




"""simple docstring"""
import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a_				:    List[Any]										=     get_tests_dir('''fixtures/test_sentencepiece.model''')

@require_sentencepiece
class __lowercase(      lowercase__	,	unittest.TestCase				):




					'''simple docstring'''


					__a						:						Optional[int]     		= XLMProphetNetTokenizer
					__a						:						Union[str, Any]     		= False
					__a						:						Union[str, Any]     		= True
					def     snake_case_				(    self     ):
								super().setUp()

								# We have a SentencePiece fixture for testing
								__lowerCamelCase					:	int	       =				XLMProphetNetTokenizer(__a						,	keep_accents=__a     )
								tokenizer.save_pretrained(self.tmpdirname     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	List[Any]	       =				'[PAD]'
								__lowerCamelCase					:	Tuple	       =				0

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(__a     )						,	__a     )
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(__a     )						,	__a     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	List[str]	       =				list(self.get_tokenizer().get_vocab().keys()     )

								self.assertEqual(vocab_keys[0]						,	'[PAD]'     )
								self.assertEqual(vocab_keys[1]						,	'[CLS]'     )
								self.assertEqual(vocab_keys[-1]						,	'j'     )
								self.assertEqual(len(__a     )						,	1012     )
					def     snake_case_				(    self     ):
								self.assertEqual(self.get_tokenizer().vocab_size						,	1012     )
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	List[str]	       =				XLMProphetNetTokenizer(__a						,	keep_accents=__a     )

								__lowerCamelCase					:	List[str]	       =				tokenizer.tokenize('This is a test'     )
								self.assertListEqual(__a						,	['▁This', '▁is', '▁a', '▁t', 'est']     )

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

								__lowerCamelCase					:	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',
								        '.',
								    ]						,	)
								__lowerCamelCase					:	str	       =				tokenizer.convert_tokens_to_ids(__a     )
								self.assertListEqual(
								    __a						,	[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
								    ]						,	)

								__lowerCamelCase					:	List[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     snake_case_				(    self     ):
								return XLMProphetNetTokenizer.from_pretrained('microsoft/xprophetnet-large-wiki100-cased'     )
					@slow
					def     snake_case_				(    self     ):
								__lowerCamelCase					:	List[str]	       =				'Hello World!'
								__lowerCamelCase					:	Optional[int]	       =				[35389, 6672, 49, 2]
								self.assertListEqual(__a						,	self.big_tokenizer.encode(__a     )     )





					@slow
					def     snake_case_				(    self     ):
								# fmt: off
								__lowerCamelCase					:	Optional[int]	       =				{'input_ids': [[11073, 82783, 18, 26, 82783, 549, 51540, 248, 17209, 1301, 217, 20, 215186, 1325, 147, 17209, 1301, 217, 20, 56370, 53, 122020, 20, 16477, 27, 87355, 4548, 20, 4728, 78392, 17, 159969, 18, 26, 24491, 629, 15, 538, 22704, 5439, 15, 2788, 24491, 9885, 15, 43534, 605, 15, 814, 18403, 33200, 29, 15, 43534, 24458, 12410, 111, 24966, 83669, 9637, 144068, 26, 850, 22346, 27, 147, 24966, 83669, 83490, 26, 39113, 735, 27, 689, 656, 2800, 1339, 4600, 53, 122020, 115785, 34, 816, 1339, 46887, 18, 147, 53905, 1951, 42238, 41170, 17732, 834, 436, 15, 27523, 98733, 217, 147, 5542, 4981, 930, 17347, 16, 2], [20091, 629, 94, 82786, 58, 490, 20, 1528, 84, 53905, 344, 80592, 110128, 18822, 5267, 1306, 62, 152537, 308, 7997, 401, 124427, 549, 35442, 225, 109, 15055, 25748, 147, 7119, 43712, 34, 767, 135366, 18, 16, 2, 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], [592, 63784, 119466, 17, 147808, 88214, 18, 656, 81, 32, 3296, 10280, 16, 2, 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, 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, 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, 0, 0, 0, 0, 0], [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, 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=__a						,	model_name='microsoft/xprophetnet-large-wiki100-cased'						,	revision='1acad1643ddd54a44df6a1b797ada8373685d90e'						,	)









"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple

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


a_				:    Dict										=     logging.get_logger(__name__)


a_				:    List[Any]										=     {
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

a_				:    Tuple										=     {
    '''vocab_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'''
        ),
    },
    '''tokenizer_config_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'''
        ),
    },
    '''merges_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'''
        ),
    },
}

a_				:    Optional[Any]										=     '''</w>'''
a_				:    Dict										=     '''@@ '''





def 						UpperCAmelCase				(			A__:    Optional[Any]     )  ->     Optional[int]:
			__lowerCamelCase					:	Any	       =				set()
			__lowerCamelCase					:	Optional[int]	       =				word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)     )
						__lowerCamelCase					:	Optional[int]	       =				char
			return pairs


# Speech2Text2 has no max input length
a_				:    Union[str, Any]										=     {'''facebook/s2t-wav2vec2-large-en-de''': 10_24}






class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						List[str]     		= VOCAB_FILES_NAMES
					__a						:						Optional[int]     		= PRETRAINED_VOCAB_FILES_MAP
					__a						:						Union[str, Any]     		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__a						:						Dict     		= ['input_ids', 'attention_mask']
					def __init__(    self						,	__a						,	__a="<s>"						,	__a="<pad>"						,	__a="</s>"						,	__a="<unk>"						,	__a=False						,	__a=None						,	**__a						,	):
								super().__init__(
								    unk_token=__a						,	bos_token=__a						,	eos_token=__a						,	pad_token=__a						,	do_lower_case=__a						,	**__a						,	)

								__lowerCamelCase					:	List[Any]	       =				do_lower_case

								with open(__a						,	encoding='utf-8'     ) as vocab_handle:
											__lowerCamelCase					:	str	       =				json.load(__a     )
								__lowerCamelCase					:	int	       =				{v: k for k, v in self.encoder.items()}

								if merges_file is None:
											logger.info(f'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''     )

											__lowerCamelCase					:	str	       =				None
											__lowerCamelCase					:	Optional[int]	       =				None
								else:
											with open(__a						,	encoding='utf-8'     ) as merges_handle:
														__lowerCamelCase					:	Optional[int]	       =				merges_handle.read().split('\n'     )[:-1]

											__lowerCamelCase					:	List[str]	       =				[tuple(merge.split()[:2]     ) for merge in merges]
											__lowerCamelCase					:	Any	       =				dict(zip(__a						,	range(len(__a     )     )     )     )
											__lowerCamelCase					:	List[str]	       =				{}
					@property
					def     snake_case_				(    self     ):
								return len(self.decoder     )
					def     snake_case_				(    self     ):
								return dict(self.encoder						,	**self.added_tokens_encoder     )
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	Optional[Any]	       =				tuple(token[:-1]     ) + (token[-1] + BPE_TOKEN_MERGES,)
								if token in self.cache:
											return self.cache[token]
								__lowerCamelCase					:	Union[str, Any]	       =				get_pairs(__a     )

								if not pairs:
											return token

								while True:
											__lowerCamelCase					:	Dict	       =				min(__a						,	key=lambda __a     : self.bpe_ranks.get(__a						,	float('inf'     )     )     )
											if bigram not in self.bpe_ranks:
														break
											__lowerCamelCase       ,      __lowerCamelCase					:	Optional[Any]	       =				bigram
											__lowerCamelCase					:	Tuple	       =				[]
											__lowerCamelCase					:	Union[str, Any]	       =				0
											while i < len(__a     ):
														try:
																	__lowerCamelCase					:	Union[str, Any]	       =				word.index(__a						,	__a     )
														except ValueError:
																	new_word.extend(word[i:]     )
																	break
														else:
																	new_word.extend(word[i:j]     )
																	__lowerCamelCase					:	Any	       =				j

														if word[i] == first and i < len(__a     ) - 1 and word[i + 1] == second:
																	new_word.append(first + second     )
																	i += 2
														else:
																	new_word.append(word[i]     )
																	i += 1
											__lowerCamelCase					:	List[str]	       =				tuple(__a     )
											__lowerCamelCase					:	Any	       =				new_word
											if len(__a     ) == 1:
														break
											else:
														__lowerCamelCase					:	Tuple	       =				get_pairs(__a     )
								__lowerCamelCase					:	Optional[int]	       =				' '.join(__a     )
								if word == "\n  " + BPE_TOKEN_MERGES:
											__lowerCamelCase					:	str	       =				'\n' + BPE_TOKEN_MERGES

								if word.endswith(__a     ):
											__lowerCamelCase					:	Tuple	       =				word.replace(__a						,	''     )

								__lowerCamelCase					:	Optional[Any]	       =				word.replace(' '						,	__a     )
								__lowerCamelCase					:	Union[str, Any]	       =				word
								return word
					def     snake_case_				(    self						,	__a     ):

								if self.bpe_ranks is None:
											raise ValueError(
											    'This tokenizer was instantiated without a `merges.txt` file, so'
											    ' that it can only be used for decoding, not for encoding.'
											    'Make sure to provide `merges.txt` file at instantiation to enable '
											    'encoding.'     )

								if self.do_lower_case:
											__lowerCamelCase					:	Any	       =				text.lower()

								__lowerCamelCase					:	Union[str, Any]	       =				text.split()

								__lowerCamelCase					:	str	       =				[]
								for token in text:
											if token:
														split_tokens.extend(list(self.bpe(__a     ).split(' '     )     )     )

								return split_tokens
					def     snake_case_				(    self						,	__a     ):
								return self.encoder.get(__a						,	self.encoder.get(self.unk_token     )     )
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	int	       =				self.decoder.get(__a						,	self.unk_token     )
								return result
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	Any	       =				' '.join(__a     )

								# make sure @@ tokens are concatenated
								__lowerCamelCase					:	Union[str, Any]	       =				''.join(string.split(__a     )     )

								return string





					def     snake_case_				(    self						,	__a						,	__a = None     ):
								if not os.path.isdir(__a     ):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
											return
								__lowerCamelCase					:	int	       =				os.path.join(
								    __a						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
								__lowerCamelCase					:	Any	       =				os.path.join(
								    __a						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']     )

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

								__lowerCamelCase					:	Optional[int]	       =				0
								if self.bpe_ranks is None:
											return (vocab_file,)

								with open(__a						,	'w'						,	encoding='utf-8'     ) as writer:
											for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,	key=lambda __a     : kv[1]     ):
														if index != token_index:
																	logger.warning(
																	    f'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
																	    ' Please check that the tokenizer is not corrupted!'     )
																	__lowerCamelCase					:	Optional[int]	       =				token_index
														writer.write(' '.join(__a     ) + '\n'     )
														index += 1

								return (vocab_file, merges_file)



