



"""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


lowercase__			   =  logging.get_logger(__name__)

lowercase__			   =  "▁"

lowercase__			   =  {"vocab_file": "sentencepiece.bpe.model"}

lowercase__			   =  {
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    }
}

lowercase__			   =  {
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}




class SCREAMING_SNAKE_CASE__					(		_UpperCAmelCase      ):
						_lowerCAmelCase							=					VOCAB_FILES_NAMES
						_lowerCAmelCase							=					PRETRAINED_VOCAB_FILES_MAP
						_lowerCAmelCase							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCAmelCase							=					['''input_ids''', '''attention_mask''']



						def __init__(self						,     _lowercase						,     _lowercase="<s>"						,     _lowercase="</s>"						,     _lowercase="</s>"						,     _lowercase="<s>"						,     _lowercase="<unk>"						,     _lowercase="<pad>"						,     _lowercase="<mask>"						,     _lowercase = None						,     **_lowercase						,     ):





													'''simple docstring'''

													__a		:		Dict									=       AddedToken(A_						,     lstrip=A_						,     rstrip=A_							) if isinstance(A_						,     A_							) else mask_token

													__a		:		Optional[int]									=       {} if sp_model_kwargs is None else sp_model_kwargs

													super().__init__(
													    bos_token=A_						,     eos_token=A_						,     unk_token=A_						,     sep_token=A_						,     cls_token=A_						,     pad_token=A_						,     mask_token=A_						,     sp_model_kwargs=self.sp_model_kwargs						,     **A_						,     )

													__a		:		int									=       spm.SentencePieceProcessor(**self.sp_model_kwargs							)
													self.sp_model.Load(str(A_							)							)
													__a		:		int									=       vocab_file

													# Original fairseq vocab and spm vocab must be "aligned":
													# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
													# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
													# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
													# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

													# Mimic fairseq token-to-id alignment for the first 4 token
													__a		:		str									=       {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

													# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
													__a		:		Dict									=       1

													__a		:		List[str]									=       len(self.sp_model							) + self.fairseq_offset
													__a		:		int									=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}



						def __getstate__(self							):





													'''simple docstring'''

													__a		:		int									=       self.__dict__.copy()
													__a		:		Tuple									=       None
													__a		:		Optional[int]									=       self.sp_model.serialized_model_proto()
													return state



						def __setstate__(self						,     _lowercase							):





													'''simple docstring'''

													__a		:		Optional[Any]									=       d

													# for backward compatibility
													if not hasattr(self						,     """sp_model_kwargs"""							):
																				__a		:		List[str]									=       {}

													__a		:		Any									=       spm.SentencePieceProcessor(**self.sp_model_kwargs							)
													self.sp_model.LoadFromSerializedProto(self.sp_model_proto							)



						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None							):





													'''simple docstring'''

													if token_ids_a is None:
																				return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
													__a		:		List[str]									=       [self.cls_token_id]
													__a		:		Any									=       [self.sep_token_id]
													return cls + token_ids_a + sep + sep + token_ids_a + sep



						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None						,     _lowercase = False							):





													'''simple docstring'''

													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     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None							):





													'''simple docstring'''

													__a		:		List[str]									=       [self.sep_token_id]
													__a		:		str									=       [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     lowerCAmelCase__(self							):





													'''simple docstring'''

													return len(self.sp_model							) + self.fairseq_offset + 1  # Add the <mask> token



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		str									=       {self.convert_ids_to_tokens(A_							): i for i in range(self.vocab_size							)}
													vocab.update(self.added_tokens_encoder							)
													return vocab



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

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



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													if token in self.fairseq_tokens_to_ids:
																				return self.fairseq_tokens_to_ids[token]
													__a		:		Union[str, Any]									=       self.sp_model.PieceToId(A_							)

													# Need to return unknown token if the SP model returned 0
													return spm_id + self.fairseq_offset if spm_id else self.unk_token_id



						def     lowerCAmelCase__(self						,     _lowercase							):





													'''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     lowerCAmelCase__(self						,     _lowercase							):





													'''simple docstring'''

													__a		:		str									=       """""".join(A_							).replace(A_						,     """ """							).strip()
													return out_string





						def     lowerCAmelCase__(self						,     _lowercase						,     _lowercase = None							):





													'''simple docstring'''

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

													if os.path.abspath(self.vocab_file							) != os.path.abspath(A_							) and os.path.isfile(self.vocab_file							):
																				copyfile(self.vocab_file						,     A_							)
													elif not os.path.isfile(self.vocab_file							):
																				with open(A_						,     """wb"""							) as fi:
																											__a		:		int									=       self.sp_model.serialized_model_proto()
																											fi.write(A_							)

													return (out_vocab_file,)






"""simple docstring"""

from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters





def       __magic_name__    (   ):
							__a		:		Dict									=       {
							    """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],
							}
							__a		:		Optional[Any]									=       Dataset.from_dict(_lowerCamelCase					)
							return dataset







class SCREAMING_SNAKE_CASE__					(		__snake_case      ):



						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Optional[int]									=       get_dataset()
													__a		:		List[Any]									=       make_duplicate_clusters(_lowercase						,     0.85							)
													self.assertEqual(len(duplicate_clusters[0]							)						,     2							)





						def     lowerCAmelCase__(self							):





													'''simple docstring'''

													__a		:		Tuple									=       get_dataset()
													__a							,     __a		:		Optional[Any]									=       deduplicate_dataset(_lowercase							)
													self.assertEqual(len(_lowercase							)						,     2							)
													print(_lowercase							)
													self.assertEqual(duplicate_clusters[0][0]["""copies"""]						,     2							)
													self.assertEqual(duplicate_clusters[0][0]["""is_extreme"""]						,     _lowercase							)

