

"""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, PreTrainedTokenizer
from ...utils import logging


__A						   =			logging.get_logger(__name__)

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

__A						   =			{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

__A						   =			{
    "camembert-base": 512,
}

__A						   =			"▁"





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Union[str, Any]         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      List[Any]         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      str         =  ["""input_ids""", """attention_mask"""]

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



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else mask_token

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

						super().__init__(
						    bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  additional_special_tokens=UpperCamelCase__     ,  sp_model_kwargs=self.sp_model_kwargs     ,  **UpperCamelCase__     ,  )
						__lowerCAmelCase:       str          =			spm.SentencePieceProcessor(**self.sp_model_kwargs)
						self.sp_model.Load(str(UpperCamelCase__))
						__lowerCAmelCase:       Tuple          =			vocab_file
						# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
						# sentencepiece vocabulary (this is the case for <s> and </s>
						__lowerCAmelCase:       Optional[Any]          =			{"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
						__lowerCAmelCase:       str          =			len(self.fairseq_tokens_to_ids)
						__lowerCAmelCase:       Optional[int]          =			len(self.sp_model) + len(self.fairseq_tokens_to_ids)
						__lowerCAmelCase:       Tuple          =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						__lowerCAmelCase:       Union[str, Any]          =			[self.cls_token_id]
						__lowerCAmelCase:       List[Any]          =			[self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep

				def 							lowercase_     (	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__)

						if token_ids_a is None:
								return [1] + ([0] * len(UpperCamelCase__)) + [1]
						return [1] + ([0] * len(UpperCamelCase__)) + [1, 1] + ([0] * len(UpperCamelCase__)) + [1]

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



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			[self.sep_token_id]
						__lowerCAmelCase:       Optional[Any]          =			[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]

				@property
				def 							lowercase_     (	self							:				List[str])->   Dict:



						'''simple docstring'''


						return len(self.fairseq_tokens_to_ids) + len(self.sp_model)

				def 							lowercase_     (	self							:				List[str])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			{self.convert_ids_to_tokens(UpperCamelCase__): i for i in range(self.vocab_size)}
						vocab.update(self.added_tokens_encoder)
						return vocab

				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				str)->   List[str]:



						'''simple docstring'''


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

				def 							lowercase_     (	self							:				Tuple     ,  UpperCamelCase__							:				str)->   int:



						'''simple docstring'''


						if token in self.fairseq_tokens_to_ids:
								return self.fairseq_tokens_to_ids[token]
						elif self.sp_model.PieceToId(UpperCamelCase__) == 0:
								# Convert sentence piece unk token to fairseq unk token index
								return self.unk_token_id
						return self.fairseq_offset + self.sp_model.PieceToId(UpperCamelCase__)

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				int)->   Optional[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 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				List[Any])->   Optional[Any]:



						'''simple docstring'''


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

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



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			self.__dict__.copy()
						__lowerCAmelCase:       Union[str, Any]          =			None
						return state

				def __setstate__(	self							:				str     ,  UpperCamelCase__							:				Optional[Any])->   Dict:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			d

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

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




				def 							lowercase_     (	self							:				Tuple     ,  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:       Dict          =			self.sp_model.serialized_model_proto()
										fi.write(UpperCamelCase__)

						return (out_vocab_file,)





"""simple docstring"""


import pytest

from datasets import inspect_metric, list_metrics, load_metric






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	Union[str, Any]:
		monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"					, set() )






@pytest.fixture
def     a__    (    __SCREAMING_SNAKE_CASE )	->	str:





		class     snake_case	:

						def __init__(	self							:				int     ,  UpperCamelCase__							:				Optional[int])->   Union[str, Any]:



								'''simple docstring'''


								__lowerCAmelCase:       str          =			metric_id





		class     snake_case	:
						SCREAMING_SNAKE_CASE_   :      List[Any]         =  [MetricMock(__snake_case  ) for metric_id in ["""accuracy""", """mse""", """precision""", """codeparrot/apps_metric"""]]

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



								'''simple docstring'''


								return self._metrics


		monkeypatch.setattr("datasets.inspect.huggingface_hub"					, HfhMock() )






@pytest.mark.parametrize(
    "func, args"					, [(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	Optional[Any]:
		if "tmp_path" in args:
				__lowerCAmelCase:       Tuple          =			tuple(arg if arg != "tmp_path" else tmp_path for arg in args )
		with pytest.warns(__SCREAMING_SNAKE_CASE					, match="https://huggingface.co/docs/evaluate" ):
				func(*__SCREAMING_SNAKE_CASE )


