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


SCREAMING_SNAKE_CASE			:						str				  =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			:						List[str]				  =		"""▁"""

SCREAMING_SNAKE_CASE			:						Optional[int]				  =		{"""vocab_file""": """sentencepiece.bpe.model"""}

SCREAMING_SNAKE_CASE			:						str				  =		{
    """vocab_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

SCREAMING_SNAKE_CASE			:						List[Any]				  =		{
    """facebook/mbart-large-50-one-to-many-mmt""": 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE			:						Any				  =		["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN""", """af_ZA""", """az_AZ""", """bn_IN""", """fa_IR""", """he_IL""", """hr_HR""", """id_ID""", """ka_GE""", """km_KH""", """mk_MK""", """ml_IN""", """mn_MN""", """mr_IN""", """pl_PL""", """ps_AF""", """pt_XX""", """sv_SE""", """sw_KE""", """ta_IN""", """te_IN""", """th_TH""", """tl_XX""", """uk_UA""", """ur_PK""", """xh_ZA""", """gl_ES""", """sl_SI"""]
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      VOCAB_FILES_NAMES
  _SCREAMING_SNAKE_CASE     					=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _SCREAMING_SNAKE_CASE     					=      PRETRAINED_VOCAB_FILES_MAP
  _SCREAMING_SNAKE_CASE     					=      ["""input_ids""", """attention_mask"""]

  _SCREAMING_SNAKE_CASE     					=      []
  _SCREAMING_SNAKE_CASE     					=      []

  def __init__(		self			:   Union[str, Any]  ,				__SCREAMING_SNAKE_CASE			:   List[Any]  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=None  ,				__SCREAMING_SNAKE_CASE			:   str=None  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]="</s>"  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]="</s>"  ,				__SCREAMING_SNAKE_CASE			:   Tuple="<s>"  ,				__SCREAMING_SNAKE_CASE			:   List[str]="<unk>"  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]="<pad>"  ,				__SCREAMING_SNAKE_CASE			:   Any="<mask>"  ,				__SCREAMING_SNAKE_CASE			:   Optional[Dict[str, Any]] = None  ,				**__SCREAMING_SNAKE_CASE			:   Tuple  ,				):
   # Mask token behave like a normal word, i.e. include the space before it
   __a							=	AddedToken(__SCREAMING_SNAKE_CASE  ,				lstrip=__SCREAMING_SNAKE_CASE  ,				rstrip=__SCREAMING_SNAKE_CASE							) if isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							) else mask_token

   __a							=	{} if sp_model_kwargs is None else sp_model_kwargs

   __a							=	kwargs.get("additional_special_tokens"  ,				[]							)
   kwargs["additional_special_tokens"] += [
       code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
   ]

   super().__init__(
       src_lang=__SCREAMING_SNAKE_CASE  ,				tgt_lang=__SCREAMING_SNAKE_CASE  ,				eos_token=__SCREAMING_SNAKE_CASE  ,				unk_token=__SCREAMING_SNAKE_CASE  ,				sep_token=__SCREAMING_SNAKE_CASE  ,				cls_token=__SCREAMING_SNAKE_CASE  ,				pad_token=__SCREAMING_SNAKE_CASE  ,				mask_token=__SCREAMING_SNAKE_CASE  ,				sp_model_kwargs=self.sp_model_kwargs  ,				**__SCREAMING_SNAKE_CASE  ,				)

   __a							=	spm.SentencePieceProcessor(**self.sp_model_kwargs							)
   self.sp_model.Load(str(__SCREAMING_SNAKE_CASE							)							)
   __a							=	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>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
   # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

   # Mimic fairseq token-to-id alignment for the first 4 token
   __a							=	{"<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
   __a							=	1

   __a							=	len(self.sp_model							)
   __a							=	{
       code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__SCREAMING_SNAKE_CASE							)
   }
   __a							=	{v: k for k, v in self.lang_code_to_id.items()}
   __a							=	len(self.sp_model							) + len(self.lang_code_to_id							) + self.fairseq_offset

   self.fairseq_tokens_to_ids.update(self.lang_code_to_id							)
   __a							=	{v: k for k, v in self.fairseq_tokens_to_ids.items()}

   __a							=	src_lang if src_lang is not None else "en_XX"
   __a							=	self.lang_code_to_id[self._src_lang]
   __a							=	tgt_lang
   self.set_src_lang_special_tokens(self._src_lang							)

  @property
  def 		_UpperCAmelCase (		self			:   Optional[Any]							):
   return len(self.sp_model							) + len(self.lang_code_to_id							) + self.fairseq_offset + 1  # Plus 1 for the mask token

  @property
  def 		_UpperCAmelCase (		self			:   List[str]							):
   return self._src_lang

  @src_lang.setter
  def 		_UpperCAmelCase (		self			:   int  ,				__SCREAMING_SNAKE_CASE			:   str							):
   __a							=	new_src_lang
   self.set_src_lang_special_tokens(self._src_lang							)

  def __getstate__(		self			:   List[str]							):
   __a							=	self.__dict__.copy()
   __a							=	None
   return state

  def __setstate__(		self			:   Optional[int]  ,				__SCREAMING_SNAKE_CASE			:   Dict							):
   __a							=	d

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

   __a							=	spm.SentencePieceProcessor(**self.sp_model_kwargs							)
   self.sp_model.Load(self.vocab_file							)

  def 		_UpperCAmelCase (		self			:   Any							):
   __a							=	{self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE							): i for i in range(self.vocab_size							)}
   vocab.update(self.added_tokens_encoder							)
   return vocab

  def 		_UpperCAmelCase (		self			:   List[str]  ,				__SCREAMING_SNAKE_CASE			:   str							):
   return self.sp_model.encode(__SCREAMING_SNAKE_CASE  ,				out_type=__SCREAMING_SNAKE_CASE							)

  def 		_UpperCAmelCase (		self			:   Union[str, Any]  ,				__SCREAMING_SNAKE_CASE			:   str							):
   if token in self.fairseq_tokens_to_ids:
    return self.fairseq_tokens_to_ids[token]
   __a							=	self.sp_model.PieceToId(__SCREAMING_SNAKE_CASE							)

   # 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 		_UpperCAmelCase (		self			:   List[str]  ,				__SCREAMING_SNAKE_CASE			:   int							):
   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 		_UpperCAmelCase (		self			:   Dict  ,				__SCREAMING_SNAKE_CASE			:   List[str]							):
   __a							=	[]
   __a							=	""
   __a							=	False
   for token in tokens:
    # make sure that special tokens are not decoded using sentencepiece model
    if token in self.all_special_tokens:
     if not prev_is_special:
      out_string += " "
     out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE							) + token
     __a							=	True
     __a							=	[]
    else:
     current_sub_tokens.append(__SCREAMING_SNAKE_CASE							)
     __a							=	False
   out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE							)
   return out_string.strip()

  def 		_UpperCAmelCase (		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   str  ,				__SCREAMING_SNAKE_CASE			:   Optional[str] = None							):
   if not os.path.isdir(__SCREAMING_SNAKE_CASE							):
    logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
    return
   __a							=	os.path.join(
       __SCREAMING_SNAKE_CASE  ,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

   if os.path.abspath(self.vocab_file							) != os.path.abspath(__SCREAMING_SNAKE_CASE							) and os.path.isfile(self.vocab_file							):
    copyfile(self.vocab_file  ,				__SCREAMING_SNAKE_CASE							)
   elif not os.path.isfile(self.vocab_file							):
    with open(__SCREAMING_SNAKE_CASE  ,				"wb"							) as fi:
     __a							=	self.sp_model.serialized_model_proto()
     fi.write(__SCREAMING_SNAKE_CASE							)

   return (out_vocab_file,)

  def 		_UpperCAmelCase (		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   List[int]  ,				__SCREAMING_SNAKE_CASE			:   Optional[List[int]] = None  ,				__SCREAMING_SNAKE_CASE			:   bool = False							):

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

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

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

  def 		_UpperCAmelCase (		self			:   Union[str, Any]  ,				__SCREAMING_SNAKE_CASE			:   List[str]  ,				__SCREAMING_SNAKE_CASE			:   str = "en_XX"  ,				__SCREAMING_SNAKE_CASE			:   Optional[List[str]] = None  ,				__SCREAMING_SNAKE_CASE			:   str = "ro_RO"  ,				**__SCREAMING_SNAKE_CASE			:   Optional[int]  ,				):
   __a							=	src_lang
   __a							=	tgt_lang
   return super().prepare_seqaseq_batch(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE  ,				**__SCREAMING_SNAKE_CASE							)

  def 		_UpperCAmelCase (		self			:   Tuple							):
   return self.set_src_lang_special_tokens(self.src_lang							)

  def 		_UpperCAmelCase (		self			:   List[str]							):
   return self.set_tgt_lang_special_tokens(self.tgt_lang							)

  def 		_UpperCAmelCase (		self			:   List[str]  ,				__SCREAMING_SNAKE_CASE			:   str							):
   __a							=	self.lang_code_to_id[src_lang]
   __a							=	[self.cur_lang_code_id]
   __a							=	[self.eos_token_id]

  def 		_UpperCAmelCase (		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   str							):
   __a							=	self.lang_code_to_id[tgt_lang]
   __a							=	[self.cur_lang_code_id]
   __a							=	[self.eos_token_id]



# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def 	__A		(      ):



 """simple docstring"""


 __a							=	ArgumentParser("Accelerate CLI tool"				,					usage="accelerate <command> [<args>]"				,					allow_abbrev=_A       )
 __a							=	parser.add_subparsers(help="accelerate command helpers"       )

 # Register commands
 get_config_parser(subparsers=_A       )
 env_command_parser(subparsers=_A       )
 launch_command_parser(subparsers=_A       )
 tpu_command_parser(subparsers=_A       )
 test_command_parser(subparsers=_A       )

 # Let's go
 __a							=	parser.parse_args()

 if not hasattr(_A				,					"func"       ):
  parser.print_help()
  exit(1       )

 # Run
 args.func(_A       )


if __name__ == "__main__":
  main()


