'''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


UpperCamelCase__     :	int				=			get_tests_dir('fixtures/test_sentencepiece_no_bos.model')


@require_sentencepiece
@require_tokenizers
class 				_lowercase	(      lowerCAmelCase		,unittest.TestCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Dict      							=   PegasusTokenizer
      UpperCAmelCase_      :      List[str]      							=   PegasusTokenizerFast
      UpperCAmelCase_      :      Optional[int]      							=   True
      UpperCAmelCase_      :      Tuple      							=   True




      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         super().setUp()

         # We have a SentencePiece fixture for testing
         UpperCAmelCase__							:				Any   				=  PegasusTokenizer(lowerCamelCase_							)
         tokenizer.save_pretrained(self.tmpdirname							)




      @cached_property
      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         return PegasusTokenizer.from_pretrained('''google/pegasus-large'''							)




      def 		lowerCAmelCase__					(				self					,**lowerCamelCase_							)			->			PegasusTokenizer:



         '''simple docstring'''



         return PegasusTokenizer.from_pretrained(self.tmpdirname					,**lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Dict:



         '''simple docstring'''



         return ("This is a test", "This is a test")




      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[int]   				=  '''</s>'''
         UpperCAmelCase__							:				str   				=  1

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




      def 		lowerCAmelCase__					(				self							)			->			Optional[Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				List[Any]   				=  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(lowerCamelCase_							)					,1103							)




      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         self.assertEqual(self.get_tokenizer().vocab_size					,1103							)




      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         UpperCAmelCase__							:				List[Any]   				=  self.rust_tokenizer_class.from_pretrained(self.tmpdirname							)
         UpperCAmelCase__							:				Any   				=  self.tokenizer_class.from_pretrained(self.tmpdirname							)
         UpperCAmelCase__							:				Optional[Any]   				=  (
             '''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>'''
         )
         UpperCAmelCase__							:				List[Any]   				=  rust_tokenizer([raw_input_str]					,return_tensors=lowerCamelCase_					,add_special_tokens=lowerCamelCase_							).input_ids[0]
         UpperCAmelCase__							:				Any   				=  py_tokenizer([raw_input_str]					,return_tensors=lowerCamelCase_					,add_special_tokens=lowerCamelCase_							).input_ids[0]
         self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			Union[str, Any]:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[Any]   				=  self._large_tokenizer
         # <mask_1> masks whole sentence while <mask_2> masks single word
         UpperCAmelCase__							:				Any   				=  '''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
         UpperCAmelCase__							:				Dict   				=  [2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
         UpperCAmelCase__							:				List[str]   				=  tokenizer([raw_input_str]					,return_tensors=lowerCamelCase_							).input_ids[0]
         self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			List[str]:



         '''simple docstring'''



         UpperCAmelCase__							:				int   				=  self._large_tokenizer
         # The tracebacks for the following asserts are **better** without messages or self.assertEqual
         assert tokenizer.vocab_size == 96103
         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
         UpperCAmelCase__							:				Dict   				=  '''To ensure a smooth flow of bank resolutions.'''
         UpperCAmelCase__							:				List[str]   				=  [413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
         UpperCAmelCase__							:				List[Any]   				=  tokenizer([raw_input_str]					,return_tensors=lowerCamelCase_							).input_ids[0]
         self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)
         assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]							) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]




      @require_torch
      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         UpperCAmelCase__							:				Tuple   				=  ['''This is going to be way too long.''' * 150, '''short example''']
         UpperCAmelCase__							:				List[Any]   				=  ['''not super long but more than 5 tokens''', '''tiny''']
         UpperCAmelCase__							:				Any   				=  self._large_tokenizer(lowerCamelCase_					,padding=lowerCamelCase_					,truncation=lowerCamelCase_					,return_tensors='''pt'''							)
         UpperCAmelCase__							:				str   				=  self._large_tokenizer(
             text_target=lowerCamelCase_					,max_length=5					,padding=lowerCamelCase_					,truncation=lowerCamelCase_					,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(lowerCamelCase_							) == 2  # input_ids, attention_mask.




      @slow
      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				List[str]   				=  {'''input_ids''': [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 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, 18289, 17780, 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=lowerCamelCase_					,model_name='''google/bigbird-pegasus-large-arxiv'''					,revision='''ba85d0851d708441f91440d509690f1ab6353415'''					,)




@require_sentencepiece
@require_tokenizers
class 				_lowercase	(      lowerCAmelCase		,unittest.TestCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Optional[int]      							=   PegasusTokenizer
      UpperCAmelCase_      :      Union[str, Any]      							=   PegasusTokenizerFast
      UpperCAmelCase_      :      Optional[Any]      							=   True
      UpperCAmelCase_      :      Optional[int]      							=   True




      def 		lowerCAmelCase__					(				self							)			->			List[Any]:



         '''simple docstring'''



         super().setUp()

         # We have a SentencePiece fixture for testing
         UpperCAmelCase__							:				Optional[int]   				=  PegasusTokenizer(lowerCamelCase_					,offset=0					,mask_token_sent=lowerCamelCase_					,mask_token='''[MASK]'''							)
         tokenizer.save_pretrained(self.tmpdirname							)




      @cached_property
      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''							)




      def 		lowerCAmelCase__					(				self					,**lowerCamelCase_							)			->			PegasusTokenizer:



         '''simple docstring'''



         return PegasusTokenizer.from_pretrained(self.tmpdirname					,**lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			str:



         '''simple docstring'''



         return ("This is a test", "This is a test")




      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



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




      @require_torch
      def 		lowerCAmelCase__					(				self							)			->			int:



         '''simple docstring'''



         UpperCAmelCase__							:				Union[str, Any]   				=  ['''This is going to be way too long.''' * 1000, '''short example''']
         UpperCAmelCase__							:				Optional[Any]   				=  ['''not super long but more than 5 tokens''', '''tiny''']
         UpperCAmelCase__							:				Union[str, Any]   				=  self._large_tokenizer(lowerCamelCase_					,padding=lowerCamelCase_					,truncation=lowerCamelCase_					,return_tensors='''pt'''							)
         UpperCAmelCase__							:				Optional[int]   				=  self._large_tokenizer(
             text_target=lowerCamelCase_					,max_length=5					,padding=lowerCamelCase_					,truncation=lowerCamelCase_					,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(lowerCamelCase_							) == 2  # input_ids, attention_mask.




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				int   				=  (
             '''This is an example string that is used to test the original TF implementation against the HF'''
             ''' implementation'''
         )

         UpperCAmelCase__							:				List[str]   				=  self._large_tokenizer(lowerCamelCase_							).input_ids

         self.assertListEqual(
             lowerCamelCase_					,[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]					,)





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__     :	Union[str, Any]				=			{'tokenization_byt5': ['ByT5Tokenizer']}


if TYPE_CHECKING:
  from .tokenization_byta import ByTaTokenizer
else:
  import sys

  UpperCamelCase__     :	List[str]				=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




