




"""simple docstring"""







import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer


if TYPE_CHECKING:
		from ...tokenization_utils_base import TextInput
from ...utils import logging


a      =		logging.get_logger(__name__)

a      =		{'vocab_file': 'spiece.model'}

a      =		{
    'vocab_file': {
        't5-small': 'https://huggingface.co/t5-small/resolve/main/spiece.model',
        't5-base': 'https://huggingface.co/t5-base/resolve/main/spiece.model',
        't5-large': 'https://huggingface.co/t5-large/resolve/main/spiece.model',
        't5-3b': 'https://huggingface.co/t5-3b/resolve/main/spiece.model',
        't5-11b': 'https://huggingface.co/t5-11b/resolve/main/spiece.model',
    }
}


# TODO(PVP) - this should be removed in Transformers v5
a      =		{
    't5-small': 5_1_2,
    't5-base': 5_1_2,
    't5-large': 5_1_2,
    't5-3b': 5_1_2,
    't5-11b': 5_1_2,
}

a      =		'▁'






class       SCREAMING_SNAKE_CASE__					(					_a					):
						_a    						=						VOCAB_FILES_NAMES
						_a    						=						PRETRAINED_VOCAB_FILES_MAP
						_a    						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_a    						=						['input_ids', 'attention_mask']


						def __init__(							self				:			Optional[Any]						,						lowerCAmelCase				:			Optional[int]						,						lowerCAmelCase				:			Any="</s>"						,						lowerCAmelCase				:			List[Any]="<unk>"						,						lowerCAmelCase				:			Any="<pad>"						,						lowerCAmelCase				:			Union[str, Any]=100						,						lowerCAmelCase				:			Any=None						,						lowerCAmelCase				:			Optional[Dict[str, Any]] = None						,						lowerCAmelCase				:			Dict=True						,						**lowerCAmelCase				:			List[str]						,						):
										# Add extra_ids to the special token list
										if extra_ids > 0 and additional_special_tokens is None:
														lowerCAmelCase  =				[f'''<extra_id_{i}>''' for i in range(lowerCAmelCase					)]
										elif extra_ids > 0 and additional_special_tokens is not None:
														# Check that we have the right number of extra_id special tokens
														lowerCAmelCase  =				len(set(filter(lambda lowerCAmelCase					: bool("""extra_id""" in str(lowerCAmelCase					)					)						,						lowerCAmelCase					)					)					)
														if extra_tokens != extra_ids:
																		raise ValueError(
																		    f'''Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'''
																		    """ provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids"""
																		    """ tokens"""					)
										if legacy:
														logger.warning_once(
														    f'''You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to'''
														    """ read the related pull request available at https://github.com/huggingface/transformers/pull/24565"""					)

										lowerCAmelCase  =				legacy
										lowerCAmelCase  =				{} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    eos_token=lowerCAmelCase						,						unk_token=lowerCAmelCase						,						pad_token=lowerCAmelCase						,						extra_ids=lowerCAmelCase						,						additional_special_tokens=lowerCAmelCase						,						sp_model_kwargs=self.sp_model_kwargs						,						legacy=lowerCAmelCase						,						**lowerCAmelCase						,						)

										lowerCAmelCase  =				vocab_file
										lowerCAmelCase  =				extra_ids

										lowerCAmelCase  =				spm.SentencePieceProcessor(**self.sp_model_kwargs					)
										self.sp_model.Load(lowerCAmelCase					)


						@staticmethod
						def   __lowercase (							lowerCAmelCase				:			List[str]						,						lowerCAmelCase				:			Optional[Any]						,						lowerCAmelCase				:			str					):
										if pretrained_model_name_or_path in TaTokenizer.max_model_input_sizes:
														lowerCAmelCase  =				TaTokenizer.max_model_input_sizes[pretrained_model_name_or_path]
														if init_max_model_length is not None and init_max_model_length != max_model_length:
																		return init_max_model_length
														elif init_max_model_length is None:
																		warnings.warn(
																		    """This tokenizer was incorrectly instantiated with a model max length of"""
																		    f''' {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this'''
																		    """ behavior is kept to avoid breaking backwards compatibility when padding/encoding with"""
																		    """ `truncation is True`.\n- Be aware that you SHOULD NOT rely on"""
																		    f''' {pretrained_model_name_or_path} automatically truncating your input to'''
																		    f''' {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences'''
																		    f''' longer than {deprecated_max_model_length} you can either instantiate this tokenizer with'''
																		    """ `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please"""
																		    """ instantiate this tokenizer with `model_max_length` set to your preferred value."""						,						lowerCAmelCase						,						)

										return max_model_length


						@property
						def   __lowercase (							self				:			List[str]					):
										return self.sp_model.get_piece_size() + self._extra_ids


						def   __lowercase (							self				:			Optional[int]					):
										lowerCAmelCase  =				{self.convert_ids_to_tokens(lowerCAmelCase					): i for i in range(self.vocab_size					)}
										vocab.update(self.added_tokens_encoder					)
										return vocab


						def   __lowercase (							self				:			Any						,						lowerCAmelCase				:			List[int]						,						lowerCAmelCase				:			Optional[List[int]] = None						,						lowerCAmelCase				:			bool = False					):
										if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=lowerCAmelCase						,						token_ids_a=lowerCAmelCase						,						already_has_special_tokens=lowerCAmelCase					)

										# normal case: some special tokens
										if token_ids_a is None:
														return ([0] * len(lowerCAmelCase					)) + [1]
										return ([0] * len(lowerCAmelCase					)) + [1] + ([0] * len(lowerCAmelCase					)) + [1]


						def   __lowercase (							self				:			Any					):
										return list(
										    set(filter(lambda lowerCAmelCase					: bool(re.search(R"""<extra_id_\d+>"""						,						lowerCAmelCase					)					) is not None						,						self.additional_special_tokens					)					)					)


						def   __lowercase (							self				:			Optional[Any]					):
										return [self._convert_token_to_id(lowerCAmelCase					) for token in self.get_sentinel_tokens()]


						def   __lowercase (							self				:			Dict						,						lowerCAmelCase				:			List[int]					):
										if len(lowerCAmelCase					) > 0 and token_ids[-1] == self.eos_token_id:
														warnings.warn(
														    f'''This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated'''
														    """ eos tokens being added."""					)
														return token_ids
										else:
														return token_ids + [self.eos_token_id]


						def   __lowercase (							self				:			Optional[int]						,						lowerCAmelCase				:			List[int]						,						lowerCAmelCase				:			Optional[List[int]] = None					):
										lowerCAmelCase  =				[self.eos_token_id]

										if token_ids_a is None:
														return len(token_ids_a + eos					) * [0]
										return len(token_ids_a + eos + token_ids_a + eos					) * [0]


						def   __lowercase (							self				:			int						,						lowerCAmelCase				:			List[int]						,						lowerCAmelCase				:			Optional[List[int]] = None					):
										lowerCAmelCase  =				self._add_eos_if_not_present(lowerCAmelCase					)
										if token_ids_a is None:
														return token_ids_a
										else:
														lowerCAmelCase  =				self._add_eos_if_not_present(lowerCAmelCase					)
														return token_ids_a + token_ids_a


						def __getstate__(							self				:			int					):
										lowerCAmelCase  =				self.__dict__.copy()
										lowerCAmelCase  =				None
										return state


						def __setstate__(							self				:			Optional[int]						,						lowerCAmelCase				:			Dict					):
										lowerCAmelCase  =				d

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

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


						def   __lowercase (							self				:			Any						,						lowerCAmelCase				:			"TextInput"						,						**lowerCAmelCase				:			Tuple					):
										# Replace the SPIECE_UNDERLINE with a space to make sure SPIECE_UNDERLINE is only used at
										# the beginning of the text
										if not self.legacy:
														lowerCAmelCase  =				SPIECE_UNDERLINE + text.replace(lowerCAmelCase						,						""" """					)
										return super().tokenize(lowerCAmelCase						,						**lowerCAmelCase					)


						def   __lowercase (							self				:			Dict						,						lowerCAmelCase				:			Dict						,						**lowerCAmelCase				:			List[str]					):
										if not self.legacy:
														lowerCAmelCase  =				text.startswith(lowerCAmelCase					)
														if is_first:
																		lowerCAmelCase  =				text[1:]

										lowerCAmelCase  =				self.sp_model.encode(lowerCAmelCase						,						out_type=lowerCAmelCase					)

										if not self.legacy and not is_first and not text.startswith(""" """					) and tokens[0].startswith(lowerCAmelCase					):
														lowerCAmelCase  =				([tokens[0][1:]] if len(tokens[0]					) > 1 else []) + tokens[1:]
										return tokens


						def   __lowercase (							self				:			List[str]						,						lowerCAmelCase				:			Optional[Any]					):
										if token.startswith("""<extra_id_"""					):
														lowerCAmelCase  =				re.match(R"""<extra_id_(\d+)>"""						,						lowerCAmelCase					)
														lowerCAmelCase  =				int(match.group(1					)					)
														return self.vocab_size - num - 1
										return self.sp_model.piece_to_id(lowerCAmelCase					)


						def   __lowercase (							self				:			Any						,						lowerCAmelCase				:			List[Any]					):
										if index < self.sp_model.get_piece_size():
														lowerCAmelCase  =				self.sp_model.IdToPiece(lowerCAmelCase					)
										else:
														lowerCAmelCase  =				f'''<extra_id_{self.vocab_size - 1 - index}>'''
										return token


						def   __lowercase (							self				:			Optional[Any]						,						lowerCAmelCase				:			Any					):
										lowerCAmelCase  =				[]
										lowerCAmelCase  =				""""""
										lowerCAmelCase  =				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
																		lowerCAmelCase  =				True
																		lowerCAmelCase  =				[]
														else:
																		current_sub_tokens.append(lowerCAmelCase					)
																		lowerCAmelCase  =				False
										out_string += self.sp_model.decode(lowerCAmelCase					)
										return out_string.strip()




						def   __lowercase (							self				:			Union[str, Any]						,						lowerCAmelCase				:			str						,						lowerCAmelCase				:			Optional[str] = None					):
										if not os.path.isdir(lowerCAmelCase					):
														logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
														return
										lowerCAmelCase  =				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:
																		lowerCAmelCase  =				self.sp_model.serialized_model_proto()
																		fi.write(lowerCAmelCase					)

										return (out_vocab_file,)











"""simple docstring"""







import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


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






@require_sentencepiece
@require_tokenizers
class       SCREAMING_SNAKE_CASE__					(					_a						,				unittest.TestCase					):
						_a    						=						XGLMTokenizer
						_a    						=						XGLMTokenizerFast
						_a    						=						True
						_a    						=						True


						def   __lowercase (							self				:			Union[str, Any]					):
										super().setUp()

										# We have a SentencePiece fixture for testing
										lowerCAmelCase  =				XGLMTokenizer(lowerCAmelCase						,						keep_accents=lowerCAmelCase					)
										tokenizer.save_pretrained(self.tmpdirname					)


						def   __lowercase (							self				:			Union[str, Any]					):
										lowerCAmelCase  =				"""<pad>"""
										lowerCAmelCase  =				1

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


						def   __lowercase (							self				:			List[str]					):
										lowerCAmelCase  =				list(self.get_tokenizer().get_vocab().keys()					)

										self.assertEqual(vocab_keys[0]						,						"""<s>"""					)
										self.assertEqual(vocab_keys[1]						,						"""<pad>"""					)
										self.assertEqual(len(lowerCAmelCase					)						,						1008					)


						def   __lowercase (							self				:			Optional[int]					):
										self.assertEqual(self.get_tokenizer().vocab_size						,						1008					)


						def   __lowercase (							self				:			int					):
										lowerCAmelCase  =				XGLMTokenizer(lowerCAmelCase						,						keep_accents=lowerCAmelCase					)

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

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(lowerCAmelCase					)						,						[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]						,						)

										lowerCAmelCase  =				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""",
										        """.""",
										    ]						,						)
										lowerCAmelCase  =				tokenizer.convert_tokens_to_ids(lowerCAmelCase					)
										self.assertListEqual(
										    lowerCAmelCase						,						[
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										    ]						,						)

										lowerCAmelCase  =				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   __lowercase (							self				:			Optional[Any]					):
										return XGLMTokenizer.from_pretrained("""facebook/xglm-564M"""					)


						def   __lowercase (							self				:			List[str]					):
										with tempfile.NamedTemporaryFile() as f:
														shutil.copyfile(lowerCAmelCase						,						f.name					)
														lowerCAmelCase  =				XGLMTokenizer(f.name						,						keep_accents=lowerCAmelCase					)
														lowerCAmelCase  =				pickle.dumps(lowerCAmelCase					)
										pickle.loads(lowerCAmelCase					)


						def   __lowercase (							self				:			Optional[int]					):
										if not self.test_rust_tokenizer:
														return

										lowerCAmelCase  =				self.get_tokenizer()
										lowerCAmelCase  =				self.get_rust_tokenizer()

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

										lowerCAmelCase  =				tokenizer.tokenize(lowerCAmelCase					)
										lowerCAmelCase  =				rust_tokenizer.tokenize(lowerCAmelCase					)
										self.assertListEqual(lowerCAmelCase						,						lowerCAmelCase					)

										lowerCAmelCase  =				tokenizer.encode(lowerCAmelCase						,						add_special_tokens=lowerCAmelCase					)
										lowerCAmelCase  =				rust_tokenizer.encode(lowerCAmelCase						,						add_special_tokens=lowerCAmelCase					)
										self.assertListEqual(lowerCAmelCase						,						lowerCAmelCase					)

										lowerCAmelCase  =				self.get_rust_tokenizer()
										lowerCAmelCase  =				tokenizer.encode(lowerCAmelCase					)
										lowerCAmelCase  =				rust_tokenizer.encode(lowerCAmelCase					)
										self.assertListEqual(lowerCAmelCase						,						lowerCAmelCase					)


						@slow
						def   __lowercase (							self				:			Union[str, Any]					):
										lowerCAmelCase  =				"""Hello World!"""
										lowerCAmelCase  =				[2, 3_1227, 4447, 35]

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


						@slow
						def   __lowercase (							self				:			str					):
										lowerCAmelCase  =				(
										    """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
										lowerCAmelCase  =				[2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 7_1630, 2_8085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 1_3675, 377, 652, 7580, 1_0341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 20_2277, 1_7892, 33, 60, 87, 4, 3234, 157, 61, 2667, 5_2376, 19, 88, 23, 735]
										# fmt: on

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




						@slow
						def   __lowercase (							self				:			str					):
										# fmt: off
										lowerCAmelCase  =				{
										    """input_ids""": [[2, 10_8825, 1163, 15, 8_8010, 473, 1_5898, 157, 1_3672, 1857, 312, 8, 23_8021, 1163, 53, 1_3672, 1857, 312, 8, 5_3283, 18_2396, 8, 1_8566, 16, 3_6733, 4101, 8, 230, 24_4017, 12_2553, 7, 15, 13_2597, 4, 293, 1_2511, 7610, 4, 3414, 13_2597, 9, 4, 3_2361, 362, 4, 734, 2_8512, 3_2569, 18, 4, 3_2361, 2_6096, 1_4982, 73, 1_8715, 2_1433, 23_5261, 15, 492, 1_2427, 16, 53, 1_8715, 2_1433, 6_5454, 15, 2_3659, 563, 16, 278, 597, 2843, 595, 7931, 18_2396, 6_4186, 22, 886, 595, 13_2981, 53, 2_5540, 3449, 4_3982, 3_9901, 5951, 878, 330, 4, 2_7694, 8_0269, 312, 53, 6517, 1_1780, 611, 2_0408, 5], [2, 6, 13_2597, 67, 4_2897, 33, 592, 8, 16_3729, 2_5540, 361, 13_6997, 10_9514, 17_3230, 7, 501, 60, 10_2913, 196, 5631, 235, 6_3243, 473, 6, 23_1757, 74, 5277, 7905, 53, 3095, 3_7317, 22, 454, 18_3874, 5], [2, 268, 3_1298, 4_6530, 6, 13_2935, 4_3831, 7, 597, 32, 24, 3688, 9865, 5]],
										    """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, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
										}  # noqa: E501
										# fmt: on

										self.tokenizer_integration_test_util(
										    expected_encoding=lowerCAmelCase						,						model_name="""facebook/xglm-564M"""						,						padding=lowerCAmelCase						,						)





