

import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 	A_		(						__snake_case      ,							unittest.TestCase    ):
							_UpperCAmelCase   :  int										=				LongformerTokenizer
							_UpperCAmelCase   :  Union[str, Any]										=				True
							_UpperCAmelCase   :  List[str]										=				LongformerTokenizerFast
							_UpperCAmelCase   :  Tuple										=				True
							def    lowerCAmelCase					(		self		:      Optional[Any]):
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								__lowerCamelCase    :    List[Any] 	=			[
								    '''l''',
								    '''o''',
								    '''w''',
								    '''e''',
								    '''r''',
								    '''s''',
								    '''t''',
								    '''i''',
								    '''d''',
								    '''n''',
								    '''\u0120''',
								    '''\u0120l''',
								    '''\u0120n''',
								    '''\u0120lo''',
								    '''\u0120low''',
								    '''er''',
								    '''\u0120lowest''',
								    '''\u0120newer''',
								    '''\u0120wider''',
								    '''<unk>''',
								]
								__lowerCamelCase    :    Union[str, Any] 	=			dict(zip(a_       ,range(len(a_))))
								__lowerCamelCase    :    List[str] 	=			['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
								__lowerCamelCase    :    List[Any] 	=			{'''unk_token''': '''<unk>'''}

								__lowerCamelCase    :    Any 	=			os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES['vocab_file'])
								__lowerCamelCase    :    int 	=			os.path.join(self.tmpdirname       ,VOCAB_FILES_NAMES['merges_file'])
								with open(self.vocab_file       ,'w'       ,encoding='utf-8') as fp:
									fp.write(json.dumps(a_) + '\n')
								with open(self.merges_file       ,'w'       ,encoding='utf-8') as fp:
									fp.write('\n'.join(a_))
							def    lowerCAmelCase					(		self		:      Tuple       ,**SCREAMING_SNAKE_CASE__		:      Dict):
								kwargs.update(self.special_tokens_map)
								return self.tokenizer_class.from_pretrained(self.tmpdirname       ,**a_)
							def    lowerCAmelCase					(		self		:      Dict       ,**SCREAMING_SNAKE_CASE__		:      int):
								kwargs.update(self.special_tokens_map)
								return self.rust_tokenizer_class.from_pretrained(self.tmpdirname       ,**a_)
							def    lowerCAmelCase					(		self		:      List[str]       ,SCREAMING_SNAKE_CASE__		:      Any):
								__lowerCamelCase    :    str 	=			'''lower newer'''
								__lowerCamelCase    :    int 	=			'''lower newer'''
								return input_text, output_text
							def    lowerCAmelCase					(		self		:      str):
								__lowerCamelCase    :    Dict 	=			self.tokenizer_class(self.vocab_file       ,self.merges_file       ,**self.special_tokens_map)
								__lowerCamelCase    :    Any 	=			'''lower newer'''
								__lowerCamelCase    :    Optional[Any] 	=			['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
								__lowerCamelCase    :    List[str] 	=			tokenizer.tokenize(a_)  # , add_prefix_space=True)
								self.assertListEqual(a_       ,a_)

								__lowerCamelCase    :    List[str] 	=			tokens + [tokenizer.unk_token]
								__lowerCamelCase    :    int 	=			[0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(a_)       ,a_)
							def    lowerCAmelCase					(		self		:      Optional[int]):
								__lowerCamelCase    :    int 	=			self.get_tokenizer()

								self.assertListEqual(tokenizer.encode('Hello world!'       ,add_special_tokens=a_)       ,[0, 3_1_4_1_4, 2_3_2, 3_2_8, 2])
								self.assertListEqual(
								    tokenizer.encode('Hello world! cécé herlolip 418'       ,add_special_tokens=a_)       ,[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]       ,)
							@slow
							def    lowerCAmelCase					(		self		:      List[str]):
								__lowerCamelCase    :    Dict 	=			self.tokenizer_class.from_pretrained('allenai/longformer-base-4096')

								__lowerCamelCase    :    List[Any] 	=			tokenizer.encode('sequence builders'       ,add_special_tokens=a_)
								__lowerCamelCase    :    Any 	=			tokenizer.encode('multi-sequence build'       ,add_special_tokens=a_)

								__lowerCamelCase    :    int 	=			tokenizer.encode(
								    'sequence builders'       ,add_special_tokens=a_       ,add_prefix_space=a_)
								__lowerCamelCase    :    int 	=			tokenizer.encode(
								    'sequence builders'       ,'multi-sequence build'       ,add_special_tokens=a_       ,add_prefix_space=a_)

								__lowerCamelCase    :    Optional[int] 	=			tokenizer.build_inputs_with_special_tokens(a_)
								__lowerCamelCase    :    str 	=			tokenizer.build_inputs_with_special_tokens(a_       ,a_)

								assert encoded_sentence == encoded_text_from_decode
								assert encoded_pair == encoded_pair_from_decode
							def    lowerCAmelCase					(		self		:      Any):
								__lowerCamelCase    :    Optional[Any] 	=			self.get_tokenizer()

								__lowerCamelCase    :    Optional[int] 	=			'''Encode this sequence.'''
								__lowerCamelCase    :    int 	=			tokenizer.byte_encoder[''' '''.encode('utf-8')[0]]

								# Testing encoder arguments
								__lowerCamelCase    :    List[str] 	=			tokenizer.encode(a_       ,add_special_tokens=a_       ,add_prefix_space=a_)
								__lowerCamelCase    :    Dict 	=			tokenizer.convert_ids_to_tokens(encoded[0])[0]
								self.assertNotEqual(a_       ,a_)

								__lowerCamelCase    :    List[Any] 	=			tokenizer.encode(a_       ,add_special_tokens=a_       ,add_prefix_space=a_)
								__lowerCamelCase    :    Dict 	=			tokenizer.convert_ids_to_tokens(encoded[0])[0]
								self.assertEqual(a_       ,a_)

								tokenizer.add_special_tokens({'bos_token': '<s>'})
								__lowerCamelCase    :    Optional[int] 	=			tokenizer.encode(a_       ,add_special_tokens=a_)
								__lowerCamelCase    :    Optional[Any] 	=			tokenizer.convert_ids_to_tokens(encoded[1])[0]
								self.assertNotEqual(a_       ,a_)

								# Testing spaces after special tokens
								__lowerCamelCase    :    List[str] 	=			'''<mask>'''
								tokenizer.add_special_tokens(
								    {'mask_token': AddedToken(a_       ,lstrip=a_       ,rstrip=a_)})  # mask token has a left space
								__lowerCamelCase    :    Tuple 	=			tokenizer.convert_tokens_to_ids(a_)

								__lowerCamelCase    :    int 	=			'''Encode <mask> sequence'''
								__lowerCamelCase    :    Optional[int] 	=			'''Encode <mask>sequence'''

								__lowerCamelCase    :    str 	=			tokenizer.encode(a_)
								__lowerCamelCase    :    Any 	=			encoded.index(a_)
								__lowerCamelCase    :    Optional[Any] 	=			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
								self.assertEqual(a_       ,a_)

								__lowerCamelCase    :    Optional[int] 	=			tokenizer.encode(a_)
								__lowerCamelCase    :    Optional[Any] 	=			encoded.index(a_)
								__lowerCamelCase    :    int 	=			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
								self.assertNotEqual(a_       ,a_)
							def    lowerCAmelCase					(		self		:      int):
								pass
							def    lowerCAmelCase					(		self		:      int):

								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"):
										__lowerCamelCase    :    List[Any] 	=			self.rust_tokenizer_class.from_pretrained(a_       ,**a_)
										__lowerCamelCase    :    str 	=			self.tokenizer_class.from_pretrained(a_       ,**a_)
										__lowerCamelCase    :    Tuple 	=			'''A, <mask> AllenNLP sentence.'''
										__lowerCamelCase    :    Union[str, Any] 	=			tokenizer_r.encode_plus(a_       ,add_special_tokens=a_       ,return_token_type_ids=a_)
										__lowerCamelCase    :    str 	=			tokenizer_p.encode_plus(a_       ,add_special_tokens=a_       ,return_token_type_ids=a_)

										# token_type_ids should put 0 everywhere
										self.assertEqual(sum(tokens_r['token_type_ids'])       ,sum(tokens_p['token_type_ids']))

										# attention_mask should put 1 everywhere, so sum over length should be 1
										self.assertEqual(
										    sum(tokens_r['attention_mask']) / len(tokens_r['attention_mask'])       ,sum(tokens_p['attention_mask']) / len(tokens_p['attention_mask'])       ,)

										__lowerCamelCase    :    Any 	=			tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'])
										__lowerCamelCase    :    Optional[Any] 	=			tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids'])

										# Rust correctly handles the space before the mask while python doesnt
										self.assertSequenceEqual(tokens_p['input_ids']       ,[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])
										self.assertSequenceEqual(tokens_r['input_ids']       ,[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2])

										self.assertSequenceEqual(
										    a_       ,['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])
										self.assertSequenceEqual(
										    a_       ,['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])
							def    lowerCAmelCase					(		self		:      str):

								for trim_offsets, add_prefix_space in itertools.product([True, False]       ,repeat=2):
									__lowerCamelCase    :    Union[str, Any] 	=			self.rust_tokenizer_class.from_pretrained(
									    self.tmpdirname       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)

									__lowerCamelCase    :    Dict 	=			json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
									__lowerCamelCase    :    int 	=			json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__())

									self.assertEqual(pre_tokenizer_state['add_prefix_space']       ,a_)

									self.assertEqual(post_processor_state['add_prefix_space']       ,a_)
									self.assertEqual(post_processor_state['trim_offsets']       ,a_)


							def    lowerCAmelCase					(		self		:      Tuple):

								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"):
										__lowerCamelCase    :    List[Any] 	=			'''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
										__lowerCamelCase    :    List[str] 	=			F"{text_of_1_token} {text_of_1_token}"

										__lowerCamelCase    :    str 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    List[Any] 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(len(a_) + 1, len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    List[Any] 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    Any 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(len(a_) + 1, len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    int 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    Optional[int] 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(len(a_), len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    Any 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    Optional[int] 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(len(a_), len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    List[Any] 	=			F" {text}"

										# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
										#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
										# )
										# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
										# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
										# self.assertEqual(
										#     encoding.offset_mapping[1],
										#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
										# )

										__lowerCamelCase    :    List[str] 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    Tuple 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(1, 1 + len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(1 + len(a_) + 1, 1 + len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    Union[str, Any] 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    Optional[Any] 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, 1 + len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(1 + len(a_), 1 + len(a_) + 1 + len(a_))       ,)

										__lowerCamelCase    :    Tuple 	=			self.rust_tokenizer_class.from_pretrained(
										    a_       ,use_fast=a_       ,add_prefix_space=a_       ,trim_offsets=a_)
										__lowerCamelCase    :    int 	=			tokenizer_r(a_       ,return_offsets_mapping=a_       ,add_special_tokens=a_)
										self.assertEqual(encoding.offset_mapping[0]       ,(0, 1 + len(a_)))
										self.assertEqual(
										    encoding.offset_mapping[1]       ,(1 + len(a_), 1 + len(a_) + 1 + len(a_))       ,)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a		={
    """configuration_bigbird_pegasus""": [
        """BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BigBirdPegasusConfig""",
        """BigBirdPegasusOnnxConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					a		=[
					    """BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """BigBirdPegasusForCausalLM""",
					    """BigBirdPegasusForConditionalGeneration""",
					    """BigBirdPegasusForQuestionAnswering""",
					    """BigBirdPegasusForSequenceClassification""",
					    """BigBirdPegasusModel""",
					    """BigBirdPegasusPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_bigbird_pegasus import (
					    BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    BigBirdPegasusConfig,
					    BigBirdPegasusOnnxConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_bigbird_pegasus import (
										    BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BigBirdPegasusForCausalLM,
										    BigBirdPegasusForConditionalGeneration,
										    BigBirdPegasusForQuestionAnswering,
										    BigBirdPegasusForSequenceClassification,
										    BigBirdPegasusModel,
										    BigBirdPegasusPreTrainedModel,
										)


else:
					import sys

					a		=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




