


'''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


_lowerCAmelCase  :		List[Any]		     =	logging.get_logger(__name__)

_lowerCAmelCase  :		List[Any]		     =	{'vocab_file': 'sentencepiece.bpe.model'}

_lowerCAmelCase  :		Dict		     =	{
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

_lowerCAmelCase  :		Dict		     =	{
    'moussaKam/mbarthez': 1024,
    'moussaKam/barthez': 1024,
    'moussaKam/barthez-orangesum-title': 1024,
}

_lowerCAmelCase  :		Optional[Any]		     =	'▁'



class  lowerCAmelCase				(				__snake_case							):
 _lowerCamelCase   :					Any			      = VOCAB_FILES_NAMES
 _lowerCamelCase   :					Tuple			      = PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase   :					str			      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase   :					Any			      = ["""input_ids""", """attention_mask"""]



 def __init__(					self ,					snake_case__ ,					snake_case__="<s>" ,					snake_case__="</s>" ,					snake_case__="</s>" ,					snake_case__="<s>" ,					snake_case__="<unk>" ,					snake_case__="<pad>" ,					snake_case__="<mask>" ,					snake_case__ = None ,					**snake_case__ ,					):
  lowerCAmelCase					:    Dict      							= AddedToken(__UpperCamelCase ,					lstrip=__UpperCamelCase ,					rstrip=__UpperCamelCase    ) if isinstance(__UpperCamelCase ,					__UpperCamelCase    ) else mask_token

  lowerCAmelCase					:    Union[str, Any]      							= {} 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 ,					sp_model_kwargs=self.sp_model_kwargs ,					**__UpperCamelCase ,					)

  lowerCAmelCase					:    List[Any]      							= vocab_file
  lowerCAmelCase					:    Tuple      							= spm.SentencePieceProcessor(**self.sp_model_kwargs    )
  self.sp_model.Load(str(__UpperCamelCase    )    )

  lowerCAmelCase					:    int      							= {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

  lowerCAmelCase					:    Dict      							= len(self.sp_model    ) - 1
  lowerCAmelCase					:    Tuple      							= {v: k for k, v in self.fairseq_tokens_to_ids.items()}



 def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):


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



 def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None ,					snake_case__ = False    ):


  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 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):
  lowerCAmelCase					:    Dict      							= [self.sep_token_id]
  lowerCAmelCase					:    Optional[int]      							= [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 				lowercase     (					self    ):
  return len(self.sp_model    )



 def 				lowercase     (					self    ):
  lowerCAmelCase					:    Optional[Any]      							= {self.convert_ids_to_tokens(__UpperCamelCase    ): i for i in range(self.vocab_size    )}
  vocab.update(self.added_tokens_encoder    )
  return vocab



 def 				lowercase     (					self ,					snake_case__    ):
  return self.sp_model.encode(__UpperCamelCase ,					out_type=__UpperCamelCase    )



 def 				lowercase     (					self ,					snake_case__    ):


  if token in self.fairseq_tokens_to_ids:
   return self.fairseq_tokens_to_ids[token]
  lowerCAmelCase					:    str      							= self.sp_model.PieceToId(__UpperCamelCase    )

  return spm_id if spm_id else self.unk_token_id



 def 				lowercase     (					self ,					snake_case__    ):


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



 def 				lowercase     (					self ,					snake_case__    ):
  lowerCAmelCase					:    int      							= []
  lowerCAmelCase					:    Union[str, Any]      							= ''
  lowerCAmelCase					:    Union[str, Any]      							= 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
    lowerCAmelCase					:    Union[str, Any]      							= True
    lowerCAmelCase					:    List[Any]      							= []
   else:
    current_sub_tokens.append(__UpperCamelCase    )
    lowerCAmelCase					:    int      							= False
  out_string += self.sp_model.decode(__UpperCamelCase    )
  return out_string.strip()



 def __getstate__(					self    ):
  lowerCAmelCase					:    int      							= self.__dict__.copy()
  lowerCAmelCase					:    List[str]      							= None
  return state



 def __setstate__(					self ,					snake_case__    ):
  lowerCAmelCase					:    int      							= d

  # for backward compatibility
  if not hasattr(self ,					'sp_model_kwargs'    ):
   lowerCAmelCase					:    List[Any]      							= {}

  lowerCAmelCase					:    Dict      							= spm.SentencePieceProcessor(**self.sp_model_kwargs    )
  self.sp_model.Load(self.vocab_file    )



 def 				lowercase     (					self ,					snake_case__ ,					snake_case__ = None    ):


  if not os.path.isdir(__UpperCamelCase    ):
   logger.error(f"Vocabulary path ({save_directory}) should be a directory"    )
   return
  lowerCAmelCase					:    Any      							= 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:
    lowerCAmelCase					:    Union[str, Any]      							= self.sp_model.serialized_model_proto()
    fi.write(__UpperCamelCase    )

  return (out_vocab_file,)




'''simple docstring'''




import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase  :		Union[str, Any]		     =	get_tests_dir('fixtures/test_sentencepiece_no_bos.model')



@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase				(				a      ,				unittest.TestCase							):
	_lowerCamelCase   :					str			      = PegasusTokenizer
	_lowerCamelCase   :					Union[str, Any]			      = PegasusTokenizerFast
	_lowerCamelCase   :					Optional[Any]			      = True
	_lowerCamelCase   :					Optional[Any]			      = True



	def 				lowercase     (					self    ):
		super().setUp()

		# We have a SentencePiece fixture for testing
		lowerCAmelCase					:    List[Any]      							= PegasusTokenizer(snake_case__    )
		tokenizer.save_pretrained(self.tmpdirname    )



	@cached_property
	def 				lowercase     (					self    ):
		return PegasusTokenizer.from_pretrained('google/pegasus-large'    )



	def 				lowercase     (					self ,					**snake_case__    ):
		return PegasusTokenizer.from_pretrained(self.tmpdirname ,					**snake_case__    )



	def 				lowercase     (					self ,					snake_case__    ):
		return ("This is a test", "This is a test")



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Optional[int]      							= '</s>'
		lowerCAmelCase					:    int      							= 1

		self.assertEqual(self.get_tokenizer()._convert_token_to_id(snake_case__    ) ,					snake_case__    )
		self.assertEqual(self.get_tokenizer()._convert_id_to_token(snake_case__    ) ,					snake_case__    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Union[str, Any]      							= list(self.get_tokenizer().get_vocab().keys()    )

		self.assertEqual(vocab_keys[0] ,					'<pad>'    )
		self.assertEqual(vocab_keys[1] ,					'</s>'    )
		self.assertEqual(vocab_keys[-1] ,					'v'    )
		self.assertEqual(len(snake_case__    ) ,					1103    )



	def 				lowercase     (					self    ):
		self.assertEqual(self.get_tokenizer().vocab_size ,					1103    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    List[Any]      							= self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
		lowerCAmelCase					:    List[Any]      							= self.tokenizer_class.from_pretrained(self.tmpdirname    )
		lowerCAmelCase					:    Optional[Any]      							= (
		    'Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'
		    ' </s> <pad> <pad> <pad>'
		)
		lowerCAmelCase					:    Optional[Any]      							= rust_tokenizer([raw_input_str] ,					return_tensors=snake_case__ ,					add_special_tokens=snake_case__    ).input_ids[0]
		lowerCAmelCase					:    Optional[int]      							= py_tokenizer([raw_input_str] ,					return_tensors=snake_case__ ,					add_special_tokens=snake_case__    ).input_ids[0]
		self.assertListEqual(snake_case__ ,					snake_case__    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Any      							= self._large_tokenizer
		# <mask_1> masks whole sentence while <mask_2> masks single word
		lowerCAmelCase					:    List[str]      							= '<mask_1> To ensure a <mask_2> flow of bank resolutions.'
		lowerCAmelCase					:    Optional[Any]      							= [2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
		lowerCAmelCase					:    Optional[Any]      							= tokenizer([raw_input_str] ,					return_tensors=snake_case__    ).input_ids[0]
		self.assertListEqual(snake_case__ ,					snake_case__    )



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Optional[Any]      							= self._large_tokenizer
		# The tracebacks for the following asserts are **better** without messages or self.assertEqual
		assert tokenizer.vocab_size == 9_6103
		assert tokenizer.pad_token_id == 0
		assert tokenizer.eos_token_id == 1
		assert tokenizer.offset == 103
		assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
		assert tokenizer.unk_token == "<unk>"
		assert tokenizer.model_max_length == 1024
		lowerCAmelCase					:    List[Any]      							= 'To ensure a smooth flow of bank resolutions.'
		lowerCAmelCase					:    Optional[int]      							= [413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
		lowerCAmelCase					:    Any      							= tokenizer([raw_input_str] ,					return_tensors=snake_case__    ).input_ids[0]
		self.assertListEqual(snake_case__ ,					snake_case__    )
		assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]    ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]



	@require_torch
	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Union[str, Any]      							= ['This is going to be way too long.' * 150, 'short example']
		lowerCAmelCase					:    int      							= ['not super long but more than 5 tokens', 'tiny']
		lowerCAmelCase					:    Dict      							= self._large_tokenizer(snake_case__ ,					padding=snake_case__ ,					truncation=snake_case__ ,					return_tensors='pt'    )
		lowerCAmelCase					:    Dict      							= self._large_tokenizer(
		    text_target=snake_case__ ,					max_length=5 ,					padding=snake_case__ ,					truncation=snake_case__ ,					return_tensors='pt'    )

		assert batch.input_ids.shape == (2, 1024)
		assert batch.attention_mask.shape == (2, 1024)
		assert targets["input_ids"].shape == (2, 5)
		assert len(snake_case__    ) == 2  # input_ids, attention_mask.



	@slow
	def 				lowercase     (					self    ):
		# fmt: off
		lowerCAmelCase					:    Tuple      							= {'input_ids': [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
		# fmt: on

		self.tokenizer_integration_test_util(
		    expected_encoding=snake_case__ ,					model_name='google/bigbird-pegasus-large-arxiv' ,					revision='ba85d0851d708441f91440d509690f1ab6353415' ,					)



@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase				(				a      ,				unittest.TestCase							):
	_lowerCamelCase   :					Optional[Any]			      = PegasusTokenizer
	_lowerCamelCase   :					str			      = PegasusTokenizerFast
	_lowerCamelCase   :					Tuple			      = True
	_lowerCamelCase   :					int			      = True



	def 				lowercase     (					self    ):
		super().setUp()

		# We have a SentencePiece fixture for testing
		lowerCAmelCase					:    int      							= PegasusTokenizer(snake_case__ ,					offset=0 ,					mask_token_sent=snake_case__ ,					mask_token='[MASK]'    )
		tokenizer.save_pretrained(self.tmpdirname    )



	@cached_property
	def 				lowercase     (					self    ):
		return PegasusTokenizer.from_pretrained('google/bigbird-pegasus-large-arxiv'    )



	def 				lowercase     (					self ,					**snake_case__    ):
		return PegasusTokenizer.from_pretrained(self.tmpdirname ,					**snake_case__    )



	def 				lowercase     (					self ,					snake_case__    ):
		return ("This is a test", "This is a test")



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Tuple      							= self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
		lowerCAmelCase					:    Union[str, Any]      							= self.tokenizer_class.from_pretrained(self.tmpdirname    )
		lowerCAmelCase					:    List[str]      							= (
		    'Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'
		    ' <pad> <pad> <pad>'
		)
		lowerCAmelCase					:    Dict      							= rust_tokenizer([raw_input_str] ,					return_tensors=snake_case__ ,					add_special_tokens=snake_case__    ).input_ids[0]
		lowerCAmelCase					:    Union[str, Any]      							= py_tokenizer([raw_input_str] ,					return_tensors=snake_case__ ,					add_special_tokens=snake_case__    ).input_ids[0]
		self.assertListEqual(snake_case__ ,					snake_case__    )



	@require_torch
	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Optional[int]      							= ['This is going to be way too long.' * 1000, 'short example']
		lowerCAmelCase					:    Union[str, Any]      							= ['not super long but more than 5 tokens', 'tiny']
		lowerCAmelCase					:    List[str]      							= self._large_tokenizer(snake_case__ ,					padding=snake_case__ ,					truncation=snake_case__ ,					return_tensors='pt'    )
		lowerCAmelCase					:    List[str]      							= self._large_tokenizer(
		    text_target=snake_case__ ,					max_length=5 ,					padding=snake_case__ ,					truncation=snake_case__ ,					return_tensors='pt'    )

		assert batch.input_ids.shape == (2, 4096)
		assert batch.attention_mask.shape == (2, 4096)
		assert targets["input_ids"].shape == (2, 5)
		assert len(snake_case__    ) == 2  # input_ids, attention_mask.



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    List[str]      							= (
		    'This is an example string that is used to test the original TF implementation against the HF'
		    ' implementation'
		)

		lowerCAmelCase					:    Tuple      							= self._large_tokenizer(snake_case__    ).input_ids

		self.assertListEqual(
		    snake_case__ ,					[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1] ,					)
