


import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin







class       lowerCamelCase__   (       lowerCAmelCase   ,							unittest.TestCase):
     SCREAMING_SNAKE_CASE__      			=			BlenderbotSmallTokenizer
     SCREAMING_SNAKE_CASE__      			=			False





     def      __A					(self       )     ->   Any:
      super().setUp()

      _lowercase							      =['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
      _lowercase							      =dict(zip(UpperCAmelCase		,     range(len(UpperCAmelCase       )       )       )       )

      _lowercase							      =['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
      _lowercase							      ={'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

      _lowercase							      =os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['''vocab_file''']       )
      _lowercase							      =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		,     **UpperCAmelCase       )     ->   List[str]:
      kwargs.update(self.special_tokens_map       )
      return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname		,     **UpperCAmelCase       )





     def      __A					(self		,     UpperCAmelCase       )     ->   Optional[int]:
      _lowercase							      ='''adapt act apte'''
      _lowercase							      ='''adapt act apte'''
      return input_text, output_text





     def      __A					(self       )     ->   str:
      _lowercase							      =BlenderbotSmallTokenizer(self.vocab_file		,     self.merges_file		,     **self.special_tokens_map       )
      _lowercase							      ='''adapt act apte'''
      _lowercase							      =['''adapt''', '''act''', '''ap@@''', '''te''']
      _lowercase							      =tokenizer.tokenize(UpperCAmelCase       )
      self.assertListEqual(UpperCAmelCase		,     UpperCAmelCase       )

      _lowercase							      =[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

      _lowercase							      =[0, 1, 2, 3, 4, 5]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase       )		,     UpperCAmelCase       )





     def      __A					(self       )     ->   Dict:
      _lowercase							      =BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
      assert tok('''sam'''       ).input_ids == [1_3_8_4]
      _lowercase							      ='''I am a small frog.'''
      _lowercase							      =tok([src_text]		,     padding=UpperCAmelCase		,     truncation=UpperCAmelCase       )['''input_ids''']
      _lowercase							      =tok.batch_decode(UpperCAmelCase		,     skip_special_tokens=UpperCAmelCase		,     clean_up_tokenization_spaces=UpperCAmelCase       )[0]
      assert src_text != decoded  # I wish it did!
      assert decoded == "i am a small frog ."





     def      __A					(self       )     ->   Dict:
      _lowercase							      =BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
      _lowercase							      ='''I am a small frog .'''
      _lowercase							      ='''.'''
      _lowercase							      =tok(UpperCAmelCase       )['''input_ids''']
      _lowercase							      =tok(UpperCAmelCase       )['''input_ids''']

      assert encoded[-1] == encoded_dot[0]





from typing import TYPE_CHECKING

from ..utils import _LazyModule


UpperCAmelCase__   	=							{
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
  from .config import (
      EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
      OnnxConfig,
      OnnxConfigWithPast,
      OnnxSeqaSeqConfigWithPast,
      PatchingSpec,
  )
  from .convert import export, validate_model_outputs
  from .features import FeaturesManager
  from .utils import ParameterFormat, compute_serialized_parameters_size

else:
  import sys

  UpperCAmelCase__   	=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

