

"""simple docstring"""






import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class        _lowercase					(     __UpperCAmelCase   , unittest.TestCase     ):
     _lowerCamelCase     =       CTRLTokenizer
     _lowerCamelCase     =       False
     _lowerCamelCase     =       False







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

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      __magic_name__     =      ['''adapt''', '''re@@''', '''a@@''', '''apt''', '''c@@''', '''t''', '''<unk>''']
      __magic_name__     =      dict(zip(UpperCamelCase_ ,						range(len(UpperCamelCase_       )       )       )       )
      __magic_name__     =      ['''#version: 0.2''', '''a p''', '''ap t</w>''', '''r e''', '''a d''', '''ad apt</w>''', '''''']
      __magic_name__     =      {'''unk_token''': '''<unk>'''}

      __magic_name__     =      os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']       )
      __magic_name__     =      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 	lowerCAmelCase__    (      self ,						**UpperCamelCase_       ):
      kwargs.update(self.special_tokens_map       )
      return CTRLTokenizer.from_pretrained(self.tmpdirname ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_       ):
      __magic_name__     =      '''adapt react readapt apt'''
      __magic_name__     =      '''adapt react readapt apt'''
      return input_text, output_text







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      CTRLTokenizer(self.vocab_file ,						self.merges_file ,						**self.special_tokens_map       )
      __magic_name__     =      '''adapt react readapt apt'''
      __magic_name__     =      '''adapt re@@ a@@ c@@ t re@@ adapt apt'''.split()
      __magic_name__     =      tokenizer.tokenize(UpperCamelCase_       )
      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )

      __magic_name__     =      tokens + [tokenizer.unk_token]

      __magic_name__     =      [0, 1, 2, 4, 5, 1, 0, 3, 6]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_       ) ,						UpperCamelCase_       )




"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCamelCase										=		{
    "configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
    "tokenization_m2m_100": ["M2M100Tokenizer"],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCamelCase										=		[
     "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST",
     "M2M100ForConditionalGeneration",
     "M2M100Model",
     "M2M100PreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
 from .tokenization_mam_aaa import MaMaaaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mam_aaa import (
      M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
      MaMaaaForConditionalGeneration,
      MaMaaaModel,
      MaMaaaPreTrainedModel,
  )


else:
 import sys

 __lowerCamelCase										=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

