




'''simple docstring'''

import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
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


a    :							Tuple										=    get_tests_dir('fixtures/test_sentencepiece_no_bos.model')






@require_sentencepiece
@require_tokenizers
class 		a							(  _lowerCamelCase  ,	unittest.TestCase	):
				snake_case_           =						PegasusTokenizer
				snake_case_           =						PegasusTokenizerFast
				snake_case_           =						True
				snake_case_           =						True


				def     A_					(						self       :   Optional[Any]   ):
									super().setUp()

									# We have a SentencePiece fixture for testing
									snake_case_		     =							PegasusTokenizer(lowercase_   )
									tokenizer.save_pretrained(self.tmpdirname   )


				@cached_property
				def     A_					(						self       :   int   ):
									return PegasusTokenizer.from_pretrained('''google/pegasus-large'''   )


				def     A_					(						self       :   List[str]			,							**lowercase_       :   Dict   ):
									return PegasusTokenizer.from_pretrained(self.tmpdirname			,							**lowercase_   )


				def     A_					(						self       :   List[str]			,							lowercase_       :   int   ):
									return ("This is a test", "This is a test")


				def     A_					(						self       :   Dict   ):
									snake_case_		     =							'''</s>'''
									snake_case_		     =							1

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


				def     A_					(						self       :   Any   ):
									snake_case_		     =							list(self.get_tokenizer().get_vocab().keys()   )

									self.assertEqual(vocab_keys[0]			,							'''<pad>'''   )
									self.assertEqual(vocab_keys[1]			,							'''</s>'''   )
									self.assertEqual(vocab_keys[-1]			,							'''v'''   )
									self.assertEqual(len(lowercase_   )			,							1103   )


				def     A_					(						self       :   int   ):
									self.assertEqual(self.get_tokenizer().vocab_size			,							1103   )


				def     A_					(						self       :   Tuple   ):
									snake_case_		     =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname   )
									snake_case_		     =							self.tokenizer_class.from_pretrained(self.tmpdirname   )
									snake_case_		     =							(
									    '''Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'''
									    ''' </s> <pad> <pad> <pad>'''
									)
									snake_case_		     =							rust_tokenizer([raw_input_str]			,							return_tensors=lowercase_			,							add_special_tokens=lowercase_   ).input_ids[0]
									snake_case_		     =							py_tokenizer([raw_input_str]			,							return_tensors=lowercase_			,							add_special_tokens=lowercase_   ).input_ids[0]
									self.assertListEqual(lowercase_			,							lowercase_   )


				def     A_					(						self       :   Any   ):
									snake_case_		     =							self._large_tokenizer
									# <mask_1> masks whole sentence while <mask_2> masks single word
									snake_case_		     =							'''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
									snake_case_		     =							[2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
									snake_case_		     =							tokenizer([raw_input_str]			,							return_tensors=lowercase_   ).input_ids[0]
									self.assertListEqual(lowercase_			,							lowercase_   )


				def     A_					(						self       :   Dict   ):
									snake_case_		     =							self._large_tokenizer
									# The tracebacks for the following asserts are **better** without messages or self.assertEqual
									assert tokenizer.vocab_size == 9_6103
									assert tokenizer.pad_token_id == 0
									assert tokenizer.eos_token_id == 1
									assert tokenizer.offset == 103
									assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
									assert tokenizer.unk_token == "<unk>"
									assert tokenizer.model_max_length == 1024
									snake_case_		     =							'''To ensure a smooth flow of bank resolutions.'''
									snake_case_		     =							[413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
									snake_case_		     =							tokenizer([raw_input_str]			,							return_tensors=lowercase_   ).input_ids[0]
									self.assertListEqual(lowercase_			,							lowercase_   )
									assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]   ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]


				@require_torch
				def     A_					(						self       :   Tuple   ):
									snake_case_		     =							['''This is going to be way too long.''' * 150, '''short example''']
									snake_case_		     =							['''not super long but more than 5 tokens''', '''tiny''']
									snake_case_		     =							self._large_tokenizer(lowercase_			,							padding=lowercase_			,							truncation=lowercase_			,							return_tensors='''pt'''   )
									snake_case_		     =							self._large_tokenizer(
									    text_target=lowercase_			,							max_length=5			,							padding=lowercase_			,							truncation=lowercase_			,							return_tensors='''pt'''   )

									assert batch.input_ids.shape == (2, 1024)
									assert batch.attention_mask.shape == (2, 1024)
									assert targets["input_ids"].shape == (2, 5)
									assert len(lowercase_   ) == 2  # input_ids, attention_mask.


				@slow
				def     A_					(						self       :   List[str]   ):
									# fmt: off
									snake_case_		     =							{'''input_ids''': [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 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], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 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]], '''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, 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, 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=lowercase_			,							model_name='''google/bigbird-pegasus-large-arxiv'''			,							revision='''ba85d0851d708441f91440d509690f1ab6353415'''			,							)







@require_sentencepiece
@require_tokenizers
class 		a							(  _lowerCamelCase  ,	unittest.TestCase	):
				snake_case_           =						PegasusTokenizer
				snake_case_           =						PegasusTokenizerFast
				snake_case_           =						True
				snake_case_           =						True


				def     A_					(						self       :   Dict   ):
									super().setUp()

									# We have a SentencePiece fixture for testing
									snake_case_		     =							PegasusTokenizer(lowercase_			,							offset=0			,							mask_token_sent=lowercase_			,							mask_token='''[MASK]'''   )
									tokenizer.save_pretrained(self.tmpdirname   )


				@cached_property
				def     A_					(						self       :   List[Any]   ):
									return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''   )


				def     A_					(						self       :   Union[str, Any]			,							**lowercase_       :   List[str]   ):
									return PegasusTokenizer.from_pretrained(self.tmpdirname			,							**lowercase_   )


				def     A_					(						self       :   Dict			,							lowercase_       :   Optional[int]   ):
									return ("This is a test", "This is a test")


				def     A_					(						self       :   Dict   ):
									snake_case_		     =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname   )
									snake_case_		     =							self.tokenizer_class.from_pretrained(self.tmpdirname   )
									snake_case_		     =							(
									    '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
									    ''' <pad> <pad> <pad>'''
									)
									snake_case_		     =							rust_tokenizer([raw_input_str]			,							return_tensors=lowercase_			,							add_special_tokens=lowercase_   ).input_ids[0]
									snake_case_		     =							py_tokenizer([raw_input_str]			,							return_tensors=lowercase_			,							add_special_tokens=lowercase_   ).input_ids[0]
									self.assertListEqual(lowercase_			,							lowercase_   )


				@require_torch
				def     A_					(						self       :   List[Any]   ):
									snake_case_		     =							['''This is going to be way too long.''' * 1000, '''short example''']
									snake_case_		     =							['''not super long but more than 5 tokens''', '''tiny''']
									snake_case_		     =							self._large_tokenizer(lowercase_			,							padding=lowercase_			,							truncation=lowercase_			,							return_tensors='''pt'''   )
									snake_case_		     =							self._large_tokenizer(
									    text_target=lowercase_			,							max_length=5			,							padding=lowercase_			,							truncation=lowercase_			,							return_tensors='''pt'''   )

									assert batch.input_ids.shape == (2, 4096)
									assert batch.attention_mask.shape == (2, 4096)
									assert targets["input_ids"].shape == (2, 5)
									assert len(lowercase_   ) == 2  # input_ids, attention_mask.


				def     A_					(						self       :   Tuple   ):
									snake_case_		     =							(
									    '''This is an example string that is used to test the original TF implementation against the HF'''
									    ''' implementation'''
									)

									snake_case_		     =							self._large_tokenizer(lowercase_   ).input_ids

									self.assertListEqual(
									    lowercase_			,							[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1]			,							)







'''simple docstring'''

from ....utils import logging


a    :							Optional[int]										=    logging.get_logger(__name__)






class 		a							(  _lowerCamelCase	):


				def __init__(						self       :   int			,							lowercase_       :   Tuple			,							lowercase_       :   Any=None			,							lowercase_       :   List[Any]=2048   ):
									snake_case_		     =							config.__dict__
									snake_case_		     =							modal_hidden_size
									if num_labels:
														snake_case_		     =							num_labels

