




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		:				int       			=		logging.get_logger(__name__)

__lowerCAmelCase		:				Any       			=		{'vocab_file': 'sentencepiece.model'}

__lowerCAmelCase		:				Any       			=		{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

__lowerCAmelCase		:				str       			=		{
    'google/rembert': 256,
}




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							int							 =					VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_       :							List[str]							 =					PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_       :							Any							 =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES





				def __init__(      self				:     Optional[int]					,      __lowerCamelCase				:     List[Any]					,      __lowerCamelCase				:     str=False					,      __lowerCamelCase				:     int=True					,      __lowerCamelCase				:     List[Any]=True					,      __lowerCamelCase				:     Optional[int]="[CLS]"					,      __lowerCamelCase				:     Dict="[SEP]"					,      __lowerCamelCase				:     Optional[Any]="[UNK]"					,      __lowerCamelCase				:     List[str]="[SEP]"					,      __lowerCamelCase				:     Union[str, Any]="[PAD]"					,      __lowerCamelCase				:     Tuple="[CLS]"					,      __lowerCamelCase				:     Union[str, Any]="[MASK]"					,      **__lowerCamelCase				:     int					,      )					->     Tuple:
							super().__init__(
							    do_lower_case=__lowerCamelCase					,      remove_space=__lowerCamelCase					,      keep_accents=__lowerCamelCase					,      bos_token=__lowerCamelCase					,      eos_token=__lowerCamelCase					,      unk_token=__lowerCamelCase					,      sep_token=__lowerCamelCase					,      pad_token=__lowerCamelCase					,      cls_token=__lowerCamelCase					,      mask_token=__lowerCamelCase					,      **__lowerCamelCase					,      )

							a    =			do_lower_case
							a    =			remove_space
							a    =			keep_accents
							a    =			vocab_file

							a    =			spm.SentencePieceProcessor()
							self.sp_model.Load(__lowerCamelCase							)





				@property
				def 							__UpperCAmelCase							(      self				:     Union[str, Any]							)					->     str:
							return len(self.sp_model							)





				def 							__UpperCAmelCase							(      self				:     List[str]							)					->     List[Any]:
							a    =			{self.convert_ids_to_tokens(__lowerCamelCase							): i for i in range(self.vocab_size							)}
							vocab.update(self.added_tokens_encoder							)
							return vocab





				def __getstate__(      self				:     List[Any]							)					->     Dict:
							a    =			self.__dict__.copy()
							a    =			None
							return state





				def __setstate__(      self				:     List[str]					,      __lowerCamelCase				:     Dict							)					->     Any:
							a    =			d
							a    =			spm.SentencePieceProcessor()
							self.sp_model.Load(self.vocab_file							)





				def 							__UpperCAmelCase							(      self				:     int					,      __lowerCamelCase				:     List[Any]					,      __lowerCamelCase				:     Optional[int]=False							)					->     str:
							a    =			self.sp_model.EncodeAsPieces(__lowerCamelCase							)
							return pieces





				def 							__UpperCAmelCase							(      self				:     str					,      __lowerCamelCase				:     Dict							)					->     Optional[int]:
							return self.sp_model.PieceToId(__lowerCamelCase							)





				def 							__UpperCAmelCase							(      self				:     Optional[Any]					,      __lowerCamelCase				:     Tuple							)					->     Optional[Any]:
							return self.sp_model.IdToPiece(__lowerCamelCase							)





				def 							__UpperCAmelCase							(      self				:     Optional[int]					,      __lowerCamelCase				:     List[Any]							)					->     List[str]:
							a    =			self.sp_model.decode_pieces(__lowerCamelCase							)
							return out_string





				def 							__UpperCAmelCase							(      self				:     Dict					,      __lowerCamelCase				:     List[int]					,      __lowerCamelCase				:     Optional[List[int]] = None							)					->     List[int]:
							a    =			[self.sep_token_id]
							a    =			[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 							__UpperCAmelCase							(      self				:     Dict					,      __lowerCamelCase				:     List[int]					,      __lowerCamelCase				:     Optional[List[int]] = None					,      __lowerCamelCase				:     bool = False							)					->     List[int]:

							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(__lowerCamelCase							)) + [1] + ([0] * len(__lowerCamelCase							)) + [1]
							return [1] + ([0] * len(__lowerCamelCase							)) + [1]





				def 							__UpperCAmelCase							(      self				:     Union[str, Any]					,      __lowerCamelCase				:     List[int]					,      __lowerCamelCase				:     Optional[List[int]] = None							)					->     List[int]:
							a    =			[self.sep_token_id]
							a    =			[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 							__UpperCAmelCase							(      self				:     str					,      __lowerCamelCase				:     str					,      __lowerCamelCase				:     Optional[str] = None							)					->     Tuple[str]:
							if not os.path.isdir(__lowerCamelCase							):
										logger.error("Vocabulary path ({}) should be a directory".format(__lowerCamelCase							)							)
										return
							a    =			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							):
										copyfile(self.vocab_file					,      __lowerCamelCase							)

							return (out_vocab_file,)












from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase		:				Optional[Any]       			=		logging.get_logger(__name__)

__lowerCAmelCase		:				str       			=		{'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							Dict							 =					"""openai-gpt"""
				SCREAMING_SNAKE_CASE_       :							Tuple							 =					{
				    """max_position_embeddings""": """n_positions""",
				    """hidden_size""": """n_embd""",
				    """num_attention_heads""": """n_head""",
				    """num_hidden_layers""": """n_layer""",
				}





				def __init__(      self				:     str					,      __lowerCamelCase				:     List[str]=4_04_78					,      __lowerCamelCase				:     List[Any]=5_12					,      __lowerCamelCase				:     List[str]=7_68					,      __lowerCamelCase				:     List[str]=12					,      __lowerCamelCase				:     Optional[Any]=12					,      __lowerCamelCase				:     str="gelu"					,      __lowerCamelCase				:     Optional[int]=0.1					,      __lowerCamelCase				:     Any=0.1					,      __lowerCamelCase				:     Dict=0.1					,      __lowerCamelCase				:     Any=1e-5					,      __lowerCamelCase				:     Optional[int]=0.02					,      __lowerCamelCase				:     Optional[int]="cls_index"					,      __lowerCamelCase				:     List[Any]=True					,      __lowerCamelCase				:     Optional[int]=None					,      __lowerCamelCase				:     Optional[Any]=True					,      __lowerCamelCase				:     Tuple=0.1					,      **__lowerCamelCase				:     Union[str, Any]					,      )					->     List[str]:
							a    =			vocab_size
							a    =			n_positions
							a    =			n_embd
							a    =			n_layer
							a    =			n_head
							a    =			afn
							a    =			resid_pdrop
							a    =			embd_pdrop
							a    =			attn_pdrop
							a    =			layer_norm_epsilon
							a    =			initializer_range
							a    =			summary_type
							a    =			summary_use_proj
							a    =			summary_activation
							a    =			summary_first_dropout
							a    =			summary_proj_to_labels
							super().__init__(**__lowerCamelCase							)






