



'''simple docstring'''

import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_A				:    Optional[Any]     						=logging.get_logger(__name__)


_A				:    int     						={'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

_A				:    List[str]     						={
    '''vocab_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
    },
}

_A				:    Optional[Any]     						={
    '''allenai/longformer-base-4096''': 4_0_9_6,
    '''allenai/longformer-large-4096''': 4_0_9_6,
    '''allenai/longformer-large-4096-finetuned-triviaqa''': 4_0_9_6,
    '''allenai/longformer-base-4096-extra.pos.embd.only''': 4_0_9_6,
    '''allenai/longformer-large-4096-extra.pos.embd.only''': 4_0_9_6,
}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 						__UpperCamelCase				(							) ->			List[str]:

	'''simple docstring'''





	_lowercase					:       Tuple       =		(
	    list(range(ord('!'					),				ord('~'					) + 1					)					) + list(range(ord('¡'					),				ord('¬'					) + 1					)					) + list(range(ord('®'					),				ord('ÿ'					) + 1					)					)
	)
	_lowercase					:       List[str]       =		bs[:]
	_lowercase					:       Any       =		0
	for b in range(2**8					):
		if b not in bs:
			bs.append(__A					)
			cs.append(2**8 + n					)
			n += 1
	_lowercase					:       Tuple       =		[chr(__A					) for n in cs]
	return dict(zip(__A,				__A					)					)







def 						__UpperCamelCase				(							_lowercase					) ->			List[Any]:

	'''simple docstring'''





	_lowercase					:       List[str]       =		set()
	_lowercase					:       int       =		word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)					)
		_lowercase					:       Union[str, Any]       =		char
	return pairs






class 		lowerCamelCase__      (						_snake_case     ):




					'''simple docstring'''



					A_						    =						VOCAB_FILES_NAMES
					A_						    =						PRETRAINED_VOCAB_FILES_MAP
					A_						    =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A_						    =						["""input_ids""", """attention_mask"""]




					def __init__(  self				:	List[str]     ,  UpperCamelCase_				:	Any     ,  UpperCamelCase_				:	str     ,  UpperCamelCase_				:	Tuple="replace"     ,  UpperCamelCase_				:	str="<s>"     ,  UpperCamelCase_				:	int="</s>"     ,  UpperCamelCase_				:	int="</s>"     ,  UpperCamelCase_				:	Dict="<s>"     ,  UpperCamelCase_				:	Dict="<unk>"     ,  UpperCamelCase_				:	Optional[Any]="<pad>"     ,  UpperCamelCase_				:	int="<mask>"     ,  UpperCamelCase_				:	str=False     ,  **UpperCamelCase_				:	List[Any]     ,  )  ->       List[str]:



						'''simple docstring'''





						_lowercase					:       Dict       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else bos_token
						_lowercase					:       Any       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else eos_token
						_lowercase					:       Dict       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else sep_token
						_lowercase					:       int       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else cls_token
						_lowercase					:       Tuple       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else unk_token
						_lowercase					:       Union[str, Any]       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else pad_token

						# Mask token behave like a normal word, i.e. include the space before it
						_lowercase					:       Any       =		AddedToken(lowerCAmelCase__     ,  lstrip=lowerCAmelCase__     ,  rstrip=lowerCAmelCase__					) if isinstance(lowerCAmelCase__     ,  lowerCAmelCase__					) else mask_token

						super().__init__(
						    errors=lowerCAmelCase__     ,  bos_token=lowerCAmelCase__     ,  eos_token=lowerCAmelCase__     ,  unk_token=lowerCAmelCase__     ,  sep_token=lowerCAmelCase__     ,  cls_token=lowerCAmelCase__     ,  pad_token=lowerCAmelCase__     ,  mask_token=lowerCAmelCase__     ,  add_prefix_space=lowerCAmelCase__     ,  **lowerCAmelCase__     ,  )

						with open(lowerCAmelCase__     ,  encoding='utf-8'					) as vocab_handle:
							_lowercase					:       Optional[Any]       =		json.load(lowerCAmelCase__					)
						_lowercase					:       str       =		{v: k for k, v in self.encoder.items()}
						_lowercase					:       Tuple       =		errors  # how to handle errors in decoding
						_lowercase					:       Any       =		bytes_to_unicode()
						_lowercase					:       Optional[int]       =		{v: k for k, v in self.byte_encoder.items()}
						with open(lowerCAmelCase__     ,  encoding='utf-8'					) as merges_handle:
							_lowercase					:       Optional[Any]       =		merges_handle.read().split('\n'					)[1:-1]
						_lowercase					:       List[Any]       =		[tuple(merge.split()					) for merge in bpe_merges]
						_lowercase					:       Tuple       =		dict(zip(lowerCAmelCase__     ,  range(len(lowerCAmelCase__					)					)					)					)
						_lowercase					:       List[str]       =		{}
						_lowercase					:       List[Any]       =		add_prefix_space

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						_lowercase					:       str       =		re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'					)




					@property
					def 						__UpperCAmelCase     (  self				:	List[Any]					)  ->       Optional[int]:



						'''simple docstring'''





						return len(self.encoder					)




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



						'''simple docstring'''





						return dict(self.encoder     ,  **self.added_tokens_encoder					)




					def 						__UpperCAmelCase     (  self				:	List[str]     ,  UpperCamelCase_				:	Optional[int]					)  ->       int:



						'''simple docstring'''





						if token in self.cache:
							return self.cache[token]
						_lowercase					:       Any       =		tuple(lowerCAmelCase__					)
						_lowercase					:       str       =		get_pairs(lowerCAmelCase__					)

						if not pairs:
							return token

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

								if word[i] == first and i < len(lowerCAmelCase__					) - 1 and word[i + 1] == second:
									new_word.append(first + second					)
									i += 2
								else:
									new_word.append(word[i]					)
									i += 1
							_lowercase					:       Optional[int]       =		tuple(lowerCAmelCase__					)
							_lowercase					:       List[str]       =		new_word
							if len(lowerCAmelCase__					) == 1:
								break
							else:
								_lowercase					:       List[Any]       =		get_pairs(lowerCAmelCase__					)
						_lowercase					:       List[Any]       =		' '.join(lowerCAmelCase__					)
						_lowercase					:       List[str]       =		word
						return word




					def 						__UpperCAmelCase     (  self				:	List[Any]     ,  UpperCamelCase_				:	List[str]					)  ->       str:



						'''simple docstring'''





						_lowercase					:       int       =		[]
						for token in re.findall(self.pat     ,  lowerCAmelCase__					):
							_lowercase					:       Any       =		''.join(
							    self.byte_encoder[b] for b in token.encode('utf-8'					)					)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
							bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCAmelCase__					).split(' '					)					)
						return bpe_tokens




					def 						__UpperCAmelCase     (  self				:	str     ,  UpperCamelCase_				:	List[str]					)  ->       str:



						'''simple docstring'''





						return self.encoder.get(lowerCAmelCase__     ,  self.encoder.get(self.unk_token					)					)




					def 						__UpperCAmelCase     (  self				:	Tuple     ,  UpperCamelCase_				:	Dict					)  ->       Tuple:



						'''simple docstring'''





						return self.decoder.get(lowerCAmelCase__					)




					def 						__UpperCAmelCase     (  self				:	List[str]     ,  UpperCamelCase_				:	Dict					)  ->       Tuple:



						'''simple docstring'''





						_lowercase					:       str       =		''.join(lowerCAmelCase__					)
						_lowercase					:       Union[str, Any]       =		bytearray([self.byte_decoder[c] for c in text]					).decode('utf-8'     ,  errors=self.errors					)
						return text




					def 						__UpperCAmelCase     (  self				:	str     ,  UpperCamelCase_				:	str     ,  UpperCamelCase_				:	Optional[str] = None					)  ->       Tuple[str]:



						'''simple docstring'''





						if not os.path.isdir(lowerCAmelCase__					):
							logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
							return
						_lowercase					:       str       =		os.path.join(
						    lowerCAmelCase__     ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)
						_lowercase					:       Dict       =		os.path.join(
						    lowerCAmelCase__     ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']					)

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

						_lowercase					:       int       =		0
						with open(lowerCAmelCase__     ,  '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 UpperCamelCase_					: 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					:       Union[str, Any]       =		token_index
								writer.write(' '.join(lowerCAmelCase__					) + '\n'					)
								index += 1

						return vocab_file, merge_file




					def 						__UpperCAmelCase     (  self				:	Any     ,  UpperCamelCase_				:	List[int]     ,  UpperCamelCase_				:	Optional[List[int]] = None					)  ->       List[int]:



						'''simple docstring'''





						if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						_lowercase					:       Dict       =		[self.cls_token_id]
						_lowercase					:       Dict       =		[self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep




					def 						__UpperCAmelCase     (  self				:	str     ,  UpperCamelCase_				:	List[int]     ,  UpperCamelCase_				:	Optional[List[int]] = None     ,  UpperCamelCase_				:	bool = False					)  ->       List[int]:



						'''simple docstring'''





						if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowerCAmelCase__     ,  token_ids_a=lowerCAmelCase__     ,  already_has_special_tokens=lowerCAmelCase__					)

						if token_ids_a is None:
							return [1] + ([0] * len(lowerCAmelCase__					)) + [1]
						return [1] + ([0] * len(lowerCAmelCase__					)) + [1, 1] + ([0] * len(lowerCAmelCase__					)) + [1]




					def 						__UpperCAmelCase     (  self				:	Optional[int]     ,  UpperCamelCase_				:	List[int]     ,  UpperCamelCase_				:	Optional[List[int]] = None					)  ->       List[int]:



						'''simple docstring'''





						_lowercase					:       Tuple       =		[self.sep_token_id]
						_lowercase					:       int       =		[self.cls_token_id]

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




					def 						__UpperCAmelCase     (  self				:	str     ,  UpperCamelCase_				:	Optional[int]     ,  UpperCamelCase_				:	Optional[int]=False     ,  **UpperCamelCase_				:	List[Any]					)  ->       str:



						'''simple docstring'''





						_lowercase					:       str       =		kwargs.pop('add_prefix_space'     ,  self.add_prefix_space					)
						if (is_split_into_words or add_prefix_space) and (len(lowerCAmelCase__					) > 0 and not text[0].isspace()):
							_lowercase					:       Dict       =		' ' + text
						return (text, kwargs)





'''simple docstring'''

import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
		import jax.numpy as jnp

		from transformers.models.roformer.modeling_flax_roformer import (
		    FlaxRoFormerForMaskedLM,
		    FlaxRoFormerForMultipleChoice,
		    FlaxRoFormerForQuestionAnswering,
		    FlaxRoFormerForSequenceClassification,
		    FlaxRoFormerForTokenClassification,
		    FlaxRoFormerModel,
		)



class 		lowerCamelCase__      (						unittest.TestCase     ):




					'''simple docstring'''



					def __init__(  self				:	Dict     ,  UpperCamelCase_				:	Union[str, Any]     ,  UpperCamelCase_				:	List[str]=13     ,  UpperCamelCase_				:	Union[str, Any]=7     ,  UpperCamelCase_				:	Union[str, Any]=True     ,  UpperCamelCase_				:	Any=True     ,  UpperCamelCase_				:	Dict=True     ,  UpperCamelCase_				:	List[str]=True     ,  UpperCamelCase_				:	int=99     ,  UpperCamelCase_				:	Tuple=32     ,  UpperCamelCase_				:	List[str]=5     ,  UpperCamelCase_				:	Dict=4     ,  UpperCamelCase_				:	Tuple=37     ,  UpperCamelCase_				:	int="gelu"     ,  UpperCamelCase_				:	int=0.1     ,  UpperCamelCase_				:	Dict=0.1     ,  UpperCamelCase_				:	Any=512     ,  UpperCamelCase_				:	List[Any]=16     ,  UpperCamelCase_				:	Optional[int]=2     ,  UpperCamelCase_				:	Tuple=0.02     ,  UpperCamelCase_				:	Union[str, Any]=4     ,  )  ->       Tuple:



						'''simple docstring'''





						_lowercase					:       int       =		parent
						_lowercase					:       str       =		batch_size
						_lowercase					:       List[str]       =		seq_length
						_lowercase					:       Dict       =		is_training
						_lowercase					:       Optional[int]       =		use_attention_mask
						_lowercase					:       List[Any]       =		use_token_type_ids
						_lowercase					:       Union[str, Any]       =		use_labels
						_lowercase					:       Dict       =		vocab_size
						_lowercase					:       List[Any]       =		hidden_size
						_lowercase					:       Any       =		num_hidden_layers
						_lowercase					:       int       =		num_attention_heads
						_lowercase					:       Optional[int]       =		intermediate_size
						_lowercase					:       Any       =		hidden_act
						_lowercase					:       List[str]       =		hidden_dropout_prob
						_lowercase					:       Union[str, Any]       =		attention_probs_dropout_prob
						_lowercase					:       Optional[int]       =		max_position_embeddings
						_lowercase					:       int       =		type_vocab_size
						_lowercase					:       Any       =		type_sequence_label_size
						_lowercase					:       Any       =		initializer_range
						_lowercase					:       str       =		num_choices




					def 						__UpperCAmelCase     (  self				:	str					)  ->       int:



						'''simple docstring'''





						_lowercase					:       Optional[int]       =		ids_tensor([self.batch_size, self.seq_length]     ,  self.vocab_size					)

						_lowercase					:       int       =		None
						if self.use_attention_mask:
							_lowercase					:       Optional[int]       =		random_attention_mask([self.batch_size, self.seq_length]					)

						_lowercase					:       Any       =		None
						if self.use_token_type_ids:
							_lowercase					:       Optional[Any]       =		ids_tensor([self.batch_size, self.seq_length]     ,  self.type_vocab_size					)

						_lowercase					:       str       =		RoFormerConfig(
						    vocab_size=self.vocab_size     ,  hidden_size=self.hidden_size     ,  num_hidden_layers=self.num_hidden_layers     ,  num_attention_heads=self.num_attention_heads     ,  intermediate_size=self.intermediate_size     ,  hidden_act=self.hidden_act     ,  hidden_dropout_prob=self.hidden_dropout_prob     ,  attention_probs_dropout_prob=self.attention_probs_dropout_prob     ,  max_position_embeddings=self.max_position_embeddings     ,  type_vocab_size=self.type_vocab_size     ,  is_decoder=UpperCamelCase_     ,  initializer_range=self.initializer_range     ,  )

						return config, input_ids, token_type_ids, attention_mask




					def 						__UpperCAmelCase     (  self				:	List[Any]					)  ->       int:



						'''simple docstring'''





						_lowercase					:       Dict       =		self.prepare_config_and_inputs()
						_lowercase  ,    _lowercase  ,    _lowercase  ,    _lowercase					:       Union[str, Any]       =		config_and_inputs
						_lowercase					:       Optional[int]       =		{'input_ids': input_ids, 'token_type_ids': token_type_ids, 'attention_mask': attention_mask}
						return config, inputs_dict






@require_flax
class 		lowerCamelCase__      (						A	,   unittest.TestCase     ):




					'''simple docstring'''



					A_						    =						True

					A_						    =						(
					    (
					        FlaxRoFormerModel,
					        FlaxRoFormerForMaskedLM,
					        FlaxRoFormerForSequenceClassification,
					        FlaxRoFormerForTokenClassification,
					        FlaxRoFormerForMultipleChoice,
					        FlaxRoFormerForQuestionAnswering,
					    )
					    if is_flax_available()
					    else ()
					)




					def 						__UpperCAmelCase     (  self				:	str					)  ->       int:



						'''simple docstring'''





						_lowercase					:       Tuple       =		FlaxRoFormerModelTester(self					)




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



						'''simple docstring'''





						for model_class_name in self.all_model_classes:
							_lowercase					:       Optional[int]       =		model_class_name.from_pretrained('junnyu/roformer_chinese_small'     ,  from_pt=UpperCamelCase_					)
							_lowercase					:       str       =		model(np.ones((1, 1)					)					)
							self.assertIsNotNone(UpperCamelCase_					)






@require_flax
class 		lowerCamelCase__      (						unittest.TestCase     ):




					'''simple docstring'''



					@slow
					def 						__UpperCAmelCase     (  self				:	List[str]					)  ->       List[Any]:



						'''simple docstring'''





						_lowercase					:       Dict       =		FlaxRoFormerForMaskedLM.from_pretrained('junnyu/roformer_chinese_base'					)
						_lowercase					:       Any       =		jnp.array([[0, 1, 2, 3, 4, 5]]					)
						_lowercase					:       int       =		model(UpperCamelCase_					)[0]

						_lowercase					:       Union[str, Any]       =		5_0000

						_lowercase					:       str       =		(1, 6, vocab_size)
						self.assertEqual(output.shape     ,  UpperCamelCase_					)

						_lowercase					:       int       =		jnp.array(
						    [[[-0.12_05, -1.02_65, 0.29_22], [-1.51_34, 0.19_74, 0.15_19], [-5.01_35, -3.90_03, -0.84_04]]]					)

						self.assertTrue(jnp.allclose(output[:, :3, :3]     ,  UpperCamelCase_     ,  atol=1E-4					)					)
