'''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=  get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')






@require_sentencepiece
@require_tokenizers
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						PegasusTokenizer
     SCREAMING_SNAKE_CASE__		   =						PegasusTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						True







     def lowerCAmelCase     (		self    ):
         super().setUp()

         # We have a SentencePiece fixture for testing
         __UpperCamelCase	:	Dict		    =  PegasusTokenizer(_lowerCamelCase    )
         tokenizer.save_pretrained(self.tmpdirname    )







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







     def lowerCAmelCase     (		self     ,			**_lowerCamelCase    ):
         return PegasusTokenizer.from_pretrained(self.tmpdirname     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return ("This is a test", "This is a test")







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  '</s>'
         __UpperCamelCase	:	Optional[Any]		    =  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    ):
         __UpperCamelCase	:	List[str]		    =  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    )     ,			1_1_0_3    )







     def lowerCAmelCase     (		self    ):
         self.assertEqual(self.get_tokenizer().vocab_size     ,			1_1_0_3    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Tuple		    =  self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
         __UpperCamelCase	:	List[Any]		    =  self.tokenizer_class.from_pretrained(self.tmpdirname    )
         __UpperCamelCase	:	Union[str, 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	:	int		    =  py_tokenizer([raw_input_str]     ,			return_tensors=_lowerCamelCase     ,			add_special_tokens=_lowerCamelCase    ).input_ids[0]
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  self._large_tokenizer
         # <mask_1> masks whole sentence while <mask_2> masks single word
         __UpperCamelCase	:	Tuple		    =  '<mask_1> To ensure a <mask_2> flow of bank resolutions.'
         __UpperCamelCase	:	str		    =  [2, 4_1_3, 6_1_5, 1_1_4, 3, 1_9_7_1, 1_1_3, 1_6_7_9, 1_0_7_1_0, 1_0_7, 1]
         __UpperCamelCase	:	Dict		    =  tokenizer([raw_input_str]     ,			return_tensors=_lowerCamelCase    ).input_ids[0]
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[Any]		    =  self._large_tokenizer
         # The tracebacks for the following asserts are **better** without messages or self.assertEqual
         assert tokenizer.vocab_size == 9_6_1_0_3
         assert tokenizer.pad_token_id == 0
         assert tokenizer.eos_token_id == 1
         assert tokenizer.offset == 1_0_3
         assert tokenizer.unk_token_id == tokenizer.offset + 2 == 1_0_5
         assert tokenizer.unk_token == "<unk>"
         assert tokenizer.model_max_length == 1_0_2_4
         __UpperCamelCase	:	Optional[Any]		    =  'To ensure a smooth flow of bank resolutions.'
         __UpperCamelCase	:	Union[str, Any]		    =  [4_1_3, 6_1_5, 1_1_4, 2_2_9_1, 1_9_7_1, 1_1_3, 1_6_7_9, 1_0_7_1_0, 1_0_7, 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    ):
         __UpperCamelCase	:	List[str]		    =  ['This is going to be way too long.' * 1_5_0, 'short example']
         __UpperCamelCase	:	int		    =  ['not super long but more than 5 tokens', 'tiny']
         __UpperCamelCase	:	Dict		    =  self._large_tokenizer(_lowerCamelCase     ,			padding=_lowerCamelCase     ,			truncation=_lowerCamelCase     ,			return_tensors='pt'    )
         __UpperCamelCase	:	Dict		    =  self._large_tokenizer(
             text_target=_lowerCamelCase     ,			max_length=5     ,			padding=_lowerCamelCase     ,			truncation=_lowerCamelCase     ,			return_tensors='pt'    )

         assert batch.input_ids.shape == (2, 1_0_2_4)
         assert batch.attention_mask.shape == (2, 1_0_2_4)
         assert targets["input_ids"].shape == (2, 5)
         assert len(_lowerCamelCase    ) == 2  # input_ids, attention_mask.







     @slow
     def lowerCAmelCase     (		self    ):
         # fmt: off
         __UpperCamelCase	:	Union[str, Any]		    =  {'input_ids': [[3_8_9_7_9, 1_4_3, 1_8_4_8_5, 6_0_6, 1_3_0, 2_6_6_6_9, 8_7_6_8_6, 1_2_1, 5_4_1_8_9, 1_1_2_9, 1_1_1, 2_6_6_6_9, 8_7_6_8_6, 1_2_1, 9_1_1_4, 1_4_7_8_7, 1_2_1, 1_3_2_4_9, 1_5_8, 5_9_2, 9_5_6, 1_2_1, 1_4_6_2_1, 3_1_5_7_6, 1_4_3, 6_2_6_1_3, 1_0_8, 9_6_8_8, 9_3_0, 4_3_4_3_0, 1_1_5_6_2, 6_2_6_1_3, 3_0_4, 1_0_8, 1_1_4_4_3, 8_9_7, 1_0_8, 9_3_1_4, 1_7_4_1_5, 6_3_3_9_9, 1_0_8, 1_1_4_4_3, 7_6_1_4, 1_8_3_1_6, 1_1_8, 4_2_8_4, 7_1_4_8, 1_2_4_3_0, 1_4_3, 1_4_0_0, 2_5_7_0_3, 1_5_8, 1_1_1, 4_2_8_4, 7_1_4_8, 1_1_7_7_2, 1_4_3, 2_1_2_9_7, 1_0_6_4, 1_5_8, 1_2_2, 2_0_4, 3_5_0_6, 1_7_5_4, 1_1_3_3, 1_4_7_8_7, 1_5_8_1, 1_1_5, 3_3_2_2_4, 4_4_8_2, 1_1_1, 1_3_5_5, 1_1_0, 2_9_1_7_3, 3_1_7, 5_0_8_3_3, 1_0_8, 2_0_1_4_7, 9_4_6_6_5, 1_1_1, 7_7_1_9_8, 1_0_7, 1], [1_1_0, 6_2_6_1_3, 1_1_7, 6_3_8, 1_1_2, 1_1_3_3, 1_2_1, 2_0_0_9_8, 1_3_5_5, 7_9_0_5_0, 1_3_8_7_2, 1_3_5, 1_5_9_6, 5_3_5_4_1, 1_3_5_2, 1_4_1, 1_3_0_3_9, 5_5_4_2, 1_2_4, 3_0_2, 5_1_8, 1_1_1, 2_6_8, 2_9_5_6, 1_1_5, 1_4_9, 4_4_2_7, 1_0_7, 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_3_9, 1_2_3_5, 2_7_9_9, 1_8_2_8_9, 1_7_7_8_0, 2_0_4, 1_0_9, 9_4_7_4, 1_2_9_6, 1_0_7, 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"""






     SCREAMING_SNAKE_CASE__		   =						PegasusTokenizer
     SCREAMING_SNAKE_CASE__		   =						PegasusTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						True







     def lowerCAmelCase     (		self    ):
         super().setUp()

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







     @cached_property
     def lowerCAmelCase     (		self    ):
         return PegasusTokenizer.from_pretrained('google/bigbird-pegasus-large-arxiv'    )







     def lowerCAmelCase     (		self     ,			**_lowerCamelCase    ):
         return PegasusTokenizer.from_pretrained(self.tmpdirname     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return ("This is a test", "This is a test")







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Any		    =  self.rust_tokenizer_class.from_pretrained(self.tmpdirname    )
         __UpperCamelCase	:	List[str]		    =  self.tokenizer_class.from_pretrained(self.tmpdirname    )
         __UpperCamelCase	:	Dict		    =  (
             '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	:	int		    =  py_tokenizer([raw_input_str]     ,			return_tensors=_lowerCamelCase     ,			add_special_tokens=_lowerCamelCase    ).input_ids[0]
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     @require_torch
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	str		    =  ['This is going to be way too long.' * 1_0_0_0, 'short example']
         __UpperCamelCase	:	Union[str, Any]		    =  ['not super long but more than 5 tokens', 'tiny']
         __UpperCamelCase	:	Any		    =  self._large_tokenizer(_lowerCamelCase     ,			padding=_lowerCamelCase     ,			truncation=_lowerCamelCase     ,			return_tensors='pt'    )
         __UpperCamelCase	:	Optional[Any]		    =  self._large_tokenizer(
             text_target=_lowerCamelCase     ,			max_length=5     ,			padding=_lowerCamelCase     ,			truncation=_lowerCamelCase     ,			return_tensors='pt'    )

         assert batch.input_ids.shape == (2, 4_0_9_6)
         assert batch.attention_mask.shape == (2, 4_0_9_6)
         assert targets["input_ids"].shape == (2, 5)
         assert len(_lowerCamelCase    ) == 2  # input_ids, attention_mask.







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  (
             'This is an example string that is used to test the original TF implementation against the HF'
             ' implementation'
         )

         __UpperCamelCase	:	List[Any]		    =  self._large_tokenizer(_lowerCamelCase    ).input_ids

         self.assertListEqual(
             _lowerCamelCase     ,			[1_8_2, 1_1_7, 1_4_2, 5_8_7, 4_2_1_1, 1_2_0, 1_1_7, 2_6_3, 1_1_2, 8_0_4, 1_0_9, 8_5_6, 2_5_0_1_6, 3_1_3_7, 4_6_4, 1_0_9, 2_6_9_5_5, 3_1_3_7, 1]     ,			)




'''simple docstring'''
import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						LayoutLMTokenizer
     SCREAMING_SNAKE_CASE__		   =						LayoutLMTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						True







     def lowerCAmelCase     (		self    ):
         super().setUp()

         __UpperCamelCase	:	List[str]		    =  [
             '[UNK]',
             '[CLS]',
             '[SEP]',
             'want',
             '##want',
             '##ed',
             'wa',
             'un',
             'runn',
             '##ing',
             ',',
             'low',
             'lowest',
         ]
         __UpperCamelCase	:	Union[str, Any]		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['vocab_file']    )
         with open(self.vocab_file     ,			'w'     ,			encoding='utf-8'    ) as vocab_writer:
             vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]    )    )







     def lowerCAmelCase     (		self     ,			**_lowerCamelCase    ):
         return LayoutLMTokenizer.from_pretrained(self.tmpdirname     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	Dict		    =  'UNwant\u00E9d,running'
         __UpperCamelCase	:	Union[str, Any]		    =  'unwanted, running'
         return input_text, output_text







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  self.tokenizer_class(self.vocab_file    )

         __UpperCamelCase	:	Optional[Any]		    =  tokenizer.tokenize('UNwant\u00E9d,running'    )
         self.assertListEqual(_lowerCamelCase     ,			['un', '##want', '##ed', ',', 'runn', '##ing']    )
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase    )     ,			[7, 4, 5, 1_0, 8, 9]    )







     def lowerCAmelCase     (		self    ):
         pass



