






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[str]						   =       get_tests_dir('''fixtures/test_sentencepiece.model''')

@require_sentencepiece
@require_tokenizers
class 		lowerCAmelCase     ( __a      ,       unittest.TestCase			):

					'''simple docstring'''

					_A						:			Union[str, Any]									=      ReformerTokenizer
					_A						:			int									=      ReformerTokenizerFast
					_A						:			Any									=      True
					_A						:			Tuple									=      False
					_A						:			Union[str, Any]									=      True



					def       lowerCAmelCase				(  self				:	Optional[int]							)			->  List[str]:


												"""simple docstring"""

												super().setUp()

												__lowercase      :							str				=     ReformerTokenizer(__a		,     keep_accents=__a							)
												tokenizer.save_pretrained(self.tmpdirname							)



					def       lowerCAmelCase				(  self				:	int							)			->  Dict:


												"""simple docstring"""

												__lowercase      :							Optional[Any]				=     """<s>"""
												__lowercase      :							Any				=     1

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



					def       lowerCAmelCase				(  self				:	Tuple							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							str				=     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(__a							)		,     1000							)



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


												"""simple docstring"""

												self.assertEqual(self.get_tokenizer().vocab_size		,     1000							)



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


												"""simple docstring"""

												if not self.test_rust_tokenizer:
																			return

												__lowercase      :							Any				=     self.get_tokenizer()
												__lowercase      :							Union[str, Any]				=     self.get_rust_tokenizer()

												__lowercase      :							Dict				=     """I was born in 92000, and this is falsé."""

												__lowercase      :							Any				=     tokenizer.tokenize(__a							)
												__lowercase      :							Any				=     rust_tokenizer.tokenize(__a							)
												self.assertListEqual(__a		,     __a							)

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

												__lowercase      :							str				=     self.get_rust_tokenizer()
												__lowercase      :							Optional[int]				=     tokenizer.encode(__a							)
												__lowercase      :							Optional[int]				=     rust_tokenizer.encode(__a							)
												self.assertListEqual(__a		,     __a							)



					def       lowerCAmelCase				(  self				:	List[str]		,     __a				:	Union[str, Any]=15							)			->  int:


												"""simple docstring"""

												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"							):
																										__lowercase      :							Dict				=     self.rust_tokenizer_class.from_pretrained(__a		,     **__a							)

																										# Simple input
																										__lowercase      :							Optional[Any]				=     """This is a simple input"""
																										__lowercase      :							Optional[int]				=     ["""This is a simple input 1""", """This is a simple input 2"""]
																										__lowercase      :							List[Any]				=     ("""This is a simple input""", """This is a pair""")
																										__lowercase      :							Any				=     [
																										    ("""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(__a		,     tokenizer_r.encode		,     __a		,     max_length=__a		,     padding="""max_length"""							)

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

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

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

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

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



					def       lowerCAmelCase				(  self				:	Optional[int]							)			->  Union[str, Any]:


												"""simple docstring"""

												pass



					def       lowerCAmelCase				(  self				:	List[Any]							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Optional[Any]				=     ReformerTokenizer(__a		,     keep_accents=__a							)

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

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

												__lowercase      :							Optional[Any]				=     tokenizer.tokenize("""I was born in 92000, and this is falsé."""							)
												self.assertListEqual(
												    __a		,     [
												        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      :							Any				=     tokenizer.convert_tokens_to_ids(__a							)
												self.assertListEqual(
												    __a		,     [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]		,     )

												__lowercase      :							Optional[Any]				=     tokenizer.convert_ids_to_tokens(__a							)
												self.assertListEqual(
												    __a		,     [
												        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       lowerCAmelCase				(  self				:	List[Any]							)			->  Tuple:


												"""simple docstring"""

												return ReformerTokenizer.from_pretrained("""google/reformer-crime-and-punishment"""							)



					@slow
					def       lowerCAmelCase				(  self				:	str							)			->  Optional[int]:


												"""simple docstring"""

												__lowercase      :							str				=     """Hello World!"""
												__lowercase      :							Optional[int]				=     [126, 32, 262, 152, 38, 72, 287]

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



					@slow
					def       lowerCAmelCase				(  self				:	Tuple							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Optional[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"""
												)
												__lowercase      :							int				=     [
												    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(__a		,     self.big_tokenizer.encode(__a							)							)



					@require_torch
					@slow
					def       lowerCAmelCase				(  self				:	Optional[int]							)			->  Dict:


												"""simple docstring"""

												import torch

												from transformers import ReformerConfig, ReformerModel

												# Build sequence
												__lowercase      :							Optional[Any]				=     list(self.big_tokenizer.get_vocab().keys()							)[:10]
												__lowercase      :							int				=     """ """.join(__a							)
												__lowercase      :							int				=     self.big_tokenizer.encode_plus(__a		,     return_tensors="""pt"""							)
												__lowercase      :							List[Any]				=     self.big_tokenizer.batch_encode_plus([sequence, sequence]		,     return_tensors="""pt"""							)

												__lowercase      :							List[str]				=     ReformerConfig()
												# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
												__lowercase      :							str				=     encoded_sequence["""input_ids"""].shape
												__lowercase      :							Optional[Any]				=     ReformerModel(__a							)

												# 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(**__a							)
																			model(**__a							)



					@slow
					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  Any:


												"""simple docstring"""

												__lowercase      :							int				=     {"""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      :							List[str]				=     [
												    """This is a very simple sentence.""",
												    """The quick brown fox jumps over the lazy dog.""",
												]

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







from argparse import ArgumentParser

from . import BaseTransformersCLICommand
def       snake_case_		(     lowerCAmelCase_       :						Dict      ):
							return DownloadCommand(args.model       ,       args.cache_dir       ,       args.force       ,       args.trust_remote_code      )



class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					@staticmethod
					def       lowerCAmelCase				(  __a				:	ArgumentParser							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     parser.add_parser("""download"""							)
												download_parser.add_argument(
												    """--cache-dir"""		,     type=__a		,     default=__a		,     help="""Path to location to store the models"""							)
												download_parser.add_argument(
												    """--force"""		,     action="""store_true"""		,     help="""Force the model to be download even if already in cache-dir"""							)
												download_parser.add_argument(
												    """--trust-remote-code"""		,     action="""store_true"""		,     help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""		,     )
												download_parser.add_argument("""model"""		,     type=__a		,     help="""Name of the model to download"""							)
												download_parser.set_defaults(func=__a							)



					def __init__(  self				:	Dict		,     __a				:	str		,     __a				:	str		,     __a				:	bool		,     __a				:	bool							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Dict				=     model
												__lowercase      :							List[Any]				=     cache
												__lowercase      :							Any				=     force
												__lowercase      :							Optional[int]				=     trust_remote_code



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


												"""simple docstring"""

												from ..models.auto import AutoModel, AutoTokenizer

												AutoModel.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)
												AutoTokenizer.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)