import os
import re
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_ : Any						  =      {"vocab_file": "spiece.model"}

lowerCAmelCase_ : Any						  =      {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

lowerCAmelCase_ : Dict						  =      {
    "google/bigbird-roberta-base": 4_096,
    "google/bigbird-roberta-large": 4_096,
    "google/bigbird-base-trivia-itc": 4_096,
}





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					=VOCAB_FILES_NAMES
   lowerCamelCase_    					=PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_    					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_    					=['input_ids', 'attention_mask']
   lowerCamelCase_    					=[]


   def __init__(   self				:	List[Any]   ,		__lowerCAmelCase				:	Dict   ,		__lowerCAmelCase				:	Dict="<unk>"   ,		__lowerCAmelCase				:	List[str]="<s>"   ,		__lowerCAmelCase				:	str="</s>"   ,		__lowerCAmelCase				:	Optional[Any]="<pad>"   ,		__lowerCAmelCase				:	List[str]="[SEP]"   ,		__lowerCAmelCase				:	Union[str, Any]="[MASK]"   ,		__lowerCAmelCase				:	Tuple="[CLS]"   ,		__lowerCAmelCase				:	Optional[Dict[str, Any]] = None   ,		**__lowerCAmelCase				:	Optional[Any]   ,		)      ->					None:
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else bos_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else eos_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else unk_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else pad_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else cls_token
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else sep_token

         # Mask token behave like a normal word, i.e. include the space before it
         lowercase_     =      AddedToken(__lowerCAmelCase   ,		lstrip=__lowerCAmelCase   ,		rstrip=__lowerCAmelCase) if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase) else mask_token

         lowercase_     =      {} if sp_model_kwargs is None else sp_model_kwargs

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

         lowercase_     =      vocab_file

         lowercase_     =      spm.SentencePieceProcessor(**self.sp_model_kwargs)
         self.sp_model.Load(__lowerCAmelCase)


   @property
   def __UpperCAmelCase       (   self				:	List[Any])      ->					Tuple:
         return self.sp_model.get_piece_size()


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


   def __getstate__(   self				:	Dict)      ->					int:
         lowercase_     =      self.__dict__.copy()
         lowercase_     =      None
         return state


   def __setstate__(   self				:	str   ,		__lowerCAmelCase				:	List[Any])      ->					str:
         lowercase_     =      d

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

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


   def __UpperCAmelCase       (   self				:	Optional[Any]   ,		__lowerCAmelCase				:	str)      ->					List[str]:
         return self.sp_model.encode(__lowerCAmelCase   ,		out_type=__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	int)      ->					Dict:
         return self.sp_model.piece_to_id(__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	Tuple)      ->					Union[str, Any]:
         lowercase_     =      self.sp_model.IdToPiece(__lowerCAmelCase)
         return token


   def __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	int)      ->					str:
         lowercase_     =      []
         lowercase_     =      ""
         lowercase_     =      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(__lowerCAmelCase) + token
                     lowercase_     =      True
                     lowercase_     =      []
               else:
                     current_sub_tokens.append(__lowerCAmelCase)
                     lowercase_     =      False
         out_string += self.sp_model.decode(__lowerCAmelCase)
         return out_string.strip()


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	bool = False   ,		__lowerCAmelCase				:	bool = None   ,		__lowerCAmelCase				:	bool = True   ,		**__lowerCAmelCase				:	Optional[int]   ,		)      ->					str:
         lowercase_     =      kwargs.pop("use_source_tokenizer"   ,		__lowerCAmelCase)

         lowercase_     =      self.convert_ids_to_tokens(__lowerCAmelCase   ,		skip_special_tokens=__lowerCAmelCase)

         # To avoid mixing byte-level and unicode for byte-level BPT
         # we need to build string separately for added tokens and byte-level tokens
         # cf. https://github.com/huggingface/transformers/issues/1133
         lowercase_     =      []
         lowercase_     =      []
         for token in filtered_tokens:
               if skip_special_tokens and token in self.all_special_ids:
                     continue
               if token in self.added_tokens_encoder:
                     if current_sub_text:
                           sub_texts.append(self.convert_tokens_to_string(__lowerCAmelCase))
                           lowercase_     =      []
                     sub_texts.append(__lowerCAmelCase)
               else:
                     current_sub_text.append(__lowerCAmelCase)
         if current_sub_text:
               sub_texts.append(self.convert_tokens_to_string(__lowerCAmelCase))

         # Mimic the behavior of the Rust tokenizer:
         # No space before [MASK] and [SEP]
         if spaces_between_special_tokens:
               lowercase_     =      re.sub(R" (\[(MASK|SEP)\])"   ,		R"\1"   ,		" ".join(__lowerCAmelCase))
         else:
               lowercase_     =      "".join(__lowerCAmelCase)

         lowercase_     =      (
             clean_up_tokenization_spaces
             if clean_up_tokenization_spaces is not None
             else self.clean_up_tokenization_spaces
         )
         if clean_up_tokenization_spaces:
               lowercase_     =      self.clean_up_tokenization(__lowerCAmelCase)
               return clean_text
         else:
               return text


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Optional[str] = None)      ->					Tuple[str]:
         if not os.path.isdir(__lowerCAmelCase):
               logger.error(F'Vocabulary path ({save_directory}) should be a directory')
               return
         lowercase_     =      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_     =      self.sp_model.serialized_model_proto()
                     fi.write(__lowerCAmelCase)

         return (out_vocab_file,)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None)      ->					List[int]:
         if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         lowercase_     =      [self.cls_token_id]
         lowercase_     =      [self.sep_token_id]
         return cls + token_ids_a + sep + token_ids_a + sep


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None   ,		__lowerCAmelCase				:	bool = 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 [1] + ([0] * len(__lowerCAmelCase)) + [1]
         return [1] + ([0] * len(__lowerCAmelCase)) + [1] + ([0] * len(__lowerCAmelCase)) + [1]


   def __UpperCAmelCase       (   self				:	List[Any]   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None)      ->					List[int]:
         lowercase_     =      [self.sep_token_id]
         lowercase_     =      [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) * [0] + len(token_ids_a + sep) * [1]







'''simple docstring'''

import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
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_ : List[Any]						  =      get_tests_dir("fixtures/test_sentencepiece.model")





@require_sentencepiece
@require_tokenizers
class 							lowercase						(						__lowerCamelCase ,				unittest.TestCase ):
   lowerCamelCase_    					=ReformerTokenizer
   lowerCamelCase_    					=ReformerTokenizerFast
   lowerCamelCase_    					=True
   lowerCamelCase_    					=False
   lowerCamelCase_    					=True


   def __UpperCAmelCase       (   self				:	Optional[Any])      ->					Optional[Any]:
         super().setUp()

         lowercase_     =      ReformerTokenizer(__lowerCAmelCase   ,		keep_accents=__lowerCAmelCase)
         tokenizer.save_pretrained(self.tmpdirname)


   def __UpperCAmelCase       (   self				:	int)      ->					int:
         lowercase_     =      "<s>"
         lowercase_     =      1

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


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Optional[int]:
         lowercase_     =      list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]   ,		"<unk>")
         self.assertEqual(vocab_keys[1]   ,		"<s>")
         self.assertEqual(vocab_keys[-1]   ,		"j")
         self.assertEqual(len(__lowerCAmelCase)   ,		1000)


   def __UpperCAmelCase       (   self				:	Union[str, Any])      ->					Optional[Any]:
         self.assertEqual(self.get_tokenizer().vocab_size   ,		1000)


   def __UpperCAmelCase       (   self				:	List[Any])      ->					List[Any]:
         if not self.test_rust_tokenizer:
               return

         lowercase_     =      self.get_tokenizer()
         lowercase_     =      self.get_rust_tokenizer()

         lowercase_     =      "I was born in 92000, and this is falsé."

         lowercase_     =      tokenizer.tokenize(__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.tokenize(__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)

         lowercase_     =      tokenizer.encode(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.encode(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)

         lowercase_     =      self.get_rust_tokenizer()
         lowercase_     =      tokenizer.encode(__lowerCAmelCase)
         lowercase_     =      rust_tokenizer.encode(__lowerCAmelCase)
         self.assertListEqual(__lowerCAmelCase   ,		__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	List[str]=15)      ->					Tuple:
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
               with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
                     lowercase_     =      self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase   ,		**__lowerCAmelCase)

                     # Simple input
                     lowercase_     =      "This is a simple input"
                     lowercase_     =      ["This is a simple input 1", "This is a simple input 2"]
                     lowercase_     =      ("This is a simple input", "This is a pair")
                     lowercase_     =      [
                         ("This is a simple input 1", "This is a simple input 2"),
                         ("This is a simple pair 1", "This is a simple pair 2"),
                     ]

                     # Simple input tests
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Simple input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Simple input
                     self.assertRaises(
                         __lowerCAmelCase   ,		tokenizer_r.batch_encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length"   ,		)

                     # Pair input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Pair input
                     self.assertRaises(__lowerCAmelCase   ,		tokenizer_r.encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length")

                     # Pair input
                     self.assertRaises(
                         __lowerCAmelCase   ,		tokenizer_r.batch_encode_plus   ,		__lowerCAmelCase   ,		max_length=__lowerCAmelCase   ,		padding="max_length"   ,		)


   def __UpperCAmelCase       (   self				:	Tuple)      ->					Tuple:
         pass


   def __UpperCAmelCase       (   self				:	Any)      ->					Optional[Any]:
         lowercase_     =      ReformerTokenizer(__lowerCAmelCase   ,		keep_accents=__lowerCAmelCase)

         lowercase_     =      tokenizer.tokenize("This is a test")
         self.assertListEqual(__lowerCAmelCase   ,		["▁This", "▁is", "▁a", "▁t", "est"])

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__lowerCAmelCase)   ,		[285, 46, 10, 170, 382]   ,		)

         lowercase_     =      tokenizer.tokenize("I was born in 92000, and this is falsé.")
         self.assertListEqual(
             __lowerCAmelCase   ,		[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "9",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "é",
                 ".",
             ]   ,		)
         lowercase_     =      tokenizer.convert_tokens_to_ids(__lowerCAmelCase)
         self.assertListEqual(
             __lowerCAmelCase   ,		[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]   ,		)

         lowercase_     =      tokenizer.convert_ids_to_tokens(__lowerCAmelCase)
         self.assertListEqual(
             __lowerCAmelCase   ,		[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "<unk>",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "<unk>",
                 ".",
             ]   ,		)


   @cached_property
   def __UpperCAmelCase       (   self				:	List[str])      ->					Any:
         return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment")


   @slow
   def __UpperCAmelCase       (   self				:	Tuple)      ->					str:
         lowercase_     =      "Hello World!"
         lowercase_     =      [126, 32, 262, 152, 38, 72, 287]

         self.assertListEqual(__lowerCAmelCase   ,		self.big_tokenizer.encode(__lowerCAmelCase))


   @slow
   def __UpperCAmelCase       (   self				:	Any)      ->					Dict:
         lowercase_     =      (
             "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
             " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
         )
         lowercase_     =      [
             108,
             265,
             24,
             111,
             4,
             258,
             156,
             35,
             28,
             275,
             3,
             259,
             297,
             260,
             84,
             4,
             35,
             110,
             44,
             8,
             259,
             91,
             268,
             21,
             11,
             209,
             274,
             109,
             266,
             277,
             117,
             86,
             93,
             315,
             258,
             278,
             258,
             277,
             258,
             0,
             258,
             288,
             258,
             319,
             258,
             0,
             258,
             0,
             258,
             0,
             258,
             0,
             258,
             287,
             258,
             315,
             258,
             289,
             258,
             278,
             99,
             269,
             266,
             262,
             8,
             259,
             241,
             4,
             217,
             230,
             268,
             266,
             55,
             168,
             106,
             75,
             193,
             266,
             223,
             27,
             49,
             26,
             282,
             25,
             264,
             299,
             19,
             26,
             0,
             258,
             277,
             117,
             86,
             93,
             176,
             183,
             270,
             11,
             262,
             42,
             61,
             265,
         ]

         self.assertListEqual(__lowerCAmelCase   ,		self.big_tokenizer.encode(__lowerCAmelCase))


   @require_torch
   @slow
   def __UpperCAmelCase       (   self				:	Any)      ->					Tuple:
         import torch

         from transformers import ReformerConfig, ReformerModel

         # Build sequence
         lowercase_     =      list(self.big_tokenizer.get_vocab().keys())[:10]
         lowercase_     =      " ".join(__lowerCAmelCase)
         lowercase_     =      self.big_tokenizer.encode_plus(__lowerCAmelCase   ,		return_tensors="pt")
         lowercase_     =      self.big_tokenizer.batch_encode_plus([sequence, sequence]   ,		return_tensors="pt")

         lowercase_     =      ReformerConfig()
         # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
         lowercase_     =      encoded_sequence["input_ids"].shape
         lowercase_     =      ReformerModel(__lowerCAmelCase)

         # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
         assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

         with torch.no_grad():
               model(**__lowerCAmelCase)
               model(**__lowerCAmelCase)


   @slow
   def __UpperCAmelCase       (   self				:	List[Any])      ->					Tuple:
         # fmt: off
         lowercase_     =      {"input_ids": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], "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]]}  # noqa: E501
         # fmt: on

         # This tokenizer does not know some characters like ")".
         # That is the reason why we use very simple texts here.
         # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
         lowercase_     =      [
             "This is a very simple sentence.",
             "The quick brown fox jumps over the lazy dog.",
         ]

         self.tokenizer_integration_test_util(
             expected_encoding=__lowerCAmelCase   ,		model_name="google/reformer-crime-and-punishment"   ,		revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"   ,		padding=__lowerCAmelCase   ,		sequences=__lowerCAmelCase   ,		)






