

import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch

import pyarrow as pa
import pytest
import requests
from packaging import version

from datasets import config


if config.PY_VERSION < version.parse('''3.8'''):
 import importlib_metadata
else:
 import importlib.metadata as importlib_metadata



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase=False					)							->     List[str]:



  """simple docstring"""






  try:
    _snake_case						=							os.environ[key]
  except KeyError:
    # KEY isn't set, default to `default`.
    _snake_case						=							default
  else:
    # KEY is set, convert it to True or False.
    try:
      _snake_case						=							strtobool(_UpperCamelCase					)
    except ValueError:
      # More values are supported, but let's keep the message simple.
      raise ValueError(F"""If set, {key} must be yes or no."""					)
  return _value


__A      		=     parse_flag_from_env('''RUN_SLOW''', default=False)
__A      		=     parse_flag_from_env('''RUN_REMOTE''', default=False)
__A      		=     parse_flag_from_env('''RUN_LOCAL''', default=True)
__A      		=     parse_flag_from_env('''RUN_PACKAGED''', default=True)

# Compression
__A      		=     pytest.mark.skipif(not config.LZ4_AVAILABLE, reason='''test requires lz4''')
__A      		=     pytest.mark.skipif(not config.PY7ZR_AVAILABLE, reason='''test requires py7zr''')
__A      		=     pytest.mark.skipif(not config.ZSTANDARD_AVAILABLE, reason='''test requires zstandard''')

# Audio
__A      		=     pytest.mark.skipif(
    # On Windows and OS X, soundfile installs sndfile
    find_spec('''soundfile''') is None or version.parse(importlib_metadata.version('''soundfile''')) < version.parse('''0.12.0'''),
    reason='''test requires sndfile>=0.12.1: \'pip install \"soundfile>=0.12.1\"\'; ''',
)

# Beam
__A      		=     pytest.mark.skipif(
    not config.BEAM_AVAILABLE or config.DILL_VERSION >= version.parse('''0.3.2'''),
    reason='''test requires apache-beam and a compatible dill version''',
)

# Dill-cloudpickle compatibility
__A      		=     pytest.mark.skipif(
    config.DILL_VERSION <= version.parse('''0.3.2'''),
    reason='''test requires dill>0.3.2 for cloudpickle compatibility''',
)

# Windows
__A      		=     pytest.mark.skipif(
    sys.platform == '''win32''',
    reason='''test should not be run on Windows''',
)



def 				snake_case_(_UpperCamelCase					)							->     int:



  """simple docstring"""






  try:
    import faiss  # noqa
  except ImportError:
    _snake_case						=							unittest.skip('''test requires faiss'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     Tuple:



  """simple docstring"""






  try:
    import regex  # noqa
  except ImportError:
    _snake_case						=							unittest.skip('''test requires regex'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     Optional[int]:



  """simple docstring"""






  try:
    import elasticsearch  # noqa
  except ImportError:
    _snake_case						=							unittest.skip('''test requires elasticsearch'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     Optional[Any]:



  """simple docstring"""






  try:
    import sqlalchemy  # noqa
  except ImportError:
    _snake_case						=							unittest.skip('''test requires sqlalchemy'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     str:



  """simple docstring"""






  if not config.TORCH_AVAILABLE:
    _snake_case						=							unittest.skip('''test requires PyTorch'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     List[Any]:



  """simple docstring"""






  if not config.TF_AVAILABLE:
    _snake_case						=							unittest.skip('''test requires TensorFlow'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     str:



  """simple docstring"""






  if not config.JAX_AVAILABLE:
    _snake_case						=							unittest.skip('''test requires JAX'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     List[Any]:



  """simple docstring"""






  if not config.PIL_AVAILABLE:
    _snake_case						=							unittest.skip('''test requires Pillow'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     Tuple:



  """simple docstring"""






  try:
    import transformers  # noqa F401
  except ImportError:
    return unittest.skip('''test requires transformers'''					)(_UpperCamelCase					)
  else:
    return test_case



def 				snake_case_(_UpperCamelCase					)							->     Tuple:



  """simple docstring"""






  try:
    import tiktoken  # noqa F401
  except ImportError:
    return unittest.skip('''test requires tiktoken'''					)(_UpperCamelCase					)
  else:
    return test_case



def 				snake_case_(_UpperCamelCase					)							->     Optional[Any]:



  """simple docstring"""






  try:
    import spacy  # noqa F401
  except ImportError:
    return unittest.skip('''test requires spacy'''					)(_UpperCamelCase					)
  else:
    return test_case



def 				snake_case_(_UpperCamelCase					)							->     Any:



  """simple docstring"""






  def _require_spacy_model(_UpperCamelCase					):
    try:
      import spacy  # noqa F401

      spacy.load(_UpperCamelCase					)
    except ImportError:
      return unittest.skip('''test requires spacy'''					)(_UpperCamelCase					)
    except OSError:
      return unittest.skip('''test requires spacy model \'{}\''''.format(_UpperCamelCase					)					)(_UpperCamelCase					)
    else:
      return test_case

  return _require_spacy_model



def 				snake_case_(_UpperCamelCase					)							->     Optional[int]:



  """simple docstring"""






  try:
    import pyspark  # noqa F401
  except ImportError:
    return unittest.skip('''test requires pyspark'''					)(_UpperCamelCase					)
  else:
    return test_case



def 				snake_case_(_UpperCamelCase					)							->     Optional[int]:



  """simple docstring"""






  try:
    import joblibspark  # noqa F401
  except ImportError:
    return unittest.skip('''test requires joblibspark'''					)(_UpperCamelCase					)
  else:
    return test_case



def 				snake_case_(_UpperCamelCase					)							->     Tuple:



  """simple docstring"""






  if not _run_slow_tests or _run_slow_tests == 0:
    _snake_case						=							unittest.skip('''test is slow'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     int:



  """simple docstring"""






  if not _run_local_tests or _run_local_tests == 0:
    _snake_case						=							unittest.skip('''test is local'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     str:



  """simple docstring"""






  if not _run_packaged_tests or _run_packaged_tests == 0:
    _snake_case						=							unittest.skip('''test is packaged'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(_UpperCamelCase					)							->     Tuple:



  """simple docstring"""






  if not _run_remote_tests or _run_remote_tests == 0:
    _snake_case						=							unittest.skip('''test requires remote'''					)(_UpperCamelCase					)
  return test_case



def 				snake_case_(*_UpperCamelCase					)							->     Any:



  """simple docstring"""






  def decorate(cls					):
    for name, fn in cls.__dict__.items():
      if callable(_UpperCamelCase					) and name.startswith('''test'''					):
        for decorator in decorators:
          _snake_case						=							decorator(_UpperCamelCase					)
        setattr(cls			,	_UpperCamelCase			,	_UpperCamelCase					)
    return cls

  return decorate



class   lowercase_   (  __lowercase					):
      pass



class   lowercase_   (  __lowercase					):
      UpperCamelCase_      :		str										=    0
      UpperCamelCase_      :		str										=    1
      UpperCamelCase_      :		Tuple										=    2



@contextmanager
def 				snake_case_(_UpperCamelCase=OfflineSimulationMode.CONNECTION_FAILS			,	_UpperCamelCase=1E-16					)							->     Union[str, Any]:



  """simple docstring"""






  _snake_case						=							requests.Session().request

  def timeout_request(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	**_UpperCamelCase					):
    # Change the url to an invalid url so that the connection hangs
    _snake_case						=							'''https://10.255.255.1'''
    if kwargs.get('''timeout'''					) is None:
      raise RequestWouldHangIndefinitelyError(
          F"""Tried a call to {url} in offline mode with no timeout set. Please set a timeout."""					)
    _snake_case						=							timeout
    try:
      return online_request(_UpperCamelCase			,	_UpperCamelCase			,	**_UpperCamelCase					)
    except Exception as e:
      # The following changes in the error are just here to make the offline timeout error prettier
      _snake_case						=							url
      _snake_case						=							e.args[0]
      _snake_case						=							(max_retry_error.args[0].replace('''10.255.255.1'''			,	F"""OfflineMock[{url}]"""					),)
      _snake_case						=							(max_retry_error,)
      raise

  def raise_connection_error(_UpperCamelCase			,	_UpperCamelCase			,	**_UpperCamelCase					):
    raise requests.ConnectionError('''Offline mode is enabled.'''			,	request=_UpperCamelCase					)

  if mode is OfflineSimulationMode.CONNECTION_FAILS:
    with patch('''requests.Session.send'''			,	_UpperCamelCase					):
      yield
  elif mode is OfflineSimulationMode.CONNECTION_TIMES_OUT:
    # inspired from https://stackoverflow.com/a/904609
    with patch('''requests.Session.request'''			,	_UpperCamelCase					):
      yield
  elif mode is OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1:
    with patch('''datasets.config.HF_DATASETS_OFFLINE'''			,	_UpperCamelCase					):
      yield
  else:
    raise ValueError('''Please use a value from the OfflineSimulationMode enum.'''					)



@contextmanager
def 				snake_case_(*_UpperCamelCase			,	**_UpperCamelCase					)							->     Dict:



  """simple docstring"""






  _snake_case						=							str(Path().resolve()					)
  with tempfile.TemporaryDirectory(*_UpperCamelCase			,	**_UpperCamelCase					) as tmp_dir:
    try:
      os.chdir(_UpperCamelCase					)
      yield
    finally:
      os.chdir(_UpperCamelCase					)



@contextmanager
def 				snake_case_()							->     Optional[Any]:



  """simple docstring"""






  import gc

  gc.collect()
  _snake_case						=							pa.total_allocated_bytes()
  yield
  assert pa.total_allocated_bytes() - previous_allocated_memory > 0, "Arrow memory didn't increase."



@contextmanager
def 				snake_case_()							->     Tuple:



  """simple docstring"""






  import gc

  gc.collect()
  _snake_case						=							pa.total_allocated_bytes()
  yield
  assert pa.total_allocated_bytes() - previous_allocated_memory <= 0, "Arrow memory wasn't expected to increase."



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase					)							->     str:



  """simple docstring"""






  return deepcopy(_UpperCamelCase					).integers(0			,	100			,	10					).tolist() == deepcopy(_UpperCamelCase					).integers(0			,	100			,	10					).tolist()



def 				snake_case_(_UpperCamelCase					)							->     Any:



  """simple docstring"""






  import decorator
  from requests.exceptions import HTTPError

  def _wrapper(_UpperCamelCase			,	*_UpperCamelCase			,	**_UpperCamelCase					):
    try:
      return func(*_UpperCamelCase			,	**_UpperCamelCase					)
    except HTTPError as err:
      if str(_UpperCamelCase					).startswith('''500'''					) or str(_UpperCamelCase					).startswith('''502'''					):
        pytest.xfail(str(_UpperCamelCase					)					)
      raise err

  return decorator.decorator(_wrapper			,	_UpperCamelCase					)



class   lowercase_   :



      def __init__(      self				:    Optional[Any]      , A__				:    str      , A__				:    List[str]      , A__				:    int		)   ->					str:
        _snake_case						=							returncode
        _snake_case						=							stdout
        _snake_case						=							stderr



async def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase					)							->     Dict:



  """simple docstring"""






  while True:
    _snake_case						=							await stream.readline()
    if line:
      callback(_UpperCamelCase					)
    else:
      break



async def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase=None			,	_UpperCamelCase=None			,	_UpperCamelCase=None			,	_UpperCamelCase=False			,	_UpperCamelCase=False					)							->     _RunOutput:



  """simple docstring"""






  if echo:
    print('''\nRunning: '''			,	''' '''.join(_UpperCamelCase					)					)

  _snake_case						=							await asyncio.create_subprocess_exec(
      cmd[0]			,	*cmd[1:]			,	stdin=_UpperCamelCase			,	stdout=asyncio.subprocess.PIPE			,	stderr=asyncio.subprocess.PIPE			,	env=_UpperCamelCase			,	)

  # note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
  # https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
  #
  # If it starts hanging, will need to switch to the following code. The problem is that no data
  # will be seen until it's done and if it hangs for example there will be no debug info.
  # out, err = await p.communicate()
  # return _RunOutput(p.returncode, out, err)

  _snake_case						=							[]
  _snake_case						=							[]

  def tee(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase=""					):
    _snake_case						=							line.decode('''utf-8'''					).rstrip()
    sink.append(_UpperCamelCase					)
    if not quiet:
      print(_UpperCamelCase			,	_UpperCamelCase			,	file=_UpperCamelCase					)

    # XXX: the timeout doesn't seem to make any difference here
  await asyncio.wait(
      [
          _read_stream(p.stdout			,	lambda _UpperCamelCase					: tee(_UpperCamelCase			,	_UpperCamelCase			,	sys.stdout			,	label='''stdout:'''					)					),
          _read_stream(p.stderr			,	lambda _UpperCamelCase					: tee(_UpperCamelCase			,	_UpperCamelCase			,	sys.stderr			,	label='''stderr:'''					)					),
      ]			,	timeout=_UpperCamelCase			,	)
  return _RunOutput(await p.wait()			,	_UpperCamelCase			,	_UpperCamelCase					)



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase=None			,	_UpperCamelCase=None			,	_UpperCamelCase=180			,	_UpperCamelCase=False			,	_UpperCamelCase=True					)							->     _RunOutput:



  """simple docstring"""






  _snake_case						=							asyncio.get_event_loop()
  _snake_case						=							loop.run_until_complete(
      _stream_subprocess(_UpperCamelCase			,	env=_UpperCamelCase			,	stdin=_UpperCamelCase			,	timeout=_UpperCamelCase			,	quiet=_UpperCamelCase			,	echo=_UpperCamelCase					)					)

  _snake_case						=							''' '''.join(_UpperCamelCase					)
  if result.returncode > 0:
    _snake_case						=							'''\n'''.join(result.stderr					)
    raise RuntimeError(
        F"""'{cmd_str}' failed with returncode {result.returncode}\n\n"""
        F"""The combined stderr from workers follows:\n{stderr}"""					)

  # check that the subprocess actually did run and produced some output, should the test rely on
  # the remote side to do the testing
  if not result.stdout and not result.stderr:
    raise RuntimeError(F"""'{cmd_str}' produced no output."""					)

  return result



def 				snake_case_()							->     Dict:



  """simple docstring"""






  _snake_case						=							os.environ.get('''PYTEST_XDIST_WORKER'''			,	'''gw0'''					)
  _snake_case						=							re.sub(R'''^gw'''			,	''''''			,	_UpperCamelCase			,	0			,	re.M					)
  return int(_UpperCamelCase					)



def 				snake_case_()							->     int:



  """simple docstring"""






  _snake_case						=							29_500
  _snake_case						=							pytest_xdist_worker_id()
  return port + uniq_delta




import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging


__A      		=     logging.get_logger(__name__)

__A      		=     '''▁'''

__A      		=     {
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__A      		=     {
    '''vocab_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json''',
    },
    '''spm_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_config_file''': {
        '''facebook/m2m100_418M''': '''https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json''',
        '''facebook/m2m100_1.2B''': '''https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json''',
    },
}

__A      		=     {
    '''facebook/m2m100_418M''': 10_24,
}

# fmt: off
__A      		=     {
    '''m2m100''': ['''af''', '''am''', '''ar''', '''ast''', '''az''', '''ba''', '''be''', '''bg''', '''bn''', '''br''', '''bs''', '''ca''', '''ceb''', '''cs''', '''cy''', '''da''', '''de''', '''el''', '''en''', '''es''', '''et''', '''fa''', '''ff''', '''fi''', '''fr''', '''fy''', '''ga''', '''gd''', '''gl''', '''gu''', '''ha''', '''he''', '''hi''', '''hr''', '''ht''', '''hu''', '''hy''', '''id''', '''ig''', '''ilo''', '''is''', '''it''', '''ja''', '''jv''', '''ka''', '''kk''', '''km''', '''kn''', '''ko''', '''lb''', '''lg''', '''ln''', '''lo''', '''lt''', '''lv''', '''mg''', '''mk''', '''ml''', '''mn''', '''mr''', '''ms''', '''my''', '''ne''', '''nl''', '''no''', '''ns''', '''oc''', '''or''', '''pa''', '''pl''', '''ps''', '''pt''', '''ro''', '''ru''', '''sd''', '''si''', '''sk''', '''sl''', '''so''', '''sq''', '''sr''', '''ss''', '''su''', '''sv''', '''sw''', '''ta''', '''th''', '''tl''', '''tn''', '''tr''', '''uk''', '''ur''', '''uz''', '''vi''', '''wo''', '''xh''', '''yi''', '''yo''', '''zh''', '''zu'''],
    '''wmt21''': ['''en''', '''ha''', '''is''', '''ja''', '''cs''', '''ru''', '''zh''', '''de''']
}



class   lowercase_   (  __lowercase					):
      UpperCamelCase_      :		str										=    VOCAB_FILES_NAMES
      UpperCamelCase_      :		Optional[int]										=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase_      :		Dict										=    PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase_      :		Union[str, Any]										=    ["input_ids", "attention_mask"]

      UpperCamelCase_      :		List[int]										=    []
      UpperCamelCase_      :		List[int]										=    []



      def __init__(      self				:    str      , A__				:    str      , A__				:    Optional[Any]      , A__				:    Union[str, Any]=None      , A__				:    Dict=None      , A__				:    Any="<s>"      , A__				:    Union[str, Any]="</s>"      , A__				:    Tuple="</s>"      , A__				:    Dict="<pad>"      , A__				:    List[Any]="<unk>"      , A__				:    str="m2m100"      , A__				:    Optional[Dict[str, Any]] = None      , A__				:    List[Any]=8      , **A__				:    Union[str, Any]      , )   ->					None:
        _snake_case						=							{} if sp_model_kwargs is None else sp_model_kwargs

        _snake_case						=							language_codes
        _snake_case						=							FAIRSEQ_LANGUAGE_CODES[language_codes]
        _snake_case						=							{lang_code: f"""__{lang_code}__""" for lang_code in fairseq_language_code}

        _snake_case						=							kwargs.get('''additional_special_tokens'''      , []		)
        kwargs["additional_special_tokens"] += [
            self.get_lang_token(A__		)
            for lang_code in fairseq_language_code
            if self.get_lang_token(A__		) not in kwargs["additional_special_tokens"]
        ]

        super().__init__(
            src_lang=A__      , tgt_lang=A__      , bos_token=A__      , eos_token=A__      , sep_token=A__      , unk_token=A__      , pad_token=A__      , language_codes=A__      , sp_model_kwargs=self.sp_model_kwargs      , num_madeup_words=A__      , **A__      , )

        _snake_case						=							vocab_file
        _snake_case						=							load_json(A__		)
        _snake_case						=							{v: k for k, v in self.encoder.items()}
        _snake_case						=							spm_file
        _snake_case						=							load_spm(A__      , self.sp_model_kwargs		)

        _snake_case						=							len(self.encoder		)

        _snake_case						=							{
            self.get_lang_token(A__		): self.encoder_size + i for i, lang_code in enumerate(A__		)
        }
        _snake_case						=							{lang_code: self.encoder_size + i for i, lang_code in enumerate(A__		)}
        _snake_case						=							{v: k for k, v in self.lang_token_to_id.items()}

        _snake_case						=							src_lang if src_lang is not None else '''en'''
        _snake_case						=							tgt_lang
        _snake_case						=							self.get_lang_id(self._src_lang		)
        self.set_src_lang_special_tokens(self._src_lang		)

        _snake_case						=							num_madeup_words



      @property
      def 						UpperCamelCase_		(      self				:    int		)   ->					int:
        return len(self.encoder		) + len(self.lang_token_to_id		)



      @property
      def 						UpperCamelCase_		(      self				:    Dict		)   ->					str:
        return self._src_lang



      @src_lang.setter
      def 						UpperCamelCase_		(      self				:    List[str]      , A__				:    str		)   ->					None:
        _snake_case						=							new_src_lang
        self.set_src_lang_special_tokens(self._src_lang		)



      def 						UpperCamelCase_		(      self				:    Any      , A__				:    str		)   ->					List[str]:
        return self.sp_model.encode(A__      , out_type=A__		)



      def 						UpperCamelCase_		(      self				:    Optional[int]      , A__				:    Dict		)   ->					str:
        if token in self.lang_token_to_id:
          return self.lang_token_to_id[token]
        return self.encoder.get(A__      , self.encoder[self.unk_token]		)



      def 						UpperCamelCase_		(      self				:    Union[str, Any]      , A__				:    int		)   ->					str:
        if index in self.id_to_lang_token:
          return self.id_to_lang_token[index]
        return self.decoder.get(A__      , self.unk_token		)



      def 						UpperCamelCase_		(      self				:    Optional[int]      , A__				:    Optional[int]		)   ->					List[Any]:
        _snake_case						=							[]
        _snake_case						=							''''''
        for token in tokens:
          # make sure that special tokens are not decoded using sentencepiece model
          if token in self.all_special_tokens:
            out_string += self.sp_model.decode(A__		) + token
            _snake_case						=							[]
          else:
            current_sub_tokens.append(A__		)
        out_string += self.sp_model.decode(A__		)
        return out_string.strip()



      def 						UpperCamelCase_		(      self				:    str      , A__				:    List[int]      , A__				:    Optional[List[int]] = None      , A__				:    bool = False		)   ->					List[int]:

        if already_has_special_tokens:
          return super().get_special_tokens_mask(
              token_ids_a=A__      , token_ids_a=A__      , already_has_special_tokens=A__		)

        _snake_case						=							[1] * len(self.prefix_tokens		)
        _snake_case						=							[1] * len(self.suffix_tokens		)
        if token_ids_a is None:
          return prefix_ones + ([0] * len(A__		)) + suffix_ones
        return prefix_ones + ([0] * len(A__		)) + ([0] * len(A__		)) + suffix_ones



      def 						UpperCamelCase_		(      self				:    Tuple      , A__				:    List[int]      , A__				:    Optional[List[int]] = None		)   ->					List[int]:
        if token_ids_a is None:
          return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens



      def 						UpperCamelCase_		(      self				:    str		)   ->					Dict:
        _snake_case						=							{self.convert_ids_to_tokens(A__		): i for i in range(self.vocab_size		)}
        vocab.update(self.added_tokens_encoder		)
        return vocab



      def __getstate__(      self				:    str		)   ->					Dict:
        _snake_case						=							self.__dict__.copy()
        _snake_case						=							None
        return state



      def __setstate__(      self				:    Union[str, Any]      , A__				:    Dict		)   ->					None:
        _snake_case						=							d

        # for backward compatibility
        if not hasattr(self      , '''sp_model_kwargs'''		):
          _snake_case						=							{}

        _snake_case						=							load_spm(self.spm_file      , self.sp_model_kwargs		)



      def 						UpperCamelCase_		(      self				:    Any      , A__				:    str      , A__				:    Optional[str] = None		)   ->					Tuple[str]:
        _snake_case						=							Path(A__		)
        if not save_dir.is_dir():
          raise OSError(f"""{save_directory} should be a directory"""		)
        _snake_case						=							save_dir / (
            (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''vocab_file''']
        )
        _snake_case						=							save_dir / (
            (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''spm_file''']
        )

        save_json(self.encoder      , A__		)

        if os.path.abspath(self.spm_file		) != os.path.abspath(A__		) and os.path.isfile(self.spm_file		):
          copyfile(self.spm_file      , A__		)
        elif not os.path.isfile(self.spm_file		):
          with open(A__      , '''wb'''		) as fi:
            _snake_case						=							self.sp_model.serialized_model_proto()
            fi.write(A__		)

        return (str(A__		), str(A__		))



      def 						UpperCamelCase_		(      self				:    Optional[int]      , A__				:    List[str]      , A__				:    str = "en"      , A__				:    Optional[List[str]] = None      , A__				:    str = "ro"      , **A__				:    List[Any]      , )   ->					BatchEncoding:
        _snake_case						=							src_lang
        _snake_case						=							tgt_lang
        self.set_src_lang_special_tokens(self.src_lang		)
        return super().prepare_seqaseq_batch(A__      , A__      , **A__		)



      def 						UpperCamelCase_		(      self				:    List[str]      , A__				:    int      , A__				:    Optional[str]      , A__				:    Optional[str]      , **A__				:    Union[str, Any]		)   ->					Tuple:
        if src_lang is None or tgt_lang is None:
          raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''		)
        _snake_case						=							src_lang
        _snake_case						=							self(A__      , add_special_tokens=A__      , **A__		)
        _snake_case						=							self.get_lang_id(A__		)
        _snake_case						=							tgt_lang_id
        return inputs



      def 						UpperCamelCase_		(      self				:    Dict		)   ->					Optional[Any]:
        self.set_src_lang_special_tokens(self.src_lang		)



      def 						UpperCamelCase_		(      self				:    Optional[Any]		)   ->					Dict:
        self.set_tgt_lang_special_tokens(self.tgt_lang		)



      def 						UpperCamelCase_		(      self				:    List[Any]      , A__				:    str		)   ->					None:
        _snake_case						=							self.get_lang_token(A__		)
        _snake_case						=							self.lang_token_to_id[lang_token]
        _snake_case						=							[self.cur_lang_id]
        _snake_case						=							[self.eos_token_id]



      def 						UpperCamelCase_		(      self				:    List[str]      , A__				:    str		)   ->					None:
        _snake_case						=							self.get_lang_token(A__		)
        _snake_case						=							self.lang_token_to_id[lang_token]
        _snake_case						=							[self.cur_lang_id]
        _snake_case						=							[self.eos_token_id]



      def 						UpperCamelCase_		(      self				:    Dict      , A__				:    str		)   ->					str:
        return self.lang_code_to_token[lang]







      def 						UpperCamelCase_		(      self				:    Tuple      , A__				:    str		)   ->					int:
        _snake_case						=							self.get_lang_token(A__		)
        return self.lang_token_to_id[lang_token]



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase					)							->     sentencepiece.SentencePieceProcessor:



  """simple docstring"""






  _snake_case						=							sentencepiece.SentencePieceProcessor(**_UpperCamelCase					)
  spm.Load(str(_UpperCamelCase					)					)
  return spm



def 				snake_case_(_UpperCamelCase					)							->     Union[Dict, List]:



  """simple docstring"""






  with open(_UpperCamelCase			,	'''r'''					) as f:
    return json.load(_UpperCamelCase					)



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase					)							->     None:



  """simple docstring"""






  with open(_UpperCamelCase			,	'''w'''					) as f:
    json.dump(_UpperCamelCase			,	_UpperCamelCase			,	indent=2					)

