
'''simple docstring'''


import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__lowercase							:   List[Any]					=     get_tests_dir('''fixtures/spiece.model''')

@require_sentencepiece
@require_tokenizers
class 	__lowercase				(  _lowercase      ,     unittest.TestCase    ):
			lowerCamelCase			:		Tuple	      =			AlbertTokenizer
			lowerCamelCase			:		Union[str, Any]	      =			AlbertTokenizerFast
			lowerCamelCase			:		List[str]	      =			True
			lowerCamelCase			:		Dict	      =			True
			lowerCamelCase			:		List[Any]	      =			True

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

								# We have a SentencePiece fixture for testing
								lowerCamelCase_					:      Optional[int]     =		AlbertTokenizer(A      )
								tokenizer.save_pretrained(self.tmpdirname      )

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Union[str, Any]     =		'''this is a test'''
								lowerCamelCase_					:      Tuple     =		'''this is a test'''
								return input_text, output_text

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      str     =		'''<pad>'''
								lowerCamelCase_					:      List[str]     =		0

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

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Tuple     =		list(self.get_tokenizer().get_vocab().keys()      )

								self.assertEqual(vocab_keys[0]			,   '''<pad>'''      )
								self.assertEqual(vocab_keys[1]			,   '''<unk>'''      )
								self.assertEqual(vocab_keys[-1]			,   '''▁eloquent'''      )
								self.assertEqual(len(A      )			,   3_0_0_0_0      )

			def        UpperCAmelCase__ (self      ):
								self.assertEqual(self.get_tokenizer().vocab_size			,   3_0_0_0_0      )

			def        UpperCAmelCase__ (self      ):
								if not self.test_rust_tokenizer:
													return

								lowerCamelCase_					:      int     =		self.get_tokenizer()
								lowerCamelCase_					:      str     =		self.get_rust_tokenizer()

								lowerCamelCase_					:      Optional[int]     =		'''I was born in 92000, and this is falsé.'''

								lowerCamelCase_					:      Dict     =		tokenizer.tokenize(A      )
								lowerCamelCase_					:      Tuple     =		rust_tokenizer.tokenize(A      )
								self.assertListEqual(A			,   A      )

								lowerCamelCase_					:      List[str]     =		tokenizer.encode(A			,   add_special_tokens=A      )
								lowerCamelCase_					:      List[Any]     =		rust_tokenizer.encode(A			,   add_special_tokens=A      )
								self.assertListEqual(A			,   A      )

								lowerCamelCase_					:      List[Any]     =		self.get_rust_tokenizer()
								lowerCamelCase_					:      Tuple     =		tokenizer.encode(A      )
								lowerCamelCase_					:      str     =		rust_tokenizer.encode(A      )
								self.assertListEqual(A			,   A      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Union[str, Any]     =		AlbertTokenizer(A			,   keep_accents=A      )

								lowerCamelCase_					:      Tuple     =		tokenizer.tokenize('''This is a test'''      )
								self.assertListEqual(A			,   ['''▁this''', '''▁is''', '''▁a''', '''▁test''']      )

								self.assertListEqual(tokenizer.convert_tokens_to_ids(A      )			,   [4_8, 2_5, 2_1, 1_2_8_9]      )

								lowerCamelCase_					:      Any     =		tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
								self.assertListEqual(
								    A			,   ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''']      )
								lowerCamelCase_					:      Union[str, Any]     =		tokenizer.convert_tokens_to_ids(A      )
								self.assertListEqual(A			,   [3_1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]      )

								lowerCamelCase_					:      Optional[int]     =		tokenizer.convert_ids_to_tokens(A      )
								self.assertListEqual(
								    A			,   ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''']			,   )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      Optional[int]     =		AlbertTokenizer(A      )

								lowerCamelCase_					:      Dict     =		tokenizer.encode('''sequence builders'''      )
								lowerCamelCase_					:      Optional[Any]     =		tokenizer.encode('''multi-sequence build'''      )

								lowerCamelCase_					:      Union[str, Any]     =		tokenizer.build_inputs_with_special_tokens(A      )
								lowerCamelCase_					:      str     =		tokenizer.build_inputs_with_special_tokens(A			,   A      )

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]






			@slow
			def        UpperCAmelCase__ (self      ):
								# fmt: off
								lowerCamelCase_					:      Optional[int]     =		{'''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, 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, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''input_ids''': [[2, 2_1_9_7_0, 1_3, 5, 6_0_9_2, 1_6_7, 2_8, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 7_0_2_8, 1_2_0_5_1, 1_8, 1_7, 7_1_0_3, 2_1_5_3, 6_7_3, 8, 3_5_1_5, 1_8_6_8_4, 8, 4_4_6_1, 6, 1_9_2_7, 2_9_7, 8, 1_2_0_6_0, 2_6_0_7, 1_8, 1_3, 5, 4_4_6_1, 1_5, 1_0_5_3_8, 3_8, 8, 1_3_5, 1_5, 8_2_2, 5_8, 1_5, 9_9_3, 1_0_3_6_3, 1_5, 1_4_6_0, 8_0_0_5, 4_4_6_1, 1_5, 9_9_3, 2_5_5, 2_3_2_8, 9, 9, 9, 6, 2_6, 1_1_1_2, 8_1_6, 3_2_6_0, 1_3, 5, 1_0_3, 2_3_7_7, 6, 1_7, 1_1_1_2, 8_1_6, 2_7_8_2, 1_3, 5, 1_0_3, 1_0_6_4_1, 6, 2_9, 8_4, 2_5_1_2, 2_4_3_0, 7_8_2, 1_8_6_8_4, 2_7_6_1, 1_9, 8_0_8, 2_4_3_0, 2_5_5_6, 1_7, 8_5_5, 1_4_8_0, 9_4_7_7, 4_0_9_1, 1_2_8, 1_1_7_1_2, 1_5, 7_1_0_3, 2_1_5_3, 6_7_3, 1_7, 2_4_8_8_3, 9_9_9_0, 9, 3], [2, 1_1_5_0_2, 2_5, 1_0_0_6, 2_0, 7_8_2, 8, 1_1_8_0_9, 8_5_5, 1_7_3_2, 1_9_3_9_3, 1_8_6_6_7, 3_7, 3_6_7, 2_1_0_1_8, 6_9, 1_8_5_4, 3_4, 1_1_8_6_0, 1_9_1_2_4, 2_7, 1_5_6, 2_2_5, 1_7, 1_9_3, 4_1_4_1, 1_9, 6_5, 9_1_2_4, 9, 3, 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], [2, 1_4, 2_2_3_1, 8_8_6, 2_3_8_5, 1_7_6_5_9, 8_4, 1_4, 1_6_7_9_2, 1_9_5_2, 9, 3, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[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, 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, 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, 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, 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=A			,   model_name='''albert-base-v2'''			,   revision='''6b6560eaf5ff2e250b00c50f380c5389a9c2d82e'''			,   )




'''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							:   Any					=     logging.get_logger(__name__)

__lowercase							:   List[str]					=     '''▁'''

__lowercase							:   Optional[Any]					=     {'''vocab_file''': '''sentencepiece.bpe.model'''}

__lowercase							:   List[str]					=     {
    '''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							:   Union[str, Any]					=     {
    '''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 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		Any	      =			VOCAB_FILES_NAMES
			lowerCamelCase			:		Optional[int]	      =			PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase			:		str	      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase			:		Union[str, Any]	      =			["input_ids", "attention_mask"]

			def __init__(self			,   A			,   A="<s>"			,   A="</s>"			,   A="</s>"			,   A="<s>"			,   A="<unk>"			,   A="<pad>"			,   A="<mask>"			,   A = None			,   **A			,   ):
								# Mask token behave like a normal word, i.e. include the space before it
								lowerCamelCase_					:      Tuple     =		AddedToken(A			,   lstrip=A			,   rstrip=A      ) if isinstance(A			,   A      ) else mask_token

								lowerCamelCase_					:      Dict     =		{} 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			,   )

								lowerCamelCase_					:      Any     =		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.Load(str(A      )      )
								lowerCamelCase_					:      Tuple     =		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
								lowerCamelCase_					:      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
								lowerCamelCase_					:      int     =		1

								lowerCamelCase_					:      Union[str, Any]     =		len(self.sp_model      ) + self.fairseq_offset
								lowerCamelCase_					:      Any     =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}

			def __getstate__(self      ):
								lowerCamelCase_					:      Any     =		self.__dict__.copy()
								lowerCamelCase_					:      Optional[Any]     =		None
								lowerCamelCase_					:      int     =		self.sp_model.serialized_model_proto()
								return state

			def __setstate__(self			,   A      ):
								lowerCamelCase_					:      Any     =		d

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

								lowerCamelCase_					:      List[Any]     =		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):

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

			def        UpperCAmelCase__ (self			,   A			,   A = None			,   A = False      ):

								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        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      List[str]     =		[self.sep_token_id]
								lowerCamelCase_					:      List[Any]     =		[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      ):
								return len(self.sp_model      ) + self.fairseq_offset + 1  # Add the <mask> token

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      str     =		{self.convert_ids_to_tokens(A      ): i for i in range(self.vocab_size      )}
								vocab.update(self.added_tokens_encoder      )
								return vocab

			def        UpperCAmelCase__ (self			,   A      ):
								return self.sp_model.encode(A			,   out_type=A      )

			def        UpperCAmelCase__ (self			,   A      ):
								if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
								lowerCamelCase_					:      int     =		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        UpperCAmelCase__ (self			,   A      ):
								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			,   A      ):
								lowerCamelCase_					:      Optional[int]     =		''''''.join(A      ).replace(A			,   ''' '''      ).strip()
								return out_string






			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								if not os.path.isdir(A      ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
													return
								lowerCamelCase_					:      str     =		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:
																		lowerCamelCase_					:      Optional[Any]     =		self.sp_model.serialized_model_proto()
																		fi.write(A      )

								return (out_vocab_file,)


