





from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader





class 				A_				(      UpperCAmelCase	):







       """simple docstring"""





       def __init__(    self	:	Optional[int]						,__A	:	NestedDataStructureLike[PathLike]						,__A	:	Optional[NamedSplit] = None						,__A	:	Optional[Features] = None						,__A	:	str = None						,__A	:	bool = False						,__A	:	bool = False						,__A	:	Optional[int] = None						,**__A	:	Tuple						,)						->					str:
         super().__init__(
             __A						,split=__A						,features=__A						,cache_dir=__A						,keep_in_memory=__A						,streaming=__A						,num_proc=__A						,**__A						,)
         _lowercase							= path_or_paths if isinstance(__A						,__A  ) else {self.split: path_or_paths}
         _lowercase							= Text(
             cache_dir=__A						,data_files=__A						,features=__A						,**__A						,)







       def    __UpperCAmelCase (    self	:	Any  )						->					List[str]:
         # Build iterable dataset
         if self.streaming:
           _lowercase							= self.builder.as_streaming_dataset(split=self.split  )
         # Build regular (map-style) dataset
         else:
           _lowercase							= None
           _lowercase							= None
           _lowercase							= None
           _lowercase							= None

           self.builder.download_and_prepare(
               download_config=__A						,download_mode=__A						,verification_mode=__A						,base_path=__A						,num_proc=self.num_proc						,)
           _lowercase							= self.builder.as_dataset(
               split=self.split						,verification_mode=__A						,in_memory=self.keep_in_memory  )
         return dataset






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


snake_case 				=       get_tests_dir("""fixtures/test_sentencepiece_no_bos.model""")





@require_sentencepiece
@require_tokenizers
class 				A_				(      UpperCAmelCase					,	unittest.TestCase	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : int      =  PegasusTokenizer
       SCREAMING_SNAKE_CASE_      : Optional[int]      =  PegasusTokenizerFast
       SCREAMING_SNAKE_CASE_      : Any      =  True
       SCREAMING_SNAKE_CASE_      : Optional[int]      =  True







       def    __UpperCAmelCase (    self	:	List[str]  )						->					Any:
         super().setUp()

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







       @cached_property
       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					List[Any]:
         return PegasusTokenizer.from_pretrained('google/pegasus-large'  )







       def    __UpperCAmelCase (    self	:	Any						,**__A	:	int  )						->					PegasusTokenizer:
         return PegasusTokenizer.from_pretrained(self.tmpdirname						,**__A  )







       def    __UpperCAmelCase (    self	:	Union[str, Any]						,__A	:	int  )						->					List[str]:
         return ("This is a test", "This is a test")







       def    __UpperCAmelCase (    self	:	List[str]  )						->					Optional[Any]:
         _lowercase							= '</s>'
         _lowercase							= 1

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







       def    __UpperCAmelCase (    self	:	List[Any]  )						->					Optional[Any]:
         _lowercase							= 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(__A  )						,1103  )







       def    __UpperCAmelCase (    self	:	Tuple  )						->					Any:
         self.assertEqual(self.get_tokenizer().vocab_size						,1103  )







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					List[str]:
         _lowercase							= self.rust_tokenizer_class.from_pretrained(self.tmpdirname  )
         _lowercase							= self.tokenizer_class.from_pretrained(self.tmpdirname  )
         _lowercase							= (
             '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>'
         )
         _lowercase							= rust_tokenizer([raw_input_str]						,return_tensors=__A						,add_special_tokens=__A  ).input_ids[0]
         _lowercase							= py_tokenizer([raw_input_str]						,return_tensors=__A						,add_special_tokens=__A  ).input_ids[0]
         self.assertListEqual(__A						,__A  )







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







       def    __UpperCAmelCase (    self	:	int  )						->					Union[str, Any]:
         _lowercase							= 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
         _lowercase							= 'To ensure a smooth flow of bank resolutions.'
         _lowercase							= [413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
         _lowercase							= tokenizer([raw_input_str]						,return_tensors=__A  ).input_ids[0]
         self.assertListEqual(__A						,__A  )
         assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]  ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]







       @require_torch
       def    __UpperCAmelCase (    self	:	Optional[int]  )						->					List[str]:
         _lowercase							= ['This is going to be way too long.' * 150, 'short example']
         _lowercase							= ['not super long but more than 5 tokens', 'tiny']
         _lowercase							= self._large_tokenizer(__A						,padding=__A						,truncation=__A						,return_tensors='pt'  )
         _lowercase							= self._large_tokenizer(
             text_target=__A						,max_length=5						,padding=__A						,truncation=__A						,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(__A  ) == 2  # input_ids, attention_mask.







       @slow
       def    __UpperCAmelCase (    self	:	Dict  )						->					Optional[int]:
         # fmt: off
         _lowercase							= {'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=__A						,model_name='google/bigbird-pegasus-large-arxiv'						,revision='ba85d0851d708441f91440d509690f1ab6353415'						,)





@require_sentencepiece
@require_tokenizers
class 				A_				(      UpperCAmelCase					,	unittest.TestCase	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : int      =  PegasusTokenizer
       SCREAMING_SNAKE_CASE_      : int      =  PegasusTokenizerFast
       SCREAMING_SNAKE_CASE_      : str      =  True
       SCREAMING_SNAKE_CASE_      : List[Any]      =  True







       def    __UpperCAmelCase (    self	:	List[str]  )						->					Optional[int]:
         super().setUp()

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







       @cached_property
       def    __UpperCAmelCase (    self	:	str  )						->					Optional[Any]:
         return PegasusTokenizer.from_pretrained('google/bigbird-pegasus-large-arxiv'  )







       def    __UpperCAmelCase (    self	:	Union[str, Any]						,**__A	:	Union[str, Any]  )						->					PegasusTokenizer:
         return PegasusTokenizer.from_pretrained(self.tmpdirname						,**__A  )







       def    __UpperCAmelCase (    self	:	Union[str, Any]						,__A	:	int  )						->					Tuple:
         return ("This is a test", "This is a test")







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







       @require_torch
       def    __UpperCAmelCase (    self	:	List[str]  )						->					Dict:
         _lowercase							= ['This is going to be way too long.' * 1000, 'short example']
         _lowercase							= ['not super long but more than 5 tokens', 'tiny']
         _lowercase							= self._large_tokenizer(__A						,padding=__A						,truncation=__A						,return_tensors='pt'  )
         _lowercase							= self._large_tokenizer(
             text_target=__A						,max_length=5						,padding=__A						,truncation=__A						,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(__A  ) == 2  # input_ids, attention_mask.







       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					int:
         _lowercase							= (
             'This is an example string that is used to test the original TF implementation against the HF'
             ' implementation'
         )

         _lowercase							= self._large_tokenizer(__A  ).input_ids

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