





import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		Union[str, Any]:







  """simple docstring"""





  lowerCamelCase__:				Tuple        =None
  if token is not None:
    lowerCamelCase__:				List[Any]        ={"Accept": "application/vnd.github+json", "Authorization": F"""Bearer {token}"""}

  lowerCamelCase__:				Tuple        =F"""https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"""
  lowerCamelCase__:				List[str]        =requests.get(__a     ,   headers=__a		).json()
  lowerCamelCase__:				Dict        ={}

  try:
    job_links.update({job["name"]: job["html_url"] for job in result["jobs"]}		)
    lowerCamelCase__:				Any        =math.ceil((result["total_count"] - 100) / 100		)

    for i in range(__a		):
      lowerCamelCase__:				int        =requests.get(url + F"""&page={i + 2}"""     ,   headers=__a		).json()
      job_links.update({job["name"]: job["html_url"] for job in result["jobs"]}		)

    return job_links
  except Exception:
    print(F"""Unknown error, could not fetch links:\n{traceback.format_exc()}"""		)

  return {}





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		Dict:







  """simple docstring"""





  lowerCamelCase__:				Tuple        =None
  if token is not None:
    lowerCamelCase__:				Optional[Any]        ={"Accept": "application/vnd.github+json", "Authorization": F"""Bearer {token}"""}

  lowerCamelCase__:				Optional[Any]        =F"""https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"""
  lowerCamelCase__:				List[Any]        =requests.get(__a     ,   headers=__a		).json()
  lowerCamelCase__:				Optional[Any]        ={}

  try:
    artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]}		)
    lowerCamelCase__:				Dict        =math.ceil((result["total_count"] - 100) / 100		)

    for i in range(__a		):
      lowerCamelCase__:				Dict        =requests.get(url + F"""&page={i + 2}"""     ,   headers=__a		).json()
      artifacts.update({artifact["name"]: artifact["archive_download_url"] for artifact in result["artifacts"]}		)

    return artifacts
  except Exception:
    print(F"""Unknown error, could not fetch links:\n{traceback.format_exc()}"""		)

  return {}





def 					lowerCAmelCase_			(	__a     ,   __a     ,   __a     ,   __a		)					->		Dict:







  """simple docstring"""





  lowerCamelCase__:				List[Any]        =None
  if token is not None:
    lowerCamelCase__:				int        ={"Accept": "application/vnd.github+json", "Authorization": F"""Bearer {token}"""}

  lowerCamelCase__:				Tuple        =requests.get(__a     ,   headers=__a     ,   allow_redirects=__a		)
  lowerCamelCase__:				List[Any]        =result.headers["Location"]
  lowerCamelCase__:				str        =requests.get(__a     ,   allow_redirects=__a		)
  lowerCamelCase__:				Optional[int]        =os.path.join(__a     ,   F"""{artifact_name}.zip"""		)
  with open(__a     ,   "wb"		) as fp:
    fp.write(response.content		)





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		Union[str, Any]:







  """simple docstring"""





  lowerCamelCase__:				Tuple        =[]
  lowerCamelCase__:				Tuple        =[]
  lowerCamelCase__:				int        =None

  with zipfile.ZipFile(__a		) as z:
    for filename in z.namelist():
      if not os.path.isdir(__a		):
        # read the file
        if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
          with z.open(__a		) as f:
            for line in f:
              lowerCamelCase__:				int        =line.decode("UTF-8"		).strip()
              if filename == "failures_line.txt":
                try:
                  # `error_line` is the place where `error` occurs
                  lowerCamelCase__:				Optional[int]        =line[: line.index(": "		)]
                  lowerCamelCase__:				Union[str, Any]        =line[line.index(": "		) + len(": "		) :]
                  errors.append([error_line, error]		)
                except Exception:
                  # skip un-related lines
                  pass
              elif filename == "summary_short.txt" and line.startswith("FAILED "		):
                # `test` is the test method that failed
                lowerCamelCase__:				int        =line[len("FAILED "		) :]
                failed_tests.append(__a		)
              elif filename == "job_name.txt":
                lowerCamelCase__:				Tuple        =line

  if len(__a		) != len(__a		):
    raise ValueError(
        F"""`errors` and `failed_tests` should have the same number of elements. Got {len(__a		)} for `errors` """
        F"""and {len(__a		)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some"""
        " problem."		)

  lowerCamelCase__:				int        =None
  if job_name and job_links:
    lowerCamelCase__:				Any        =job_links.get(__a     ,   __a		)

  # A list with elements of the form (line of error, error, failed test)
  lowerCamelCase__:				int        =[x + [y] + [job_link] for x, y in zip(__a     ,   __a		)]

  return result





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		int:







  """simple docstring"""





  lowerCamelCase__:				Optional[Any]        =[]

  lowerCamelCase__:				int        =[os.path.join(__a     ,   __a		) for p in os.listdir(__a		) if p.endswith(".zip"		)]
  for p in paths:
    errors.extend(get_errors_from_single_artifact(__a     ,   job_links=__a		)		)

  return errors





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		Optional[Any]:







  """simple docstring"""





  lowerCamelCase__:				Any        =Counter()
  counter.update([x[1] for x in logs]		)
  lowerCamelCase__:				str        =counter.most_common()
  lowerCamelCase__:				List[Any]        ={}
  for error, count in counts:
    if error_filter is None or error not in error_filter:
      lowerCamelCase__:				Optional[int]        ={"count": count, "failed_tests": [(x[2], x[0]) for x in logs if x[1] == error]}

  lowerCamelCase__:				Any        =dict(sorted(r.items()     ,   key=lambda __a		: item[1]["count"]     ,   reverse=__a		)		)
  return r





def 					lowerCAmelCase_			(	__a		)					->		Optional[int]:







  """simple docstring"""





  lowerCamelCase__:				str        =test.split("::"		)[0]
  if test.startswith("tests/models/"		):
    lowerCamelCase__:				Tuple        =test.split("/"		)[2]
  else:
    lowerCamelCase__:				List[str]        =None

  return test





def 					lowerCAmelCase_			(	__a     ,   __a=None		)					->		Dict:







  """simple docstring"""





  lowerCamelCase__:				Union[str, Any]        =[(x[0], x[1], get_model(x[2]		)) for x in logs]
  lowerCamelCase__:				int        =[x for x in logs if x[2] is not None]
  lowerCamelCase__:				int        ={x[2] for x in logs}

  lowerCamelCase__:				Optional[Any]        ={}
  for test in tests:
    lowerCamelCase__:				List[Any]        =Counter()
    # count by errors in `test`
    counter.update([x[1] for x in logs if x[2] == test]		)
    lowerCamelCase__:				List[str]        =counter.most_common()
    lowerCamelCase__:				Any        ={error: count for error, count in counts if (error_filter is None or error not in error_filter)}
    lowerCamelCase__:				List[str]        =sum(error_counts.values()		)
    if n_errors > 0:
      lowerCamelCase__:				str        ={"count": n_errors, "errors": error_counts}

  lowerCamelCase__:				int        =dict(sorted(r.items()     ,   key=lambda __a		: item[1]["count"]     ,   reverse=__a		)		)
  return r





def 					lowerCAmelCase_			(	__a		)					->		Any:







  """simple docstring"""





  lowerCamelCase__:				Union[str, Any]        ="| no. | error | status |"
  lowerCamelCase__:				Dict        ="|-:|:-|:-|"
  lowerCamelCase__:				str        =[header, sep]
  for error in reduced_by_error:
    lowerCamelCase__:				Optional[int]        =reduced_by_error[error]["count"]
    lowerCamelCase__:				int        =F"""| {count} | {error[:100]} |  |"""
    lines.append(__a		)

  return "\n".join(__a		)





def 					lowerCAmelCase_			(	__a		)					->		int:







  """simple docstring"""





  lowerCamelCase__:				Optional[int]        ="| model | no. of errors | major error | count |"
  lowerCamelCase__:				int        ="|-:|-:|-:|-:|"
  lowerCamelCase__:				Union[str, Any]        =[header, sep]
  for model in reduced_by_model:
    lowerCamelCase__:				List[str]        =reduced_by_model[model]["count"]
    lowerCamelCase__:				Optional[Any]        =list(reduced_by_model[model]["errors"].items()		)[0]
    lowerCamelCase__:				Dict        =F"""| {model} | {count} | {error[:60]} | {_count} |"""
    lines.append(__a		)

  return "\n".join(__a		)


if __name__ == "__main__":
    __A     =    argparse.ArgumentParser()
    # Required parameters
    parser.add_argument("--workflow_run_id", type=str, required=True, help="A GitHub Actions workflow run id.")
    parser.add_argument(
        "--output_dir",
        type=str,
        required=True,
        help="Where to store the downloaded artifacts and other result files.",
    )
    parser.add_argument("--token", default=None, type=str, help="A token that has actions:read permission.")
    __A     =    parser.parse_args()

    os.makedirs(args.output_dir, exist_ok=True)

    __A     =    get_job_links(args.workflow_run_id, token=args.token)
    __A     =    {}
    # To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
    # For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
    if _job_links:
        for k, v in _job_links.items():
            # This is how GitHub actions combine job names.
            if " / " in k:
                __A     =    k.find(" / ")
                __A     =    k[index + len(" / ") :]
            __A     =    v
    with open(os.path.join(args.output_dir, "job_links.json"), "w", encoding="UTF-8") as fp:
        json.dump(job_links, fp, ensure_ascii=False, indent=4)

    __A     =    get_artifacts_links(args.workflow_run_id, token=args.token)
    with open(os.path.join(args.output_dir, "artifacts.json"), "w", encoding="UTF-8") as fp:
        json.dump(artifacts, fp, ensure_ascii=False, indent=4)

    for idx, (name, url) in enumerate(artifacts.items()):
        download_artifact(name, url, args.output_dir, args.token)
        # Be gentle to GitHub
        time.sleep(1)

    __A     =    get_all_errors(args.output_dir, job_links=job_links)

    # `e[1]` is the error
    __A     =    Counter()
    counter.update([e[1] for e in errors])

    # print the top 30 most common test errors
    __A     =    counter.most_common(30)
    for item in most_common:
        print(item)

    with open(os.path.join(args.output_dir, "errors.json"), "w", encoding="UTF-8") as fp:
        json.dump(errors, fp, ensure_ascii=False, indent=4)

    __A     =    reduce_by_error(errors)
    __A     =    reduce_by_model(errors)

    __A     =    make_github_table(reduced_by_error)
    __A     =    make_github_table_per_model(reduced_by_model)

    with open(os.path.join(args.output_dir, "reduced_by_error.txt"), "w", encoding="UTF-8") as fp:
        fp.write(sa)
    with open(os.path.join(args.output_dir, "reduced_by_model.txt"), "w", encoding="UTF-8") as fp:
        fp.write(sa)








import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


__A     =    logging.get_logger(__name__)

__A     =    "▁"

__A     =    {"vocab_file": "sentencepiece.bpe.model"}

__A     =    {
    "vocab_file": {
        "facebook/nllb-200-distilled-600M": (
            "https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model"
        ),
    }
}

__A     =    {
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
__A     =    ["ace_Arab", "ace_Latn", "acm_Arab", "acq_Arab", "aeb_Arab", "afr_Latn", "ajp_Arab", "aka_Latn", "amh_Ethi", "apc_Arab", "arb_Arab", "ars_Arab", "ary_Arab", "arz_Arab", "asm_Beng", "ast_Latn", "awa_Deva", "ayr_Latn", "azb_Arab", "azj_Latn", "bak_Cyrl", "bam_Latn", "ban_Latn", "bel_Cyrl", "bem_Latn", "ben_Beng", "bho_Deva", "bjn_Arab", "bjn_Latn", "bod_Tibt", "bos_Latn", "bug_Latn", "bul_Cyrl", "cat_Latn", "ceb_Latn", "ces_Latn", "cjk_Latn", "ckb_Arab", "crh_Latn", "cym_Latn", "dan_Latn", "deu_Latn", "dik_Latn", "dyu_Latn", "dzo_Tibt", "ell_Grek", "eng_Latn", "epo_Latn", "est_Latn", "eus_Latn", "ewe_Latn", "fao_Latn", "pes_Arab", "fij_Latn", "fin_Latn", "fon_Latn", "fra_Latn", "fur_Latn", "fuv_Latn", "gla_Latn", "gle_Latn", "glg_Latn", "grn_Latn", "guj_Gujr", "hat_Latn", "hau_Latn", "heb_Hebr", "hin_Deva", "hne_Deva", "hrv_Latn", "hun_Latn", "hye_Armn", "ibo_Latn", "ilo_Latn", "ind_Latn", "isl_Latn", "ita_Latn", "jav_Latn", "jpn_Jpan", "kab_Latn", "kac_Latn", "kam_Latn", "kan_Knda", "kas_Arab", "kas_Deva", "kat_Geor", "knc_Arab", "knc_Latn", "kaz_Cyrl", "kbp_Latn", "kea_Latn", "khm_Khmr", "kik_Latn", "kin_Latn", "kir_Cyrl", "kmb_Latn", "kon_Latn", "kor_Hang", "kmr_Latn", "lao_Laoo", "lvs_Latn", "lij_Latn", "lim_Latn", "lin_Latn", "lit_Latn", "lmo_Latn", "ltg_Latn", "ltz_Latn", "lua_Latn", "lug_Latn", "luo_Latn", "lus_Latn", "mag_Deva", "mai_Deva", "mal_Mlym", "mar_Deva", "min_Latn", "mkd_Cyrl", "plt_Latn", "mlt_Latn", "mni_Beng", "khk_Cyrl", "mos_Latn", "mri_Latn", "zsm_Latn", "mya_Mymr", "nld_Latn", "nno_Latn", "nob_Latn", "npi_Deva", "nso_Latn", "nus_Latn", "nya_Latn", "oci_Latn", "gaz_Latn", "ory_Orya", "pag_Latn", "pan_Guru", "pap_Latn", "pol_Latn", "por_Latn", "prs_Arab", "pbt_Arab", "quy_Latn", "ron_Latn", "run_Latn", "rus_Cyrl", "sag_Latn", "san_Deva", "sat_Beng", "scn_Latn", "shn_Mymr", "sin_Sinh", "slk_Latn", "slv_Latn", "smo_Latn", "sna_Latn", "snd_Arab", "som_Latn", "sot_Latn", "spa_Latn", "als_Latn", "srd_Latn", "srp_Cyrl", "ssw_Latn", "sun_Latn", "swe_Latn", "swh_Latn", "szl_Latn", "tam_Taml", "tat_Cyrl", "tel_Telu", "tgk_Cyrl", "tgl_Latn", "tha_Thai", "tir_Ethi", "taq_Latn", "taq_Tfng", "tpi_Latn", "tsn_Latn", "tso_Latn", "tuk_Latn", "tum_Latn", "tur_Latn", "twi_Latn", "tzm_Tfng", "uig_Arab", "ukr_Cyrl", "umb_Latn", "urd_Arab", "uzn_Latn", "vec_Latn", "vie_Latn", "war_Latn", "wol_Latn", "xho_Latn", "ydd_Hebr", "yor_Latn", "yue_Hant", "zho_Hans", "zho_Hant", "zul_Latn"]



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      VOCAB_FILES_NAMES
 lowercase_		=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_		=      PRETRAINED_VOCAB_FILES_MAP
 lowercase_		=      ["input_ids", "attention_mask"]

 lowercase_		=      []
 lowercase_		=      []

 def __init__(self    :       Tuple	,			UpperCAmelCase_    :       Optional[int]	,			UpperCAmelCase_    :       Tuple="<s>"	,			UpperCAmelCase_    :       int="</s>"	,			UpperCAmelCase_    :       List[str]="</s>"	,			UpperCAmelCase_    :       List[str]="<s>"	,			UpperCAmelCase_    :       Tuple="<unk>"	,			UpperCAmelCase_    :       List[Any]="<pad>"	,			UpperCAmelCase_    :       Tuple="<mask>"	,			UpperCAmelCase_    :       Optional[int]=None	,			UpperCAmelCase_    :       Dict=None	,			UpperCAmelCase_    :       Optional[int]=None	,			UpperCAmelCase_    :       Optional[Dict[str, Any]] = None	,			UpperCAmelCase_    :       Any=None	,			UpperCAmelCase_    :       Dict=False	,			**UpperCAmelCase_    :       Tuple	,			)	->List[str]:



   '''simple docstring'''



   lowerCamelCase__:				Any        =AddedToken(UpperCAmelCase_	,			lstrip=UpperCAmelCase_	,			rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_	,			UpperCAmelCase_) else mask_token

   lowerCamelCase__:				Any        ={} if sp_model_kwargs is None else sp_model_kwargs
   lowerCamelCase__:				List[str]        =legacy_behaviour

   super().__init__(
       bos_token=UpperCAmelCase_	,			eos_token=UpperCAmelCase_	,			unk_token=UpperCAmelCase_	,			sep_token=UpperCAmelCase_	,			cls_token=UpperCAmelCase_	,			pad_token=UpperCAmelCase_	,			mask_token=UpperCAmelCase_	,			tokenizer_file=UpperCAmelCase_	,			src_lang=UpperCAmelCase_	,			tgt_lang=UpperCAmelCase_	,			additional_special_tokens=UpperCAmelCase_	,			sp_model_kwargs=self.sp_model_kwargs	,			legacy_behaviour=UpperCAmelCase_	,			**UpperCAmelCase_	,			)

   lowerCamelCase__:				Optional[Any]        =spm.SentencePieceProcessor(**self.sp_model_kwargs)
   self.sp_model.Load(str(UpperCAmelCase_))
   lowerCamelCase__:				str        =vocab_file
   # Original fairseq vocab and spm vocab must be "aligned":
   # Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
   # -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
   # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
   # spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

   # Mimic fairseq token-to-id alignment for the first 4 token
   lowerCamelCase__:				str        ={"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

   # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
   lowerCamelCase__:				List[str]        =1

   lowerCamelCase__:				Any        =len(self.sp_model)
   lowerCamelCase__:				Any        ={
       code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(UpperCAmelCase_)
   }
   lowerCamelCase__:				Dict        ={v: k for k, v in self.lang_code_to_id.items()}
   lowerCamelCase__:				Optional[int]        =len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

   self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
   lowerCamelCase__:				List[str]        ={v: k for k, v in self.fairseq_tokens_to_ids.items()}
   lowerCamelCase__:				List[str]        =list(self.lang_code_to_id.keys())

   if additional_special_tokens is not None:
     # Only add those special tokens if they are not already there.
     self._additional_special_tokens.extend(
         [t for t in additional_special_tokens if t not in self._additional_special_tokens])

   lowerCamelCase__:				int        =src_lang if src_lang is not None else "eng_Latn"
   lowerCamelCase__:				List[str]        =self.lang_code_to_id[self._src_lang]
   lowerCamelCase__:				Optional[int]        =tgt_lang
   self.set_src_lang_special_tokens(self._src_lang)

 def __getstate__(self    :       List[str])	->int:



   '''simple docstring'''



   lowerCamelCase__:				Optional[int]        =self.__dict__.copy()
   lowerCamelCase__:				Any        =None
   lowerCamelCase__:				Optional[int]        =self.sp_model.serialized_model_proto()
   return state

 def __setstate__(self    :       Dict	,			UpperCAmelCase_    :       Union[str, Any])	->Optional[int]:



   '''simple docstring'''



   lowerCamelCase__:				Dict        =d

   # for backward compatibility
   if not hasattr(self	,			"sp_model_kwargs"):
     lowerCamelCase__:				List[Any]        ={}

   lowerCamelCase__:				Dict        =spm.SentencePieceProcessor(**self.sp_model_kwargs)
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto)

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->List[str]:



   '''simple docstring'''



   return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       Dict)	->str:



   '''simple docstring'''



   return self._src_lang

 @src_lang.setter
 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int]	,			UpperCAmelCase_    :       str)	->None:



   '''simple docstring'''



   lowerCamelCase__:				Any        =new_src_lang
   self.set_src_lang_special_tokens(self._src_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None	,			UpperCAmelCase_    :       bool = False)	->List[int]:



   '''simple docstring'''



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

   lowerCamelCase__:				int        =[1] * len(self.prefix_tokens)
   lowerCamelCase__:				Any        =[1] * len(self.suffix_tokens)
   if token_ids_a is None:
     return prefix_ones + ([0] * len(UpperCAmelCase_)) + suffix_ones
   return prefix_ones + ([0] * len(UpperCAmelCase_)) + ([0] * len(UpperCAmelCase_)) + suffix_ones

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None)	->List[int]:



   '''simple docstring'''



   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 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None)	->List[int]:



   '''simple docstring'''



   lowerCamelCase__:				Any        =[self.sep_token_id]
   lowerCamelCase__:				List[str]        =[self.cls_token_id]

   if token_ids_a is None:
     return len(cls + token_ids_a + sep) * [0]
   return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       List[Any]	,			UpperCAmelCase_    :       str	,			UpperCAmelCase_    :       Optional[str]	,			UpperCAmelCase_    :       Optional[str]	,			**UpperCAmelCase_    :       Optional[int])	->Dict:



   '''simple docstring'''



   if src_lang is None or tgt_lang is None:
     raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model")
   lowerCamelCase__:				Optional[int]        =src_lang
   lowerCamelCase__:				Dict        =self(UpperCAmelCase_	,			add_special_tokens=UpperCAmelCase_	,			return_tensors=UpperCAmelCase_	,			**UpperCAmelCase_)
   lowerCamelCase__:				int        =self.convert_tokens_to_ids(UpperCAmelCase_)
   lowerCamelCase__:				Tuple        =tgt_lang_id
   return inputs

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



   '''simple docstring'''



   lowerCamelCase__:				Optional[int]        ={self.convert_ids_to_tokens(UpperCAmelCase_): i for i in range(self.vocab_size)}
   vocab.update(self.added_tokens_encoder)
   return vocab

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any]	,			UpperCAmelCase_    :       str)	->List[str]:



   '''simple docstring'''



   return self.sp_model.encode(UpperCAmelCase_	,			out_type=UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       int	,			UpperCAmelCase_    :       Union[str, Any])	->Union[str, Any]:



   '''simple docstring'''



   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   lowerCamelCase__:				Dict        =self.sp_model.PieceToId(UpperCAmelCase_)

   # Need to return unknown token if the SP model returned 0
   return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any]	,			UpperCAmelCase_    :       Optional[int])	->List[Any]:



   '''simple docstring'''



   if index in self.fairseq_ids_to_tokens:
     return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       List[Any])	->int:



   '''simple docstring'''



   lowerCamelCase__:				List[Any]        ="".join(UpperCAmelCase_).replace(UpperCAmelCase_	,			" ").strip()
   return out_string

 def 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any]	,			UpperCAmelCase_    :       str	,			UpperCAmelCase_    :       Optional[str] = None)	->Tuple[str]:



   '''simple docstring'''



   if not os.path.isdir(UpperCAmelCase_):
     logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
     return
   lowerCamelCase__:				str        =os.path.join(
       UpperCAmelCase_	,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

   if os.path.abspath(self.vocab_file) != os.path.abspath(UpperCAmelCase_) and os.path.isfile(self.vocab_file):
     copyfile(self.vocab_file	,			UpperCAmelCase_)
   elif not os.path.isfile(self.vocab_file):
     with open(UpperCAmelCase_	,			"wb") as fi:
       lowerCamelCase__:				Optional[Any]        =self.sp_model.serialized_model_proto()
       fi.write(UpperCAmelCase_)

   return (out_vocab_file,)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       List[str]	,			UpperCAmelCase_    :       str = "eng_Latn"	,			UpperCAmelCase_    :       Optional[List[str]] = None	,			UpperCAmelCase_    :       str = "fra_Latn"	,			**UpperCAmelCase_    :       Dict	,			)	->BatchEncoding:



   '''simple docstring'''



   lowerCamelCase__:				Tuple        =src_lang
   lowerCamelCase__:				Union[str, Any]        =tgt_lang
   return super().prepare_seqaseq_batch(UpperCAmelCase_	,			UpperCAmelCase_	,			**UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->Optional[Any]:



   '''simple docstring'''



   return self.set_src_lang_special_tokens(self.src_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[Any])	->int:



   '''simple docstring'''



   return self.set_tgt_lang_special_tokens(self.tgt_lang)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int]	,			UpperCAmelCase_    :       List[Any])	->None:



   '''simple docstring'''



   lowerCamelCase__:				int        =self.lang_code_to_id[src_lang]
   if self.legacy_behaviour:
     lowerCamelCase__:				Any        =[]
     lowerCamelCase__:				Tuple        =[self.eos_token_id, self.cur_lang_code]
   else:
     lowerCamelCase__:				Any        =[self.cur_lang_code]
     lowerCamelCase__:				Dict        =[self.eos_token_id]







 def 							SCREAMING_SNAKE_CASE_ (self    :       Dict	,			UpperCAmelCase_    :       str)	->None:



   '''simple docstring'''



   lowerCamelCase__:				Any        =self.lang_code_to_id[lang]
   if self.legacy_behaviour:
     lowerCamelCase__:				int        =[]
     lowerCamelCase__:				str        =[self.eos_token_id, self.cur_lang_code]
   else:
     lowerCamelCase__:				Union[str, Any]        =[self.cur_lang_code]
     lowerCamelCase__:				Optional[Any]        =[self.eos_token_id]

