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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase :			str              =	logging.get_logger(__name__)

_UpperCAmelCase :			List[Any]              =	{"vocab_file": "spiece.model"}

_UpperCAmelCase :			Any              =	{
    "vocab_file": {
        "bert_for_seq_generation": (
            "https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"
        ),
    }
}

_UpperCAmelCase :			Optional[int]              =	{"bert_for_seq_generation": 512}


class     lowercase (		_SCREAMING_SNAKE_CASE       ):
		__lowercase	:	str     					=    VOCAB_FILES_NAMES
		__lowercase	:	List[Any]     					=    PRETRAINED_VOCAB_FILES_MAP
		__lowercase	:	Dict     					=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		__lowercase	:	List[int]     					=    []
		__lowercase	:	Union[str, Any]     					=    ["input_ids", "attention_mask"]



		def __init__(			self    ,				A_    ,				A_="<s>"    ,				A_="</s>"    ,				A_="<unk>"    ,				A_="<pad>"    ,				A_="<::::>"    ,				A_ = None    ,				**A_    ,				)  -> None:
				"""simple docstring"""
				UpperCamelCase          =					{} if sp_model_kwargs is None else sp_model_kwargs

				# Add extra_ids to the special token list
				super().__init__(
				    bos_token=A_    ,				eos_token=A_    ,				unk_token=A_    ,				pad_token=A_    ,				sep_token=A_    ,				sp_model_kwargs=self.sp_model_kwargs    ,				**A_    ,				)

				UpperCamelCase          =					vocab_file

				UpperCamelCase          =					spm.SentencePieceProcessor(**self.sp_model_kwargs	)
				self.sp_model.Load(A_	)



		@property
		def __UpperCamelCase			(			self	)  -> List[str]:
				"""simple docstring"""
				return self.sp_model.get_piece_size()



		def __UpperCamelCase			(			self	)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					{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	)  -> Tuple:
				"""simple docstring"""
				UpperCamelCase          =					self.__dict__.copy()
				UpperCamelCase          =					None
				return state



		def __setstate__(			self    ,				A_	)  -> List[Any]:
				"""simple docstring"""
				UpperCamelCase          =					d

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

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



		def __UpperCamelCase			(			self    ,				A_	)  -> List[str]:
				"""simple docstring"""
				return self.sp_model.encode(A_    ,				out_type=A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> Dict:
				"""simple docstring"""
				return self.sp_model.piece_to_id(A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					self.sp_model.IdToPiece(A_	)
				return token



		def __UpperCamelCase			(			self    ,				A_	)  -> Optional[int]:
				"""simple docstring"""
				UpperCamelCase          =					[]
				UpperCamelCase          =					''
				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
								UpperCamelCase          =					[]
						else:
								current_sub_tokens.append(A_	)
				out_string += self.sp_model.decode(A_	)
				return out_string.strip()



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = None	)  -> Tuple[str]:
				"""simple docstring"""
				if not os.path.isdir(A_	):
						logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
						return
				UpperCamelCase          =					os.path.join(
				    A_    ,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

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

				return (out_vocab_file,)


import json
import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin


class     lowercase (		_SCREAMING_SNAKE_CASE  ,       unittest.TestCase       ):
		__lowercase	:	Any     					=    CTRLTokenizer
		__lowercase	:	Any     					=    False
		__lowercase	:	Union[str, Any]     					=    False



		def __UpperCamelCase			(			self	)  -> Any:
				"""simple docstring"""
				super().setUp()

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

				UpperCamelCase          =					os.path.join(self.tmpdirname    ,				VOCAB_FILES_NAMES['vocab_file']	)
				UpperCamelCase          =					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(A_	) + '\n'	)
				with open(self.merges_file    ,				'w'    ,				encoding='utf-8'	) as fp:
						fp.write('\n'.join(A_	)	)



		def __UpperCamelCase			(			self    ,				**A_	)  -> List[Any]:
				"""simple docstring"""
				kwargs.update(self.special_tokens_map	)
				return CTRLTokenizer.from_pretrained(self.tmpdirname    ,				**A_	)



		def __UpperCamelCase			(			self    ,				A_	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					'adapt react readapt apt'
				UpperCamelCase          =					'adapt react readapt apt'
				return input_text, output_text



		def __UpperCamelCase			(			self	)  -> str:
				"""simple docstring"""
				UpperCamelCase          =					CTRLTokenizer(self.vocab_file    ,				self.merges_file    ,				**self.special_tokens_map	)
				UpperCamelCase          =					'adapt react readapt apt'
				UpperCamelCase          =					'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
				UpperCamelCase          =					tokenizer.tokenize(A_	)
				self.assertListEqual(A_    ,				A_	)

				UpperCamelCase          =					tokens + [tokenizer.unk_token]

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