




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       a__	( SCREAMING_SNAKE_CASE_       , unittest.TestCase				):
     a		:      Any		 =     ProphetNetTokenizer
     a		:      Any		 =     False







     def       lowerCAmelCase_    (     self			)  ->   Dict:



          '''simple docstring'''



          super().setUp()

          a     =				[
              '[UNK]',
              '[CLS]',
              '[SEP]',
              '[PAD]',
              '[MASK]',
              'want',
              '##want',
              '##ed',
              'wa',
              'un',
              'runn',
              '##ing',
              ',',
              'low',
              'lowest',
          ]
          a     =				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  ,		A			)  ->   List[str]:



          '''simple docstring'''



          a     =				'UNwant\u00E9d,running'
          a     =				'unwanted, running'
          return input_text, output_text







     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



          a     =				self.tokenizer_class(self.vocab_file			)

          a     =				tokenizer.tokenize("UNwant\u00E9d,running"			)
          self.assertListEqual(__a  ,		["un", "##want", "##ed", ",", "runn", "##ing"]			)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__a			)  ,		[9, 6, 7, 12, 10, 11]			)







     def       lowerCAmelCase_    (     self			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				BasicTokenizer()

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







     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Optional[int]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a  ,		strip_accents=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Any:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a  ,		strip_accents=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   List[str]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a  ,		strip_accents=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Optional[Any]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a  ,		strip_accents=__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   List[str]:



          '''simple docstring'''



          a     =				BasicTokenizer(do_lower_case=__a  ,		never_split=["[UNK]"]			)

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







     def       lowerCAmelCase_    (     self			)  ->   List[Any]:



          '''simple docstring'''



          a     =				['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

          a     =				{}
          for i, token in enumerate(__a			):
               a     =				i
          a     =				WordpieceTokenizer(vocab=__a  ,		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			)  ->   Tuple:



          '''simple docstring'''



          a     =				self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased"			)

          a     =				['A long paragraph for summarization.', 'Another paragraph for summarization.']
          a     =				[1037, 2146, 20423, 2005, 7680, 7849, 3989, 1012, 102]
          a     =				tokenizer(__a  ,		padding=__a  ,		return_tensors="pt"			)
          self.assertIsInstance(__a  ,		__a			)
          a     =				list(batch.input_ids.numpy()[0]			)
          self.assertListEqual(__a  ,		__a			)

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







     def       lowerCAmelCase_    (     self			)  ->   Any:



          '''simple docstring'''



          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]:



          '''simple docstring'''



          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			)  ->   int:



          '''simple docstring'''



          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[int]:



          '''simple docstring'''



          a     =				self.tokenizer_class.from_pretrained("microsoft/prophetnet-large-uncased"			)

          a     =				tokenizer.encode("sequence builders"  ,		add_special_tokens=__a			)
          a     =				tokenizer.encode("multi-sequence build"  ,		add_special_tokens=__a			)

          a     =				tokenizer.build_inputs_with_special_tokens(__a			)
          a     =				tokenizer.build_inputs_with_special_tokens(__a  ,		__a			)

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







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

import sentencepiece as spm

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


lowercase__				:      int	   = logging.get_logger(__name__)


lowercase__				:      Dict	   = "▁"

lowercase__				:      Union[str, Any]	   = {"vocab_file": "spiece.model"}

lowercase__				:      Union[str, Any]	   = {
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    }
}

lowercase__				:      Tuple	   = {
    "google/reformer-crime-and-punishment": 524_288,
}




class       a__	( UpperCamelCase__				):
     a		:      List[Any]		 =     VOCAB_FILES_NAMES
     a		:      List[Any]		 =     PRETRAINED_VOCAB_FILES_MAP
     a		:      Any		 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     a		:      Dict		 =     ["""input_ids""", """attention_mask"""]







     def __init__(     self  ,		A  ,		A="</s>"  ,		A="<unk>"  ,		A=[]  ,		A = None  ,		**A  ,		)  ->   None:



          '''simple docstring'''



          a     =				{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              eos_token=A  ,		unk_token=A  ,		additional_special_tokens=A  ,		sp_model_kwargs=self.sp_model_kwargs  ,		**A  ,		)

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







     @property
     def       lowerCAmelCase_    (     self			)  ->   Optional[Any]:



          '''simple docstring'''



          return self.sp_model.get_piece_size()







     def       lowerCAmelCase_    (     self			)  ->   Dict[str, int]:



          '''simple docstring'''



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







     def __getstate__(     self			)  ->   Optional[int]:



          '''simple docstring'''



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







     def __setstate__(     self  ,		A			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				d

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

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







     def       lowerCAmelCase_    (     self  ,		A			)  ->   List[str]:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Union[str, Any]:



          '''simple docstring'''



          return self.sp_model.piece_to_id(A			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Optional[int]:



          '''simple docstring'''



          if index < self.sp_model.get_piece_size():
               a     =				self.sp_model.IdToPiece(A			)
          return token







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Union[str, Any]:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   Tuple[str]:



          '''simple docstring'''



          if not os.path.isdir(A			):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
               return
          a     =				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     =				self.sp_model.serialized_model_proto()
                    fi.write(A			)

          return (out_vocab_file,)

