


"""simple docstring"""






import json
import os
import unittest

from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors


@require_tokenizers
class 	A_       (     _UpperCAmelCase      ,  unittest.TestCase   ):





  """simple docstring"""

  lowercase		:	Tuple   =						BartTokenizer
  lowercase		:	List[str]   =						BartTokenizerFast
  lowercase		:	Any   =						True
  lowercase		:	int   =						filter_roberta_detectors
  def 							lowercase_     (						self						)				->					Any:
     super().setUp()
     a   :	Optional[int]						=    [
         'l',
         'o',
         'w',
         'e',
         'r',
         's',
         't',
         'i',
         'd',
         'n',
         '\u0120',
         '\u0120l',
         '\u0120n',
         '\u0120lo',
         '\u0120low',
         'er',
         '\u0120lowest',
         '\u0120newer',
         '\u0120wider',
         '<unk>',
     ]
     a   :	List[str]						=    dict(zip(__UpperCAmelCase  ,					range(len(__UpperCAmelCase						)						)						)						)
     a   :	List[str]						=    ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
     a   :	List[str]						=    {'unk_token': '<unk>'}

     a   :	Union[str, Any]						=    os.path.join(self.tmpdirname  ,					VOCAB_FILES_NAMES['vocab_file']						)
     a   :	Optional[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(__UpperCAmelCase						) + '\n'						)
     with open(self.merges_file  ,					'w'  ,					encoding='utf-8'						) as fp:
        fp.write('\n'.join(__UpperCAmelCase						)						)
  def 							lowercase_     (						self  ,					**__UpperCAmelCase						)				->					Tuple:
     kwargs.update(self.special_tokens_map						)
     return self.tokenizer_class.from_pretrained(self.tmpdirname  ,					**__UpperCAmelCase						)
  def 							lowercase_     (						self  ,					**__UpperCAmelCase						)				->					Dict:
     kwargs.update(self.special_tokens_map						)
     return self.rust_tokenizer_class.from_pretrained(self.tmpdirname  ,					**__UpperCAmelCase						)
  def 							lowercase_     (						self  ,					__UpperCAmelCase						)				->					Any:
     return "lower newer", "lower newer"
  @cached_property
  def 							lowercase_     (						self						)				->					str:
     return BartTokenizer.from_pretrained('facebook/bart-large'						)
  @cached_property
  def 							lowercase_     (						self						)				->					int:
     return BartTokenizerFast.from_pretrained('facebook/bart-large'						)
  @require_torch
  def 							lowercase_     (						self						)				->					int:
     a   :	int						=    ['A long paragraph for summarization.', 'Another paragraph for summarization.']
     a   :	List[str]						=    [0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]

     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        a   :	Dict						=    tokenizer(__UpperCAmelCase  ,					max_length=len(__UpperCAmelCase						)  ,					padding=__UpperCAmelCase  ,					return_tensors='pt'						)
        self.assertIsInstance(__UpperCAmelCase  ,					__UpperCAmelCase						)

        self.assertEqual((2, 9)  ,					batch.input_ids.shape						)
        self.assertEqual((2, 9)  ,					batch.attention_mask.shape						)
        a   :	List[str]						=    batch.input_ids.tolist()[0]
        self.assertListEqual(__UpperCAmelCase  ,					__UpperCAmelCase						)
        # Test that special tokens are reset
  @require_torch
  def 							lowercase_     (						self						)				->					List[Any]:
     a   :	str						=    ['A long paragraph for summarization.', 'Another paragraph for summarization.']
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        a   :	List[str]						=    tokenizer(__UpperCAmelCase  ,					padding=__UpperCAmelCase  ,					return_tensors='pt'						)
        # check if input_ids are returned and no labels
        self.assertIn('input_ids'  ,					__UpperCAmelCase						)
        self.assertIn('attention_mask'  ,					__UpperCAmelCase						)
        self.assertNotIn('labels'  ,					__UpperCAmelCase						)
        self.assertNotIn('decoder_attention_mask'  ,					__UpperCAmelCase						)
  @require_torch
  def 							lowercase_     (						self						)				->					List[str]:
     a   :	Any						=    [
         'Summary of the text.',
         'Another summary.',
     ]
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        a   :	str						=    tokenizer(text_target=__UpperCAmelCase  ,					max_length=32  ,					padding='max_length'  ,					return_tensors='pt'						)
        self.assertEqual(32  ,					targets['input_ids'].shape[1]						)
  @require_torch
  def 							lowercase_     (						self						)				->					List[Any]:
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        a   :	Tuple						=    tokenizer(
            ['I am a small frog' * 10_24, 'I am a small frog']  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase  ,					return_tensors='pt'						)
        self.assertIsInstance(__UpperCAmelCase  ,					__UpperCAmelCase						)
        self.assertEqual(batch.input_ids.shape  ,					(2, 10_24)						)
  @require_torch
  def 							lowercase_     (						self						)				->					Dict:
     a   :	List[Any]						=    ['A long paragraph for summarization.']
     a   :	Dict						=    [
         'Summary of the text.',
     ]
     for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        a   :	Dict						=    tokenizer(__UpperCAmelCase  ,					return_tensors='pt'						)
        a   :	Optional[Any]						=    tokenizer(text_target=__UpperCAmelCase  ,					return_tensors='pt'						)
        a   :	Tuple						=    inputs['input_ids']
        a   :	Dict						=    targets['input_ids']
        self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()						)
        self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()						)
        self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()						)
        self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()						)
  def 							lowercase_     (						self						)				->					Tuple:
     pass






  def 							lowercase_     (						self						)				->					Tuple:
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'						):
           a   :	Tuple						=    self.rust_tokenizer_class.from_pretrained(__UpperCAmelCase  ,					**__UpperCAmelCase						)
           a   :	List[str]						=    self.tokenizer_class.from_pretrained(__UpperCAmelCase  ,					**__UpperCAmelCase						)
           a   :	List[Any]						=    'A, <mask> AllenNLP sentence.'
           a   :	Optional[int]						=    tokenizer_r.encode_plus(__UpperCAmelCase  ,					add_special_tokens=__UpperCAmelCase  ,					return_token_type_ids=__UpperCAmelCase						)
           a   :	Union[str, Any]						=    tokenizer_p.encode_plus(__UpperCAmelCase  ,					add_special_tokens=__UpperCAmelCase  ,					return_token_type_ids=__UpperCAmelCase						)

           # 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']						)  ,					)

           a   :	Union[str, Any]						=    tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']						)
           a   :	Union[str, 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_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]						)
           self.assertSequenceEqual(tokens_r['input_ids']  ,					[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]						)

           self.assertSequenceEqual(
               __UpperCAmelCase  ,					['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']						)
           self.assertSequenceEqual(
               __UpperCAmelCase  ,					['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']						)









"""simple docstring"""






from transformers.models.cpm.tokenization_cpm import CpmTokenizer
from transformers.testing_utils import custom_tokenizers

from ..xlnet.test_modeling_xlnet import XLNetModelTest


@custom_tokenizers
class 	A_       (     _UpperCAmelCase   ):





  """simple docstring"""

  def 							lowercase_     (						self  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase  ,					__UpperCAmelCase						)				->					int:
     return True






  def 							lowercase_     (						self						)				->					int:
     a   :	Optional[int]						=    CpmTokenizer.from_pretrained('TsinghuaAI/CPM-Generate'						)
     a   :	Any						=    'Hugging Face大法好，谁用谁知道。'
     a   :	Tuple						=    'Hugging Face大法好,谁用谁知道。<unk>'
     a   :	Optional[int]						=    '▁Hu gg ing ▁ ▂ ▁F ace ▁大法 ▁好 ▁ , ▁谁 ▁用 ▁谁 ▁知 道 ▁ 。'.split()

     a   :	Optional[int]						=    tokenizer.tokenize(__UpperCAmelCase						)
     self.assertListEqual(__UpperCAmelCase  ,					__UpperCAmelCase						)

     a   :	Optional[Any]						=    tokens + [tokenizer.unk_token]

     a   :	str						=    [1_37_89, 1_32_83, 14_21, 8, 10, 11_64, 1_36_08, 1_65_28, 63, 8, 9, 4_40, 1_08, 4_40, 1_21, 90, 8, 12, 0]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase						)  ,					__UpperCAmelCase						)

     a   :	List[Any]						=    tokenizer.decode(__UpperCAmelCase						)
     self.assertEqual(__UpperCAmelCase  ,					__UpperCAmelCase						)





