





from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate




@dataclass(frozen=__A)
class        _a    (    __A):

      """simple docstring"""


      UpperCamelCase__  		=       field(default="""summarization"""						,			metadata={"""include_in_asdict_even_if_is_default""": True})
      UpperCamelCase__  		=       Features({"""text""": Value("""string""")})
      UpperCamelCase__  		=       Features({"""summary""": Value("""string""")})
      UpperCamelCase__  		=       """text"""
      UpperCamelCase__  		=       """summary"""






      @property
      def 			UpperCAmelCase_       (		self:			int					):
          '''simple docstring'''


          return {self.text_column: "text", self.summary_column: "summary"}









'''simple docstring'''



import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
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 UpperCAmelCase_       (     __A					,							unittest.TestCase					):




      """simple docstring"""




      UpperCamelCase_             =      MvpTokenizer
      UpperCamelCase_             =      MvpTokenizerFast
      UpperCamelCase_             =      True
      UpperCamelCase_             =      filter_roberta_detectors






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


       '''simple docstring'''

       super().setUp()
       lowercase       : Dict						=[
           '''l''',
           '''o''',
           '''w''',
           '''e''',
           '''r''',
           '''s''',
           '''t''',
           '''i''',
           '''d''',
           '''n''',
           '''\u0120''',
           '''\u0120l''',
           '''\u0120n''',
           '''\u0120lo''',
           '''\u0120low''',
           '''er''',
           '''\u0120lowest''',
           '''\u0120newer''',
           '''\u0120wider''',
           '''<unk>''',
       ]
       lowercase       : Tuple						=dict(zip(UpperCAmelCase  ,   range(len(UpperCAmelCase		)		)		)		)
       lowercase       : Optional[Any]						=['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
       lowercase       : List[Any]						={'''unk_token''': '''<unk>'''}

       lowercase       : Dict						=os.path.join(self.tmpdirname  ,   VOCAB_FILES_NAMES['''vocab_file''']		)
       lowercase       : Dict						=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 					A__   (			self      :		Union[str, Any]  ,   **UpperCAmelCase      :		Dict		)	->	Tuple:


       '''simple docstring'''

       kwargs.update(self.special_tokens_map		)
       return self.tokenizer_class.from_pretrained(self.tmpdirname  ,   **UpperCAmelCase		)






      def 					A__   (			self      :		List[str]  ,   **UpperCAmelCase      :		Any		)	->	Tuple:


       '''simple docstring'''

       kwargs.update(self.special_tokens_map		)
       return self.rust_tokenizer_class.from_pretrained(self.tmpdirname  ,   **UpperCAmelCase		)






      def 					A__   (			self      :		Tuple  ,   UpperCAmelCase      :		Any		)	->	Union[str, Any]:


       '''simple docstring'''

       return "lower newer", "lower newer"






      @cached_property
      def 					A__   (			self      :		Tuple		)	->	List[Any]:


       '''simple docstring'''

       return MvpTokenizer.from_pretrained('''RUCAIBox/mvp'''		)






      @cached_property
      def 					A__   (			self      :		Any		)	->	int:


       '''simple docstring'''

       return MvpTokenizerFast.from_pretrained('''RUCAIBox/mvp'''		)






      @require_torch
      def 					A__   (			self      :		Union[str, Any]		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : Optional[int]						=['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
       lowercase       : List[str]						=[0, 250, 251, 1_7818, 13, 3_9186, 1938, 4, 2]

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase       : Union[str, Any]						=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		)
        lowercase       : Union[str, Any]						=batch.input_ids.tolist()[0]
        self.assertListEqual(UpperCAmelCase  ,   UpperCAmelCase		)
        # Test that special tokens are reset






      @require_torch
      def 					A__   (			self      :		Tuple		)	->	Any:


       '''simple docstring'''

       lowercase       : Any						=['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase       : Dict						=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 					A__   (			self      :		Dict		)	->	int:


       '''simple docstring'''

       lowercase       : int						=[
           '''Summary of the text.''',
           '''Another summary.''',
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase       : Optional[Any]						=tokenizer(text_target=UpperCAmelCase  ,   max_length=32  ,   padding='''max_length'''  ,   return_tensors='''pt'''		)
        self.assertEqual(32  ,   targets['''input_ids'''].shape[1]		)






      @require_torch
      def 					A__   (			self      :		Union[str, Any]		)	->	Any:


       '''simple docstring'''

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase       : Union[str, Any]						=tokenizer(
            ['''I am a small frog''' * 1024, '''I am a small frog''']  ,   padding=UpperCAmelCase  ,   truncation=UpperCAmelCase  ,   return_tensors='''pt'''		)
        self.assertIsInstance(UpperCAmelCase  ,   UpperCAmelCase		)
        self.assertEqual(batch.input_ids.shape  ,   (2, 1024)		)






      @require_torch
      def 					A__   (			self      :		str		)	->	List[Any]:


       '''simple docstring'''

       lowercase       : Optional[Any]						=['''A long paragraph for summarization.''']
       lowercase       : List[Any]						=[
           '''Summary of the text.''',
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
        lowercase       : List[str]						=tokenizer(UpperCAmelCase  ,   text_target=UpperCAmelCase  ,   return_tensors='''pt'''		)
        lowercase       : Optional[int]						=inputs['''input_ids''']
        lowercase       : Optional[Any]						=inputs['''labels''']
        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 					A__   (			self      :		List[Any]		)	->	List[Any]:


       '''simple docstring'''

       pass






      def 					A__   (			self      :		List[str]		)	->	Tuple:


       '''simple docstring'''

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

         lowercase       : Any						=tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']		)
         lowercase       : str						=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, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]		)
         self.assertSequenceEqual(tokens_r['''input_ids''']  ,   [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]		)

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



