


'''simple docstring'''







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


lowerCAmelCase    :     str					=						logging.get_logger(__name__)

lowerCAmelCase    :     List[Any]					=						"""▁"""

lowerCAmelCase    :     Optional[Any]					=						{"""vocab_file""": """sentencepiece.bpe.model"""}

lowerCAmelCase    :     Any					=						{
    """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"""
        ),
    }
}

lowerCAmelCase    :     int					=						{
    """facebook/mbart-large-50-one-to-many-mmt""": 10_24,
}

# fmt: off
lowerCAmelCase    :     int					=						["""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__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     __magic_name__    			=    VOCAB_FILES_NAMES
     __magic_name__    			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __magic_name__    			=    PRETRAINED_VOCAB_FILES_MAP
     __magic_name__    			=    ["input_ids", "attention_mask"]

     __magic_name__    			=    []
     __magic_name__    			=    []







     def __init__( self      ,	snake_case__      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__="</s>"      ,	snake_case__="</s>"      ,	snake_case__="<s>"      ,	snake_case__="<unk>"      ,	snake_case__="<pad>"      ,	snake_case__="<mask>"      ,	snake_case__ = None      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							str   			=       AddedToken(snake_case__      ,	lstrip=snake_case__      ,	rstrip=snake_case__   ) if isinstance(snake_case__      ,	snake_case__   ) else mask_token

            _lowerCAmelCase    :							int   			=       {} if sp_model_kwargs is None else sp_model_kwargs

            _lowerCAmelCase    :							Dict   			=       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=snake_case__      ,	tgt_lang=snake_case__      ,	eos_token=snake_case__      ,	unk_token=snake_case__      ,	sep_token=snake_case__      ,	cls_token=snake_case__      ,	pad_token=snake_case__      ,	mask_token=snake_case__      ,	sp_model_kwargs=self.sp_model_kwargs      ,	**snake_case__      ,	)

            _lowerCAmelCase    :							str   			=       spm.SentencePieceProcessor(**self.sp_model_kwargs   )
            self.sp_model.Load(str(snake_case__   )   )
            _lowerCAmelCase    :							Optional[int]   			=       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
            _lowerCAmelCase    :							Optional[int]   			=       {'<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    :							Union[str, Any]   			=       1

            _lowerCAmelCase    :							Any   			=       len(self.sp_model   )
            _lowerCAmelCase    :							int   			=       {
                code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(snake_case__   )
            }
            _lowerCAmelCase    :							str   			=       {v: k for k, v in self.lang_code_to_id.items()}
            _lowerCAmelCase    :							Union[str, Any]   			=       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    :							Tuple   			=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}

            _lowerCAmelCase    :							Any   			=       src_lang if src_lang is not None else 'en_XX'
            _lowerCAmelCase    :							Optional[Any]   			=       self.lang_code_to_id[self._src_lang]
            _lowerCAmelCase    :							Optional[int]   			=       tgt_lang
            self.set_src_lang_special_tokens(self._src_lang   )







     @property
     def a	( self   ):

            '''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 a	( self   ):

            '''simple docstring'''

            return self._src_lang







     @src_lang.setter
     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Tuple   			=       new_src_lang
            self.set_src_lang_special_tokens(self._src_lang   )







     def __getstate__( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[Any]   			=       self.__dict__.copy()
            _lowerCAmelCase    :							int   			=       None
            return state







     def __setstate__( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       d

            # for backward compatibility
            if not hasattr(self      ,	'sp_model_kwargs'   ):
                   _lowerCAmelCase    :							Optional[int]   			=       {}

            _lowerCAmelCase    :							str   			=       spm.SentencePieceProcessor(**self.sp_model_kwargs   )
            self.sp_model.Load(self.vocab_file   )







     def a	( self   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[str]   			=       {self.convert_ids_to_tokens(snake_case__   ): i for i in range(self.vocab_size   )}
            vocab.update(self.added_tokens_encoder   )
            return vocab







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

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







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            if token in self.fairseq_tokens_to_ids:
                   return self.fairseq_tokens_to_ids[token]
            _lowerCAmelCase    :							Union[str, Any]   			=       self.sp_model.PieceToId(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 a	( self      ,	snake_case__   ):

            '''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 a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[str]   			=       []
            _lowerCAmelCase    :							Dict   			=       ''
            _lowerCAmelCase    :							Optional[int]   			=       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(snake_case__   ) + token
                          _lowerCAmelCase    :							Any   			=       True
                          _lowerCAmelCase    :							Any   			=       []
                   else:
                          current_sub_tokens.append(snake_case__   )
                          _lowerCAmelCase    :							Any   			=       False
            out_string += self.sp_model.decode(snake_case__   )
            return out_string.strip()







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            if not os.path.isdir(snake_case__   ):
                   logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
                   return
            _lowerCAmelCase    :							List[Any]   			=       os.path.join(
                snake_case__      ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

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

            return (out_vocab_file,)







     def a	( self      ,	snake_case__      ,	snake_case__ = None      ,	snake_case__ = False   ):

            '''simple docstring'''

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

            _lowerCAmelCase    :							Dict   			=       [1] * len(self.prefix_tokens   )
            _lowerCAmelCase    :							Optional[Any]   			=       [1] * len(self.suffix_tokens   )
            if token_ids_a is None:
                   return prefix_ones + ([0] * len(snake_case__   )) + suffix_ones
            return prefix_ones + ([0] * len(snake_case__   )) + ([0] * len(snake_case__   )) + suffix_ones







     def a	( self      ,	snake_case__      ,	snake_case__ = 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 a	( self      ,	snake_case__      ,	snake_case__      ,	snake_case__      ,	snake_case__      ,	**snake_case__   ):

            '''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    :							str   			=       src_lang
            _lowerCAmelCase    :							Optional[Any]   			=       self(snake_case__      ,	add_special_tokens=snake_case__      ,	return_tensors=snake_case__      ,	**snake_case__   )
            _lowerCAmelCase    :							Any   			=       self.convert_tokens_to_ids(snake_case__   )
            _lowerCAmelCase    :							Dict   			=       tgt_lang_id
            return inputs







     def a	( self      ,	snake_case__      ,	snake_case__ = "en_XX"      ,	snake_case__ = None      ,	snake_case__ = "ro_RO"      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       src_lang
            _lowerCAmelCase    :							List[Any]   			=       tgt_lang
            return super().prepare_seqaseq_batch(snake_case__      ,	snake_case__      ,	**snake_case__   )







     def a	( self   ):

            '''simple docstring'''

            return self.set_src_lang_special_tokens(self.src_lang   )







     def a	( self   ):

            '''simple docstring'''

            return self.set_tgt_lang_special_tokens(self.tgt_lang   )







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[Any]   			=       self.lang_code_to_id[src_lang]
            _lowerCAmelCase    :							int   			=       [self.cur_lang_code_id]
            _lowerCAmelCase    :							List[Any]   			=       [self.eos_token_id]







     def a	( self      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Any   			=       self.lang_code_to_id[tgt_lang]
            _lowerCAmelCase    :							Any   			=       [self.cur_lang_code_id]
            _lowerCAmelCase    :							Optional[int]   			=       [self.eos_token_id]







'''simple docstring'''







import socket






def 			lowercase				():







       """simple docstring"""







       _lowerCAmelCase    :							Tuple   			=       socket.socket(socket.AF_INET   ,						socket.SOCK_STREAM					)
       _lowerCAmelCase    :							Optional[int]   			=       socket.gethostname()
       _lowerCAmelCase    :							Any   			=       1_2_3_1_2

       sock.connect((host, port)					)
       sock.send(B'Hello server!'					)

       with open('Received_file'   ,						'wb'					) as out_file:
              print('File opened'					)
              print('Receiving data...'					)
              while True:
                     _lowerCAmelCase    :							Union[str, Any]   			=       sock.recv(1_0_2_4					)
                     if not data:
                            break
                     out_file.write(_A					)

       print('Successfully received the file'					)
       sock.close()
       print('Connection closed'					)


if __name__ == "__main__":
       main()

