
"""simple docstring"""







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

import sentencepiece as spm

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


lowerCamelCase__        =		logging.get_logger(__name__)

lowerCamelCase__        =		{"""vocab_file""": """sentencepiece.model"""}

lowerCamelCase__        =		{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
}

lowerCamelCase__        =		{
    """google/rembert""": 256,
}




class 			A__	(     _lowerCamelCase):
		A_						:	Optional[Any]           =     VOCAB_FILES_NAMES
		A_						:	Any           =     PRETRAINED_VOCAB_FILES_MAP
		A_						:	int           =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

		def __init__(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE="[CLS]"	,		_SCREAMING_SNAKE_CASE="[SEP]"	,		_SCREAMING_SNAKE_CASE="[UNK]"	,		_SCREAMING_SNAKE_CASE="[SEP]"	,		_SCREAMING_SNAKE_CASE="[PAD]"	,		_SCREAMING_SNAKE_CASE="[CLS]"	,		_SCREAMING_SNAKE_CASE="[MASK]"	,		**_SCREAMING_SNAKE_CASE	,		):
			super().__init__(
			    do_lower_case=_SCREAMING_SNAKE_CASE	,		remove_space=_SCREAMING_SNAKE_CASE	,		keep_accents=_SCREAMING_SNAKE_CASE	,		bos_token=_SCREAMING_SNAKE_CASE	,		eos_token=_SCREAMING_SNAKE_CASE	,		unk_token=_SCREAMING_SNAKE_CASE	,		sep_token=_SCREAMING_SNAKE_CASE	,		pad_token=_SCREAMING_SNAKE_CASE	,		cls_token=_SCREAMING_SNAKE_CASE	,		mask_token=_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE	,		)

			__lowerCAmelCase      :						Tuple						      =				do_lower_case
			__lowerCAmelCase      :						Dict						      =				remove_space
			__lowerCAmelCase      :						List[str]						      =				keep_accents
			__lowerCAmelCase      :						Any						      =				vocab_file

			__lowerCAmelCase      :						Tuple						      =				spm.SentencePieceProcessor()
			self.sp_model.Load(_SCREAMING_SNAKE_CASE			)

		@property
		def 							__lowerCamelCase							(				self			):
			return len(self.sp_model			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						Any						      =				{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 __getstate__(				self			):
			__lowerCAmelCase      :						Union[str, Any]						      =				self.__dict__.copy()
			__lowerCAmelCase      :						List[Any]						      =				None
			return state

		def __setstate__(				self	,		_SCREAMING_SNAKE_CASE			):
			__lowerCAmelCase      :						Tuple						      =				d
			__lowerCAmelCase      :						Union[str, Any]						      =				spm.SentencePieceProcessor()
			self.sp_model.Load(self.vocab_file			)

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE=False			):
			__lowerCAmelCase      :						str						      =				self.sp_model.EncodeAsPieces(_SCREAMING_SNAKE_CASE			)
			return pieces

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE			):
			return self.sp_model.PieceToId(_SCREAMING_SNAKE_CASE			)

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE			):
			return self.sp_model.IdToPiece(_SCREAMING_SNAKE_CASE			)

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE			):
			__lowerCAmelCase      :						int						      =				self.sp_model.decode_pieces(_SCREAMING_SNAKE_CASE			)
			return out_string

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE = None			):
			__lowerCAmelCase      :						Dict						      =				[self.sep_token_id]
			__lowerCAmelCase      :						Dict						      =				[self.cls_token_id]
			if token_ids_a is None:
				return cls + token_ids_a + sep
			return cls + token_ids_a + sep + token_ids_a + sep

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE = None	,		_SCREAMING_SNAKE_CASE = False			):

			if already_has_special_tokens:
				if token_ids_a is not None:
					raise ValueError(
					    'You should not supply a second sequence if the provided sequence of '
					    'ids is already formatted with special tokens for the model.'			)
				return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

			if token_ids_a is not None:
				return [1] + ([0] * len(_SCREAMING_SNAKE_CASE			)) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE			)) + [1]
			return [1] + ([0] * len(_SCREAMING_SNAKE_CASE			)) + [1]

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE = None			):
			__lowerCAmelCase      :						List[Any]						      =				[self.sep_token_id]
			__lowerCAmelCase      :						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			) * [0] + len(token_ids_a + sep			) * [1]







		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE = None			):
			if not os.path.isdir(_SCREAMING_SNAKE_CASE			):
				logger.error('Vocabulary path ({}) should be a directory'.format(_SCREAMING_SNAKE_CASE			)			)
				return
			__lowerCAmelCase      :						Optional[int]						      =				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			):
				copyfile(self.vocab_file	,		_SCREAMING_SNAKE_CASE			)

			return (out_vocab_file,)

"""simple docstring"""







# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    """stable diffusion controlnet""",
    """0.22.0""",
    """Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.""",
    standard_warn=False,
    stacklevel=3,
)