






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__	:			Optional[int]			   = logging.get_logger(__name__)

A__	:			Dict			   = '▁'

A__	:			Tuple			   = {'vocab_file': 'sentencepiece.bpe.model'}

A__	:			Tuple			   = {
    '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'
        ),
    }
}

A__	:			List[str]			   = {
    'facebook/mbart-large-50-one-to-many-mmt': 10_24,
}

# fmt: off
A__	:			List[str]			   = ['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       _UpperCAmelCase					(       A__	):

				"""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						:    int,  lowerCamelCase						:    List[Any],  lowerCamelCase						:    str=None,  lowerCamelCase						:    Tuple=None,  lowerCamelCase						:    Tuple="</s>",  lowerCamelCase						:    List[str]="</s>",  lowerCamelCase						:    Tuple="<s>",  lowerCamelCase						:    Tuple="<unk>",  lowerCamelCase						:    Any="<pad>",  lowerCamelCase						:    Optional[int]="<mask>",  lowerCamelCase						:    Optional[Dict[str, Any]] = None,  **lowerCamelCase						:    Any,  ):

								'''simple docstring'''
								# Mask token behave like a normal word, i.e. include the space before it
								lowercase__    =			AddedToken(lowerCamelCase,  lstrip=lowerCamelCase,  rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,  lowerCamelCase  ) else mask_token

								lowercase__    =			{} if sp_model_kwargs is None else sp_model_kwargs

								lowercase__    =			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=lowerCamelCase,  tgt_lang=lowerCamelCase,  eos_token=lowerCamelCase,  unk_token=lowerCamelCase,  sep_token=lowerCamelCase,  cls_token=lowerCamelCase,  pad_token=lowerCamelCase,  mask_token=lowerCamelCase,  sp_model_kwargs=self.sp_model_kwargs,  **lowerCamelCase,  )

								lowercase__    =			spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(str(lowerCamelCase  )  )
								lowercase__    =			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
								lowercase__    =			{'''<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
								lowercase__    =			1

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

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

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




				@property
				def 				lowercase__   (     self						:    Tuple  ):

								'''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 				lowercase__   (     self						:    Optional[Any]  ):

								'''simple docstring'''
								return self._src_lang




				@src_lang.setter
				def 				lowercase__   (     self						:    Optional[int],  lowerCamelCase						:    str  ):

								'''simple docstring'''
								lowercase__    =			new_src_lang
								self.set_src_lang_special_tokens(self._src_lang  )




				def __getstate__(     self						:    Tuple  ):

								'''simple docstring'''
								lowercase__    =			self.__dict__.copy()
								lowercase__    =			None
								return state




				def __setstate__(     self						:    Dict,  lowerCamelCase						:    Dict  ):

								'''simple docstring'''
								lowercase__    =			d

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

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




				def 				lowercase__   (     self						:    Optional[int]  ):

								'''simple docstring'''
								lowercase__    =			{self.convert_ids_to_tokens(lowerCamelCase  ): i for i in range(self.vocab_size  )}
								vocab.update(self.added_tokens_encoder  )
								return vocab




				def 				lowercase__   (     self						:    Any,  lowerCamelCase						:    str  ):

								'''simple docstring'''
								return self.sp_model.encode(lowerCamelCase,  out_type=lowerCamelCase  )




				def 				lowercase__   (     self						:    List[str],  lowerCamelCase						:    str  ):

								'''simple docstring'''
								if token in self.fairseq_tokens_to_ids:
												return self.fairseq_tokens_to_ids[token]
								lowercase__    =			self.sp_model.PieceToId(lowerCamelCase  )

								# 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 				lowercase__   (     self						:    Dict,  lowerCamelCase						:    int  ):

								'''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 				lowercase__   (     self						:    Dict,  lowerCamelCase						:    Tuple  ):

								'''simple docstring'''
								lowercase__    =			[]
								lowercase__    =			''''''
								lowercase__    =			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(lowerCamelCase  ) + token
																lowercase__    =			True
																lowercase__    =			[]
												else:
																current_sub_tokens.append(lowerCamelCase  )
																lowercase__    =			False
								out_string += self.sp_model.decode(lowerCamelCase  )
								return out_string.strip()




				def 				lowercase__   (     self						:    Tuple,  lowerCamelCase						:    str,  lowerCamelCase						:    Optional[str] = None  ):

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

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

								return (out_vocab_file,)




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

								'''simple docstring'''

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

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




				def 				lowercase__   (     self						:    Optional[Any],  lowerCamelCase						:    List[int],  lowerCamelCase						:    Optional[List[int]] = None  ):

								'''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 				lowercase__   (     self						:    Tuple,  lowerCamelCase						:    List[str],  lowerCamelCase						:    str,  lowerCamelCase						:    Optional[str],  lowerCamelCase						:    Optional[str],  **lowerCamelCase						:    Optional[int]  ):

								'''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'''  )
								lowercase__    =			src_lang
								lowercase__    =			self(lowerCamelCase,  add_special_tokens=lowerCamelCase,  return_tensors=lowerCamelCase,  **lowerCamelCase  )
								lowercase__    =			self.convert_tokens_to_ids(lowerCamelCase  )
								lowercase__    =			tgt_lang_id
								return inputs




				def 				lowercase__   (     self						:    List[Any],  lowerCamelCase						:    List[str],  lowerCamelCase						:    str = "en_XX",  lowerCamelCase						:    Optional[List[str]] = None,  lowerCamelCase						:    str = "ro_RO",  **lowerCamelCase						:    Optional[int],  ):

								'''simple docstring'''
								lowercase__    =			src_lang
								lowercase__    =			tgt_lang
								return super().prepare_seqaseq_batch(lowerCamelCase,  lowerCamelCase,  **lowerCamelCase  )




				def 				lowercase__   (     self						:    Tuple  ):

								'''simple docstring'''
								return self.set_src_lang_special_tokens(self.src_lang  )




				def 				lowercase__   (     self						:    str  ):

								'''simple docstring'''
								return self.set_tgt_lang_special_tokens(self.tgt_lang  )




				def 				lowercase__   (     self						:    List[Any],  lowerCamelCase						:    str  ):

								'''simple docstring'''
								lowercase__    =			self.lang_code_to_id[src_lang]
								lowercase__    =			[self.cur_lang_code_id]
								lowercase__    =			[self.eos_token_id]




				def 				lowercase__   (     self						:    str,  lowerCamelCase						:    str  ):

								'''simple docstring'''
								lowercase__    =			self.lang_code_to_id[tgt_lang]
								lowercase__    =			[self.cur_lang_code_id]
								lowercase__    =			[self.eos_token_id]












import json
import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin
class       _UpperCAmelCase					(       A__		,unittest.TestCase	):

				"""simple docstring"""




				lowercase__											=       CTRLTokenizer
				lowercase__											=       False
				lowercase__											=       False




				def 				lowercase__   (     self						:    Union[str, Any]  ):

								'''simple docstring'''
								super().setUp()

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

								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(lowerCamelCase  ) + '''\n'''  )
								with open(self.merges_file,  '''w''',  encoding='''utf-8'''  ) as fp:
												fp.write('''\n'''.join(lowerCamelCase  )  )




				def 				lowercase__   (     self						:    Union[str, Any],  **lowerCamelCase						:    Dict  ):

								'''simple docstring'''
								kwargs.update(self.special_tokens_map  )
								return CTRLTokenizer.from_pretrained(self.tmpdirname,  **lowerCamelCase  )




				def 				lowercase__   (     self						:    Dict,  lowerCamelCase						:    Optional[int]  ):

								'''simple docstring'''
								lowercase__    =			'''adapt react readapt apt'''
								lowercase__    =			'''adapt react readapt apt'''
								return input_text, output_text




				def 				lowercase__   (     self						:    Tuple  ):

								'''simple docstring'''
								lowercase__    =			CTRLTokenizer(self.vocab_file,  self.merges_file,  **self.special_tokens_map  )
								lowercase__    =			'''adapt react readapt apt'''
								lowercase__    =			'''adapt re@@ a@@ c@@ t re@@ adapt apt'''.split()
								lowercase__    =			tokenizer.tokenize(lowerCamelCase  )
								self.assertListEqual(lowerCamelCase,  lowerCamelCase  )

								lowercase__    =			tokens + [tokenizer.unk_token]

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




