
'''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					=			get_tests_dir('fixtures/test_sentencepiece.model')


@require_sentencepiece
@require_tokenizers
class      _lowerCAmelCase       (       __lowercase	,				unittest.TestCase ):







							'''simple docstring'''

							lowerCAmelCase_   		=		ReformerTokenizer
							lowerCAmelCase_   		=		ReformerTokenizerFast
							lowerCAmelCase_   		=		True
							lowerCAmelCase_   		=		False
							lowerCAmelCase_   		=		True

							def 			lowercase				(self    )	->  Tuple:
														super().setUp()

														_snake_case  =    ReformerTokenizer(UpperCAmelCase    ,    keep_accents=UpperCAmelCase    )
														tokenizer.save_pretrained(self.tmpdirname    )

							def 			lowercase				(self    )	->  Dict:
														_snake_case  =    """<s>"""
														_snake_case  =    1

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

							def 			lowercase				(self    )	->  Optional[int]:
														_snake_case  =    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(UpperCAmelCase    )    ,    1000    )

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

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

														if not self.test_rust_tokenizer:
																					return

														_snake_case  =    self.get_tokenizer()
														_snake_case  =    self.get_rust_tokenizer()

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

														_snake_case  =    tokenizer.tokenize(UpperCAmelCase    )
														_snake_case  =    rust_tokenizer.tokenize(UpperCAmelCase    )
														self.assertListEqual(UpperCAmelCase    ,    UpperCAmelCase    )

														_snake_case  =    tokenizer.encode(UpperCAmelCase    ,    add_special_tokens=UpperCAmelCase    )
														_snake_case  =    rust_tokenizer.encode(UpperCAmelCase    ,    add_special_tokens=UpperCAmelCase    )
														self.assertListEqual(UpperCAmelCase    ,    UpperCAmelCase    )

														_snake_case  =    self.get_rust_tokenizer()
														_snake_case  =    tokenizer.encode(UpperCAmelCase    )
														_snake_case  =    rust_tokenizer.encode(UpperCAmelCase    )
														self.assertListEqual(UpperCAmelCase    ,    UpperCAmelCase    )

							def 			lowercase				(self    ,    UpperCAmelCase=15    )	->  Optional[int]:

														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""    ):
																												_snake_case  =    self.rust_tokenizer_class.from_pretrained(UpperCAmelCase    ,    **UpperCAmelCase    )

																												# Simple input
																												_snake_case  =    """This is a simple input"""
																												_snake_case  =    ["""This is a simple input 1""", """This is a simple input 2"""]
																												_snake_case  =    ("""This is a simple input""", """This is a pair""")
																												_snake_case  =    [
																												    ("""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(UpperCAmelCase    ,    tokenizer_r.encode    ,    UpperCAmelCase    ,    max_length=UpperCAmelCase    ,    padding="""max_length"""    )

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

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

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

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

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

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

							def 			lowercase				(self    )	->  int:
														_snake_case  =    ReformerTokenizer(UpperCAmelCase    ,    keep_accents=UpperCAmelCase    )

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

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

														_snake_case  =    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""",
														        """.""",
														    ]    ,    )
														_snake_case  =    tokenizer.convert_tokens_to_ids(UpperCAmelCase    )
														self.assertListEqual(
														    UpperCAmelCase    ,    [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]    ,    )

														_snake_case  =    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 			lowercase				(self    )	->  List[Any]:
														return ReformerTokenizer.from_pretrained("""google/reformer-crime-and-punishment"""    )

							@slow
							def 			lowercase				(self    )	->  Any:
														_snake_case  =    """Hello World!"""
														_snake_case  =    [126, 32, 262, 152, 38, 72, 287]

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

							@slow
							def 			lowercase				(self    )	->  List[Any]:
														_snake_case  =    (
														    """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"""
														)
														_snake_case  =    [
														    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(UpperCAmelCase    ,    self.big_tokenizer.encode(UpperCAmelCase    )    )

							@require_torch
							@slow
							def 			lowercase				(self    )	->  Optional[int]:
														import torch

														from transformers import ReformerConfig, ReformerModel

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

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

														# 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(**UpperCAmelCase    )
																					model(**UpperCAmelCase    )





							@slow
							def 			lowercase				(self    )	->  Optional[Any]:
														_snake_case  =    {"""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
														_snake_case  =    [
														    """This is a very simple sentence.""",
														    """The quick brown fox jumps over the lazy dog.""",
														]

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

import warnings

from .generation import TFGenerationMixin







class 							lowerCAmelCase__   ( __lowercase						):
						# warning at import time
						warnings.warn(
						    "Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
						    "be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead."		,						__lowercase		,						)



