'''simple docstring'''

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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__a:			List[str]	       =       logging.get_logger(__name__)

__a:			int	       =       """▁"""

__a:			Optional[int]	       =       {"""vocab_file""": """prophetnet.tokenizer"""}

__a:			Optional[int]	       =       {
    """vocab_file""": {
        """microsoft/xprophetnet-large-wiki100-cased""": (
            """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/prophetnet.tokenizer"""
        ),
    }
}

__a:			List[str]	       =       {
    """microsoft/xprophetnet-large-wiki100-cased""": {"""do_lower_case""": False},
}

__a:			Tuple	       =       {
    """microsoft/xprophetnet-large-wiki100-cased""": 5_12,
}
def       __UpperCamelCase	(       UpperCAmelCase					):
 lowercase__    :   Dict						= collections.OrderedDict()
 with open(UpperCAmelCase		,					'''r'''		,					encoding='''utf-8'''					) as reader:
  lowercase__    :   List[Any]						= reader.readlines()
 for index, token in enumerate(UpperCAmelCase					):
  lowercase__    :   List[Any]						= token.rstrip('''\n'''					)
  lowercase__    :   Tuple						= index
 return vocab





class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE 		=   PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE 		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       SCREAMING_SNAKE_CASE 		=   ["input_ids", "attention_mask"]

       def __init__(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase="[SEP]"     ,       __lowerCAmelCase="[SEP]"     ,       __lowerCAmelCase="[SEP]"     ,       __lowerCAmelCase="[UNK]"     ,       __lowerCAmelCase="[PAD]"     ,       __lowerCAmelCase="[CLS]"     ,       __lowerCAmelCase="[MASK]"     ,       __lowerCAmelCase = None     ,       **__lowerCAmelCase     ,       )  ->  None:
        lowercase__    :   Dict						= {} if sp_model_kwargs is None else sp_model_kwargs

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

        try:
         import sentencepiece as spm
        except ImportError:
         logger.warning(
             '''You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'''
             ''' pip install sentencepiece'''			)
         raise

        lowercase__    :   str						= spm.SentencePieceProcessor(**self.sp_model_kwargs			)
        self.sp_model.Load(str(__lowerCAmelCase			)			)
        lowercase__    :   Optional[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'

        # put special tokens and [unused] tokens into the vocab
        lowercase__    :   str						= {'''[PAD]''': 0, '''[CLS]''': 1, '''[SEP]''': 2, '''[UNK]''': 3, '''[MASK]''': 4}

        for i in range(10			):
         lowercase__    :   Tuple						= F"""[unused{i}]"""
         lowercase__    :   List[Any]						= 5 + i

        # The first "real" token "," has position 15 in the embedding vocab and position 3 in the spm vocab
        lowercase__    :   Optional[Any]						= 12
        lowercase__    :   Tuple						= {v: k for k, v in self.fairseq_tokens_to_ids.items()}
        for k in self.fairseq_tokens_to_ids.keys():
         self.unique_no_split_tokens.append(__lowerCAmelCase			)

       def __getstate__(						self			)  ->  Union[str, Any]:
        lowercase__    :   Dict						= self.__dict__.copy()
        lowercase__    :   Optional[Any]						= None
        return state

       def __setstate__(						self     ,       __lowerCAmelCase			)  ->  Dict:
        lowercase__    :   Any						= d
        try:
         import sentencepiece as spm
        except ImportError:
         logger.warning(
             '''You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece'''
             ''' pip install sentencepiece'''			)
         raise

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

        lowercase__    :   int						= spm.SentencePieceProcessor(**self.sp_model_kwargs			)
        self.sp_model.Load(self.vocab_file			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None     ,       __lowerCAmelCase = False			)  ->  List[int]:

        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 ([0] * len(__lowerCAmelCase			)) + [1]
        return ([0] * len(__lowerCAmelCase			)) + [1] + ([0] * len(__lowerCAmelCase			)) + [1]

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  List[int]:
        lowercase__    :   List[str]						= [self.sep_token_id]

        if token_ids_a is None:
         return len(token_ids_a + sep			) * [0]
        return len(token_ids_a + sep + sep + token_ids_a + sep			) * [0]

       @property
       def _lowerCAmelCase(						self			)  ->  List[Any]:
        return len(self.sp_model			) + self.fairseq_offset

       def _lowerCAmelCase(						self			)  ->  List[str]:
        lowercase__    :   str						= {self.convert_ids_to_tokens(__lowerCAmelCase			): i for i in range(self.vocab_size			)}
        vocab.update(self.added_tokens_encoder			)
        return vocab

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        return self.sp_model.encode(__lowerCAmelCase     ,       out_type=__lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Optional[Any]:
        if token in self.fairseq_tokens_to_ids:
         return self.fairseq_tokens_to_ids[token]
        lowercase__    :   Tuple						= self.sp_model.PieceToId(__lowerCAmelCase			)

        # 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     ,       __lowerCAmelCase			)  ->  str:
        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     ,       __lowerCAmelCase			)  ->  Union[str, Any]:
        lowercase__    :   Optional[Any]						= ''''''.join(__lowerCAmelCase			).replace(__lowerCAmelCase     ,       ''' '''			).strip()
        return out_string

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  Tuple[str]:
        if not os.path.isdir(__lowerCAmelCase			):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
         return
        lowercase__    :   str						= os.path.join(
            __lowerCAmelCase     ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

        if os.path.abspath(self.vocab_file			) != os.path.abspath(__lowerCAmelCase			) and os.path.isfile(self.vocab_file			):
         copyfile(self.vocab_file     ,       __lowerCAmelCase			)
        elif not os.path.isfile(self.vocab_file			):
         with open(__lowerCAmelCase     ,       '''wb'''			) as fi:
          lowercase__    :   List[Any]						= self.sp_model.serialized_model_proto()
          fi.write(__lowerCAmelCase			)

        return (out_vocab_file,)


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  List[int]:

        if token_ids_a is None:
         return token_ids_a + [self.sep_token_id]
        lowercase__    :   str						= [self.sep_token_id]
        return token_ids_a + sep + token_ids_a + sep


'''simple docstring'''

import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin



class       UpperCAmelCase  (						a__   ,						unittest.TestCase ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   ProphetNetTokenizer
       SCREAMING_SNAKE_CASE 		=   False

       def _lowerCAmelCase(						self			)  ->  Any:
        super().setUp()

        lowercase__    :   Tuple						= [
            '''[UNK]''',
            '''[CLS]''',
            '''[SEP]''',
            '''[PAD]''',
            '''[MASK]''',
            '''want''',
            '''##want''',
            '''##ed''',
            '''wa''',
            '''un''',
            '''runn''',
            '''##ing''',
            ''',''',
            '''low''',
            '''lowest''',
        ]
        lowercase__    :   List[str]						= os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''vocab_file''']			)
        with open(self.vocab_file     ,       '''w'''     ,       encoding='''utf-8'''			) as vocab_writer:
         vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]			)			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        lowercase__    :   Union[str, Any]						= '''UNwant\u00E9d,running'''
        lowercase__    :   List[Any]						= '''unwanted, running'''
        return input_text, output_text

       def _lowerCAmelCase(						self			)  ->  Any:
        lowercase__    :   List[str]						= self.tokenizer_class(self.vocab_file			)

        lowercase__    :   Union[str, Any]						= tokenizer.tokenize('''UNwant\u00E9d,running'''			)
        self.assertListEqual(__lowerCAmelCase     ,       ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']			)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)     ,       [9, 6, 7, 12, 10, 11]			)

       def _lowerCAmelCase(						self			)  ->  List[str]:
        lowercase__    :   List[str]						= BasicTokenizer()

        self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz'''			)     ,       ['''ah''', '''\u535A''', '''\u63A8''', '''zz''']			)

       def _lowerCAmelCase(						self			)  ->  Tuple:
        lowercase__    :   List[Any]						= BasicTokenizer(do_lower_case=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''			)     ,       ['''hello''', '''!''', '''how''', '''are''', '''you''', '''?''']			)
        self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''			)     ,       ['''hello''']			)

       def _lowerCAmelCase(						self			)  ->  Union[str, Any]:
        lowercase__    :   Optional[int]						= BasicTokenizer(do_lower_case=__lowerCAmelCase     ,       strip_accents=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''			)     ,       ['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?''']			)
        self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''			)     ,       ['''h\u00E9llo''']			)

       def _lowerCAmelCase(						self			)  ->  Tuple:
        lowercase__    :   str						= BasicTokenizer(do_lower_case=__lowerCAmelCase     ,       strip_accents=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''			)     ,       ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']			)
        self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''			)     ,       ['''hello''']			)

       def _lowerCAmelCase(						self			)  ->  int:
        lowercase__    :   Union[str, Any]						= BasicTokenizer(do_lower_case=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''			)     ,       ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?''']			)
        self.assertListEqual(tokenizer.tokenize('''H\u00E9llo'''			)     ,       ['''hello''']			)

       def _lowerCAmelCase(						self			)  ->  List[Any]:
        lowercase__    :   int						= BasicTokenizer(do_lower_case=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  '''			)     ,       ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']			)

       def _lowerCAmelCase(						self			)  ->  List[str]:
        lowercase__    :   Tuple						= BasicTokenizer(do_lower_case=__lowerCAmelCase     ,       strip_accents=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''			)     ,       ['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']			)

       def _lowerCAmelCase(						self			)  ->  Any:
        lowercase__    :   Tuple						= BasicTokenizer(do_lower_case=__lowerCAmelCase     ,       strip_accents=__lowerCAmelCase			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  '''			)     ,       ['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''']			)

       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        lowercase__    :   Optional[int]						= BasicTokenizer(do_lower_case=__lowerCAmelCase     ,       never_split=['''[UNK]''']			)

        self.assertListEqual(
            tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]'''			)     ,       ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]''']			)

       def _lowerCAmelCase(						self			)  ->  int:
        lowercase__    :   Union[str, Any]						= ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

        lowercase__    :   Union[str, Any]						= {}
        for i, token in enumerate(__lowerCAmelCase			):
         lowercase__    :   List[Any]						= i
        lowercase__    :   Dict						= WordpieceTokenizer(vocab=__lowerCAmelCase     ,       unk_token='''[UNK]'''			)

        self.assertListEqual(tokenizer.tokenize(''''''			)     ,       []			)

        self.assertListEqual(tokenizer.tokenize('''unwanted running'''			)     ,       ['''un''', '''##want''', '''##ed''', '''runn''', '''##ing''']			)

        self.assertListEqual(tokenizer.tokenize('''unwantedX running'''			)     ,       ['''[UNK]''', '''runn''', '''##ing''']			)

       @require_torch
       def _lowerCAmelCase(						self			)  ->  Union[str, Any]:
        lowercase__    :   Union[str, Any]						= self.tokenizer_class.from_pretrained('''microsoft/prophetnet-large-uncased'''			)

        lowercase__    :   Optional[int]						= ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        lowercase__    :   Dict						= [1037, 2146, 20423, 2005, 7680, 7849, 3989, 1012, 102]
        lowercase__    :   int						= tokenizer(__lowerCAmelCase     ,       padding=__lowerCAmelCase     ,       return_tensors='''pt'''			)
        self.assertIsInstance(__lowerCAmelCase     ,       __lowerCAmelCase			)
        lowercase__    :   Optional[int]						= list(batch.input_ids.numpy()[0]			)
        self.assertListEqual(__lowerCAmelCase     ,       __lowerCAmelCase			)

        self.assertEqual((2, 9)     ,       batch.input_ids.shape			)
        self.assertEqual((2, 9)     ,       batch.attention_mask.shape			)

       def _lowerCAmelCase(						self			)  ->  str:
        self.assertTrue(_is_whitespace(''' '''			)			)
        self.assertTrue(_is_whitespace('''\t'''			)			)
        self.assertTrue(_is_whitespace('''\r'''			)			)
        self.assertTrue(_is_whitespace('''\n'''			)			)
        self.assertTrue(_is_whitespace('''\u00A0'''			)			)

        self.assertFalse(_is_whitespace('''A'''			)			)
        self.assertFalse(_is_whitespace('''-'''			)			)

       def _lowerCAmelCase(						self			)  ->  Optional[Any]:
        self.assertTrue(_is_control('''\u0005'''			)			)

        self.assertFalse(_is_control('''A'''			)			)
        self.assertFalse(_is_control(''' '''			)			)
        self.assertFalse(_is_control('''\t'''			)			)
        self.assertFalse(_is_control('''\r'''			)			)

       def _lowerCAmelCase(						self			)  ->  Dict:
        self.assertTrue(_is_punctuation('''-'''			)			)
        self.assertTrue(_is_punctuation('''$'''			)			)
        self.assertTrue(_is_punctuation('''`'''			)			)
        self.assertTrue(_is_punctuation('''.'''			)			)

        self.assertFalse(_is_punctuation('''A'''			)			)
        self.assertFalse(_is_punctuation(''' '''			)			)


       @slow
       def _lowerCAmelCase(						self			)  ->  Optional[Any]:
        lowercase__    :   List[Any]						= self.tokenizer_class.from_pretrained('''microsoft/prophetnet-large-uncased'''			)

        lowercase__    :   List[str]						= tokenizer.encode('''sequence builders'''     ,       add_special_tokens=__lowerCAmelCase			)
        lowercase__    :   Optional[int]						= tokenizer.encode('''multi-sequence build'''     ,       add_special_tokens=__lowerCAmelCase			)

        lowercase__    :   Tuple						= tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase			)
        lowercase__    :   List[str]						= tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase     ,       __lowerCAmelCase			)

        assert encoded_sentence == text + [102]
        assert encoded_pair == text + [102] + text_a + [102]

