					__UpperCAmelCase				)



