






"""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      UpperCamelCase		(__snake_case						,						unittest.TestCase     ):
						_SCREAMING_SNAKE_CASE  : str												=		ReformerTokenizer
						_SCREAMING_SNAKE_CASE  : int												=		ReformerTokenizerFast
						_SCREAMING_SNAKE_CASE  : Any												=		True
						_SCREAMING_SNAKE_CASE  : str												=		False
						_SCREAMING_SNAKE_CASE  : List[str]												=		True






						def      __snake_case      (		self  :Any				)      ->List[Any]:
										super().setUp()

										lowercase    :      str       = ReformerTokenizer(__magic_name__			, keep_accents=__magic_name__				)
										tokenizer.save_pretrained(self.tmpdirname				)






						def      __snake_case      (		self  :Any				)      ->List[str]:
										lowercase    :      Dict       = """<s>"""
										lowercase    :      Tuple       = 1

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






						def      __snake_case      (		self  :Optional[Any]				)      ->int:
										lowercase    :      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]			, """j"""				)
										self.assertEqual(len(__magic_name__				)			, 1_000				)






						def      __snake_case      (		self  :Dict				)      ->List[Any]:
										self.assertEqual(self.get_tokenizer().vocab_size			, 1_000				)






						def      __snake_case      (		self  :int				)      ->Dict:
										if not self.test_rust_tokenizer:
														return

										lowercase    :      int       = self.get_tokenizer()
										lowercase    :      Any       = self.get_rust_tokenizer()

										lowercase    :      Any       = """I was born in 92000, and this is falsé."""

										lowercase    :      Union[str, Any]       = tokenizer.tokenize(__magic_name__				)
										lowercase    :      List[str]       = rust_tokenizer.tokenize(__magic_name__				)
										self.assertListEqual(__magic_name__			, __magic_name__				)

										lowercase    :      Optional[Any]       = tokenizer.encode(__magic_name__			, add_special_tokens=__magic_name__				)
										lowercase    :      Any       = rust_tokenizer.encode(__magic_name__			, add_special_tokens=__magic_name__				)
										self.assertListEqual(__magic_name__			, __magic_name__				)

										lowercase    :      str       = self.get_rust_tokenizer()
										lowercase    :      int       = tokenizer.encode(__magic_name__				)
										lowercase    :      Any       = rust_tokenizer.encode(__magic_name__				)
										self.assertListEqual(__magic_name__			, __magic_name__				)






						def      __snake_case      (		self  :List[str]			, __magic_name__  :Any=15				)      ->List[str]:
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
																		lowercase    :      List[str]       = self.rust_tokenizer_class.from_pretrained(__magic_name__			, **__magic_name__				)

																		# Simple input
																		lowercase    :      str       = """This is a simple input"""
																		lowercase    :      Union[str, Any]       = ["""This is a simple input 1""", """This is a simple input 2"""]
																		lowercase    :      Any       = ("""This is a simple input""", """This is a pair""")
																		lowercase    :      Optional[int]       = [
																		    ("""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(__magic_name__			, tokenizer_r.encode			, __magic_name__			, max_length=__magic_name__			, padding="""max_length"""				)

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

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

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

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

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






						def      __snake_case      (		self  :Dict				)      ->List[str]:
										pass






						def      __snake_case      (		self  :Optional[Any]				)      ->Union[str, Any]:
										lowercase    :      int       = ReformerTokenizer(__magic_name__			, keep_accents=__magic_name__				)

										lowercase    :      Optional[int]       = tokenizer.tokenize("""This is a test"""				)
										self.assertListEqual(__magic_name__			, ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]				)

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

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

										lowercase    :      int       = tokenizer.convert_ids_to_tokens(__magic_name__				)
										self.assertListEqual(
										    __magic_name__			, [
										        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  :Optional[int]				)      ->Any:
										return ReformerTokenizer.from_pretrained("""google/reformer-crime-and-punishment"""				)






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

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






						@slow
						def      __snake_case      (		self  :str				)      ->Optional[Any]:
										lowercase    :      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    :      Dict       = [
										    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(__magic_name__			, self.big_tokenizer.encode(__magic_name__				)				)






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

										from transformers import ReformerConfig, ReformerModel

										# Build sequence
										lowercase    :      Union[str, Any]       = list(self.big_tokenizer.get_vocab().keys()				)[:10]
										lowercase    :      List[str]       = """ """.join(__magic_name__				)
										lowercase    :      str       = self.big_tokenizer.encode_plus(__magic_name__			, return_tensors="""pt"""				)
										lowercase    :      Optional[Any]       = self.big_tokenizer.batch_encode_plus([sequence, sequence]			, return_tensors="""pt"""				)

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

										# 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(**__magic_name__				)
														model(**__magic_name__				)






						@slow
						def      __snake_case      (		self  :str				)      ->int:
										# fmt: off
										lowercase    :      Optional[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    :      Optional[int]       = [
										    """This is a very simple sentence.""",
										    """The quick brown fox jumps over the lazy dog.""",
										]

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








"""simple docstring"""







import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


_lowerCAmelCase            =	logging.get_logger(__name__)


_lowerCAmelCase            =	{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

_lowerCAmelCase            =	{
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

_lowerCAmelCase            =	{'facebook/blenderbot_small-90M': 5_12}


def      UpperCamelCase       ( _A )     ->       Dict:
				lowercase    :      Union[str, Any]       = set()
				lowercase    :      Union[str, Any]       = word[0]
				for char in word[1:]:
								pairs.add((prev_char, char) )
								lowercase    :      List[str]       = char

				lowercase    :      Optional[Any]       = set(_A )
				return pairs


class      UpperCamelCase		(__snake_case     ):
						_SCREAMING_SNAKE_CASE  : Optional[int]												=		VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE  : str												=		PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE  : Union[str, Any]												=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_SCREAMING_SNAKE_CASE  : Any												=		["""input_ids""", """attention_mask"""]






						def __init__(		self  :Any			, __magic_name__  :Union[str, Any]			, __magic_name__  :str			, __magic_name__  :Union[str, Any]="__start__"			, __magic_name__  :Optional[int]="__end__"			, __magic_name__  :Tuple="__unk__"			, __magic_name__  :Optional[int]="__null__"			, **__magic_name__  :Tuple			, )      ->Tuple:
										super().__init__(unk_token=__magic_name__			, bos_token=__magic_name__			, eos_token=__magic_name__			, pad_token=__magic_name__			, **__magic_name__				)

										with open(__magic_name__			, encoding="""utf-8"""				) as vocab_handle:
														lowercase    :      int       = json.load(__magic_name__				)
										lowercase    :      int       = {v: k for k, v in self.encoder.items()}
										with open(__magic_name__			, encoding="""utf-8"""				) as merges_handle:
														lowercase    :      Any       = merges_handle.read().split("""\n"""				)[1:-1]
										lowercase    :      Union[str, Any]       = [tuple(merge.split()				) for merge in merges]
										lowercase    :      Any       = dict(zip(__magic_name__			, range(len(__magic_name__				)				)				)				)
										lowercase    :      Union[str, Any]       = {}






						@property
						def      __snake_case      (		self  :int				)      ->int:
										return len(self.encoder				)






						def      __snake_case      (		self  :Optional[Any]				)      ->Dict:
										return dict(self.encoder			, **self.added_tokens_encoder				)






						def      __snake_case      (		self  :List[str]			, __magic_name__  :str				)      ->str:
										if token in self.cache:
														return self.cache[token]
										lowercase    :      Dict       = re.sub("""([.,!?()])"""			, r""" \1"""			, __magic_name__				)
										lowercase    :      Tuple       = re.sub("""(')"""			, r""" \1 """			, __magic_name__				)
										lowercase    :      List[str]       = re.sub(r"""\s{2,}"""			, """ """			, __magic_name__				)
										if "\n" in token:
														lowercase    :      int       = token.replace("""\n"""			, """ __newln__"""				)

										lowercase    :      Tuple       = token.split(""" """				)
										lowercase    :      Dict       = []
										for token in tokens:
														if not len(__magic_name__				):
																		continue

														lowercase    :      List[Any]       = token.lower()
														lowercase    :      int       = tuple(__magic_name__				)
														lowercase    :      List[str]       = tuple(list(word[:-1]				) + [word[-1] + """</w>"""]				)
														lowercase    :      List[str]       = get_pairs(__magic_name__				)

														if not pairs:
																		words.append(__magic_name__				)
																		continue

														while True:
																		lowercase    :      Optional[Any]       = min(__magic_name__			, key=lambda __magic_name__				: self.bpe_ranks.get(__magic_name__			, float("""inf"""				)				)				)
																		if bigram not in self.bpe_ranks:
																						break
																		lowercase      ,      lowercase    :      List[str]       = bigram
																		lowercase    :      Dict       = []
																		lowercase    :      Optional[int]       = 0

																		while i < len(__magic_name__				):
																						try:
																										lowercase    :      Optional[Any]       = word.index(__magic_name__			, __magic_name__				)
																										new_word.extend(word[i:j]				)
																										lowercase    :      Union[str, Any]       = j
																						except ValueError:
																										new_word.extend(word[i:]				)
																										break

																						if word[i] == first and i < len(__magic_name__				) - 1 and word[i + 1] == second:
																										new_word.append(first + second				)
																										i += 2
																						else:
																										new_word.append(word[i]				)
																										i += 1
																		lowercase    :      str       = tuple(__magic_name__				)
																		lowercase    :      Optional[Any]       = new_word
																		if len(__magic_name__				) == 1:
																						break
																		else:
																						lowercase    :      List[Any]       = get_pairs(__magic_name__				)
														lowercase    :      int       = """@@ """.join(__magic_name__				)
														lowercase    :      int       = word[:-4]

														lowercase    :      List[str]       = word
														words.append(__magic_name__				)
										return " ".join(__magic_name__				)






						def      __snake_case      (		self  :List[str]			, __magic_name__  :str				)      ->List[str]:
										lowercase    :      str       = []

										lowercase    :      Dict       = re.findall(r"""\S+\n?"""			, __magic_name__				)

										for token in words:
														split_tokens.extend(list(self.bpe(__magic_name__				).split(""" """				)				)				)
										return split_tokens






						def      __snake_case      (		self  :int			, __magic_name__  :str				)      ->int:
										lowercase    :      Tuple       = token.lower()
										return self.encoder.get(__magic_name__			, self.encoder.get(self.unk_token				)				)






						def      __snake_case      (		self  :Tuple			, __magic_name__  :int				)      ->str:
										return self.decoder.get(__magic_name__			, self.unk_token				)






						def      __snake_case      (		self  :Tuple			, __magic_name__  :List[str]				)      ->str:
										lowercase    :      Tuple       = """ """.join(__magic_name__				).replace("""@@ """			, """"""				).strip()
										return out_string






						def      __snake_case      (		self  :List[Any]			, __magic_name__  :str			, __magic_name__  :Optional[str] = None				)      ->Tuple[str]:
										if not os.path.isdir(__magic_name__				):
														logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
														return
										lowercase    :      str       = os.path.join(
										    __magic_name__			, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)
										lowercase    :      List[str]       = os.path.join(
										    __magic_name__			, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]				)

										with open(__magic_name__			, """w"""			, encoding="""utf-8"""				) as f:
														f.write(json.dumps(self.encoder			, indent=2			, sort_keys=__magic_name__			, ensure_ascii=__magic_name__				) + """\n"""				)

										lowercase    :      Any       = 0
										with open(__magic_name__			, """w"""			, encoding="""utf-8"""				) as writer:
														writer.write("""#version: 0.2\n"""				)
														for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			, key=lambda __magic_name__				: kv[1]				):
																		if index != token_index:
																						logger.warning(
																						    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																						    """ Please check that the tokenizer is not corrupted!"""				)
																						lowercase    :      Any       = token_index
																		writer.write(""" """.join(__magic_name__				) + """\n"""				)
																		index += 1

										return vocab_file, merge_file
