



import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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						    =  """▁"""

_lowerCamelCase						    =  get_tests_dir("""fixtures/test_sentencepiece.model""")

@require_sentencepiece
@require_tokenizers
class       _SCREAMING_SNAKE_CASE	(UpperCamelCase			,    unittest.TestCase ):
     lowerCAmelCase					=			BigBirdTokenizer
     lowerCAmelCase					=			BigBirdTokenizerFast
     lowerCAmelCase					=			True
     lowerCAmelCase					=			True





     def 	__snake_case    (       self :							Union[str, Any]				)->Tuple:
      super().setUp()

      __SCREAMING_SNAKE_CASE       :    int       =	self.tokenizer_class(UpperCamelCase     ,  keep_accents=UpperCamelCase				)
      tokenizer.save_pretrained(self.tmpdirname				)





     def 	__snake_case    (       self :							Optional[Any]				)->str:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	"<s>"
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	1

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





     def 	__snake_case    (       self :							Optional[int]				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Any       =	list(self.get_tokenizer().get_vocab().keys()				)

      self.assertEqual(vocab_keys[0]     ,  "<unk>"				)
      self.assertEqual(vocab_keys[1]     ,  "<s>"				)
      self.assertEqual(vocab_keys[-1]     ,  "[MASK]"				)
      self.assertEqual(len(UpperCamelCase				)     ,  1_0_0_4				)





     def 	__snake_case    (       self :							List[Any]				)->List[Any]:
      self.assertEqual(self.get_tokenizer().vocab_size     ,  1_0_0_0				)





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

      __SCREAMING_SNAKE_CASE       :    List[Any]       =	self.get_tokenizer()
      __SCREAMING_SNAKE_CASE       :    Any       =	self.get_rust_tokenizer()

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

      __SCREAMING_SNAKE_CASE       :    Dict       =	tokenizer.tokenize(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    List[str]       =	rust_tokenizer.tokenize(UpperCamelCase				)
      self.assertListEqual(UpperCamelCase     ,  UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    str       =	tokenizer.encode(UpperCamelCase     ,  add_special_tokens=UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	rust_tokenizer.encode(UpperCamelCase     ,  add_special_tokens=UpperCamelCase				)
      self.assertListEqual(UpperCamelCase     ,  UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    str       =	self.get_rust_tokenizer()
      __SCREAMING_SNAKE_CASE       :    str       =	tokenizer.encode(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    str       =	rust_tokenizer.encode(UpperCamelCase				)
      self.assertListEqual(UpperCamelCase     ,  UpperCamelCase				)





     def 	__snake_case    (       self :							Union[str, Any]				)->List[Any]:
      __SCREAMING_SNAKE_CASE       :    Tuple       =	BigBirdTokenizer(UpperCamelCase     ,  keep_accents=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    Any       =	tokenizer.tokenize("This is a test"				)
      self.assertListEqual(UpperCamelCase     ,  ["▁This", "▁is", "▁a", "▁t", "est"]				)

      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(UpperCamelCase				)     ,  [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]     ,  )

      __SCREAMING_SNAKE_CASE       :    List[str]       =	tokenizer.tokenize("I was born in 92000, and this is falsé."				)
      self.assertListEqual(
          UpperCamelCase     ,  [
              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",
              ".",
          ]     ,  )
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	tokenizer.convert_tokens_to_ids(UpperCamelCase				)
      self.assertListEqual(
          UpperCamelCase     ,  [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]     ,  )

      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	tokenizer.convert_ids_to_tokens(UpperCamelCase				)
      self.assertListEqual(
          UpperCamelCase     ,  [
              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 	__snake_case    (       self :							Any				)->Optional[int]:
      return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"				)





     @slow
     def 	__snake_case    (       self :							Any				)->Dict:
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	"Hello World!"
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	[6_5, 1_8_5_3_6, 2_2_6_0, 1_0_1, 6_6]

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





     @slow
     def 	__snake_case    (       self :							Any				)->Union[str, Any]:
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	(
          "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"
      )
      # fmt: off
      __SCREAMING_SNAKE_CASE       :    Union[str, Any]       =	[6_5, 8_7_1, 4_1_9, 3_5_8, 9_4_6, 9_9_1, 2_5_2_1, 4_5_2, 3_5_8, 1_3_5_7, 3_8_7, 7_7_5_1, 3_5_3_6, 1_1_2, 9_8_5, 4_5_6, 1_2_6, 8_6_5, 9_3_8, 5_4_0_0, 5_7_3_4, 4_5_8, 1_3_6_8, 4_6_7, 7_8_6, 2_4_6_2, 5_2_4_6, 1_1_5_9, 6_3_3, 8_6_5, 4_5_1_9, 4_5_7, 5_8_2, 8_5_2, 2_5_5_7, 4_2_7, 9_1_6, 5_0_8, 4_0_5, 3_4_3_2_4, 4_9_7, 3_9_1, 4_0_8, 1_1_3_4_2, 1_2_4_4, 3_8_5, 1_0_0, 9_3_8, 9_8_5, 4_5_6, 5_7_4, 3_6_2, 1_2_5_9_7, 3_2_0_0, 3_1_2_9, 1_1_7_2, 6_6]  # noqa: E231
      # fmt: on
      self.assertListEqual(UpperCamelCase     ,  self.big_tokenizer.encode(UpperCamelCase				)				)





     @require_torch
     @slow
     def 	__snake_case    (       self :							Optional[Any]				)->Tuple:
      import torch

      from transformers import BigBirdConfig, BigBirdModel

      # Build sequence
      __SCREAMING_SNAKE_CASE       :    Tuple       =	list(self.big_tokenizer.get_vocab().keys()				)[:1_0]
      __SCREAMING_SNAKE_CASE       :    int       =	" ".join(UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	self.big_tokenizer.encode_plus(UpperCamelCase     ,  return_tensors="pt"     ,  return_token_type_ids=UpperCamelCase				)
      __SCREAMING_SNAKE_CASE       :    int       =	self.big_tokenizer.batch_encode_plus(
          [sequence + " " + sequence]     ,  return_tensors="pt"     ,  return_token_type_ids=UpperCamelCase				)

      __SCREAMING_SNAKE_CASE       :    List[Any]       =	BigBirdConfig(attention_type="original_full"				)
      __SCREAMING_SNAKE_CASE       :    List[str]       =	BigBirdModel(UpperCamelCase				)

      assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

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





     @slow
     def 	__snake_case    (       self :							Optional[int]				)->List[str]:
      __SCREAMING_SNAKE_CASE       :    List[str]       =	BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"				)
      __SCREAMING_SNAKE_CASE       :    List[str]       =	tokenizer.decode(tokenizer("Paris is the [MASK]."				).input_ids				)

      self.assertTrue(decoded_text == "[CLS] Paris is the[MASK].[SEP]"				)






     @slow
     def 	__snake_case    (       self :							int				)->int:
      # fmt: off
      __SCREAMING_SNAKE_CASE       :    Tuple       =	{"input_ids": [[6_5, 3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4, 6_6], [6_5, 4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 6_6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [6_5, 4_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 6_6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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], [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]]}  # noqa: E501
      # fmt: on

      self.tokenizer_integration_test_util(
          expected_encoding=UpperCamelCase     ,  model_name="google/bigbird-roberta-base"     ,  revision="215c99f1600e06f83acce68422f2035b2b5c3510"     ,  )











from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike

class       _SCREAMING_SNAKE_CASE	(UpperCamelCase ):





     def __init__(       self :							List[str]     ,  UpperCamelCase :							Optional[NestedDataStructureLike[PathLike]] = None     ,  UpperCamelCase :							Optional[NamedSplit] = None     ,  UpperCamelCase :							Optional[Features] = None     ,  UpperCamelCase :							str = None     ,  UpperCamelCase :							bool = False     ,  UpperCamelCase :							bool = False     ,  UpperCamelCase :							Optional[int] = None     ,  **UpperCamelCase :							Dict     ,  )->int:
      __SCREAMING_SNAKE_CASE       :    List[str]       =	path_or_paths
      __SCREAMING_SNAKE_CASE       :    Optional[int]       =	split if split or isinstance(UpperCamelCase     ,  UpperCamelCase				) else "train"
      __SCREAMING_SNAKE_CASE       :    Dict       =	features
      __SCREAMING_SNAKE_CASE       :    List[Any]       =	cache_dir
      __SCREAMING_SNAKE_CASE       :    Tuple       =	keep_in_memory
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	streaming
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	num_proc
      __SCREAMING_SNAKE_CASE       :    int       =	kwargs






     @abstractmethod
     def 	__snake_case    (       self :							Optional[int]				)->Union[Dataset, DatasetDict, IterableDataset, IterableDatasetDict]:
      pass






class       _SCREAMING_SNAKE_CASE	(UpperCamelCase ):





     def __init__(       self :							Optional[Any]     ,  UpperCamelCase :							Optional[Features] = None     ,  UpperCamelCase :							str = None     ,  UpperCamelCase :							bool = False     ,  UpperCamelCase :							bool = False     ,  UpperCamelCase :							Optional[int] = None     ,  **UpperCamelCase :							Dict     ,  )->Optional[int]:
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	features
      __SCREAMING_SNAKE_CASE       :    str       =	cache_dir
      __SCREAMING_SNAKE_CASE       :    Any       =	keep_in_memory
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	streaming
      __SCREAMING_SNAKE_CASE       :    int       =	num_proc
      __SCREAMING_SNAKE_CASE       :    Optional[Any]       =	kwargs






     @abstractmethod
     def 	__snake_case    (       self :							str				)->Union[Dataset, IterableDataset]:
      pass






