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


_lowercase:	Dict       			=		logging.get_logger(__name__)

_lowercase:	Dict       			=		'''▁'''

_lowercase:	Optional[Any]       			=		{'''vocab_file''': '''sentencepiece.bpe.model'''}

_lowercase:	Any       			=		{
    '''vocab_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

_lowercase:	int       			=		{
    '''xlm-roberta-base''': 5_1_2,
    '''xlm-roberta-large''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll03-english''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll03-german''': 5_1_2,
}



class        lowerCamelCase__				(   UpperCAmelCase				):
			UpperCamelCase__    							=VOCAB_FILES_NAMES
			UpperCamelCase__    							=PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__    							=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__    							=["input_ids", "attention_mask"]





			def __init__(       self	:	int  ,  lowercase__	:	List[str]  ,  lowercase__	:	Tuple="<s>"  ,  lowercase__	:	Union[str, Any]="</s>"  ,  lowercase__	:	Optional[int]="</s>"  ,  lowercase__	:	Union[str, Any]="<s>"  ,  lowercase__	:	Union[str, Any]="<unk>"  ,  lowercase__	:	Optional[Any]="<pad>"  ,  lowercase__	:	Any="<mask>"  ,  lowercase__	:	Optional[Dict[str, Any]] = None  ,  **lowercase__	:	Optional[int]  ,  ):
										# Mask token behave like a normal word, i.e. include the space before it
										_lowerCAmelCase							=							AddedToken(lowercase__  ,  lstrip=lowercase__  ,  rstrip=lowercase__						) if isinstance(lowercase__  ,  lowercase__						) else mask_token

										_lowerCAmelCase							=							{} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    bos_token=lowercase__  ,  eos_token=lowercase__  ,  unk_token=lowercase__  ,  sep_token=lowercase__  ,  cls_token=lowercase__  ,  pad_token=lowercase__  ,  mask_token=lowercase__  ,  sp_model_kwargs=self.sp_model_kwargs  ,  **lowercase__  ,  )

										_lowerCAmelCase							=							spm.SentencePieceProcessor(**self.sp_model_kwargs						)
										self.sp_model.Load(str(lowercase__						)						)
										_lowerCAmelCase							=							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							=							{'<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							=							1

										_lowerCAmelCase							=							len(self.sp_model						) + self.fairseq_offset
										_lowerCAmelCase							=							{v: k for k, v in self.fairseq_tokens_to_ids.items()}





			def __getstate__(       self	:	List[Any]						):
										_lowerCAmelCase							=							self.__dict__.copy()
										_lowerCAmelCase							=							None
										_lowerCAmelCase							=							self.sp_model.serialized_model_proto()
										return state





			def __setstate__(       self	:	Optional[int]  ,  lowercase__	:	int						):
										_lowerCAmelCase							=							d

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

										_lowerCAmelCase							=							spm.SentencePieceProcessor(**self.sp_model_kwargs						)
										self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Tuple  ,  lowercase__	:	List[int]  ,  lowercase__	:	Optional[List[int]] = None						):

										if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										_lowerCAmelCase							=							[self.cls_token_id]
										_lowerCAmelCase							=							[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep





			def   SCREAMING_SNAKE_CASE__     (       self	:	Dict  ,  lowercase__	:	List[int]  ,  lowercase__	:	Optional[List[int]] = None  ,  lowercase__	:	bool = False						):

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

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





			def   SCREAMING_SNAKE_CASE__     (       self	:	Optional[Any]  ,  lowercase__	:	List[int]  ,  lowercase__	:	Optional[List[int]] = None						):
										_lowerCAmelCase							=							[self.sep_token_id]
										_lowerCAmelCase							=							[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   SCREAMING_SNAKE_CASE__     (       self	:	int						):
										return len(self.sp_model						) + self.fairseq_offset + 1  # Add the <mask> token





			def   SCREAMING_SNAKE_CASE__     (       self	:	Any						):
										_lowerCAmelCase							=							{self.convert_ids_to_tokens(lowercase__						): i for i in range(self.vocab_size						)}
										vocab.update(self.added_tokens_encoder						)
										return vocab





			def   SCREAMING_SNAKE_CASE__     (       self	:	Union[str, Any]  ,  lowercase__	:	str						):
										return self.sp_model.encode(lowercase__  ,  out_type=lowercase__						)





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

										# 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   SCREAMING_SNAKE_CASE__     (       self	:	str  ,  lowercase__	:	int						):
										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   SCREAMING_SNAKE_CASE__     (       self	:	Union[str, Any]  ,  lowercase__	:	Optional[int]						):
										_lowerCAmelCase							=							''.join(lowercase__						).replace(lowercase__  ,  ' '						).strip()
										return out_string





			def   SCREAMING_SNAKE_CASE__     (       self	:	Optional[Any]  ,  lowercase__	:	str  ,  lowercase__	:	Optional[str] = None						):
										if not os.path.isdir(lowercase__						):
																	logger.error(f'Vocabulary path ({save_directory}) should be a directory'						)
																	return
										_lowerCAmelCase							=							os.path.join(
										    lowercase__  ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)

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

										return (out_vocab_file,)







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

_lowercase:	Tuple       			=		{
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}



class        lowerCamelCase__				(   UpperCAmelCase				):
			UpperCamelCase__    							="roberta-prelayernorm"





			def __init__(       self	:	int  ,  lowercase__	:	int=5_02_65  ,  lowercase__	:	str=7_68  ,  lowercase__	:	List[Any]=12  ,  lowercase__	:	Any=12  ,  lowercase__	:	Optional[Any]=30_72  ,  lowercase__	:	List[Any]="gelu"  ,  lowercase__	:	str=0.1  ,  lowercase__	:	List[Any]=0.1  ,  lowercase__	:	Tuple=5_12  ,  lowercase__	:	Optional[int]=2  ,  lowercase__	:	Dict=0.0_2  ,  lowercase__	:	Tuple=1e-12  ,  lowercase__	:	Optional[int]=1  ,  lowercase__	:	Optional[int]=0  ,  lowercase__	:	Union[str, Any]=2  ,  lowercase__	:	Any="absolute"  ,  lowercase__	:	Any=True  ,  lowercase__	:	Any=None  ,  **lowercase__	:	Optional[int]  ,  ):
										super().__init__(pad_token_id=lowercase__  ,  bos_token_id=lowercase__  ,  eos_token_id=lowercase__  ,  **lowercase__						)

										_lowerCAmelCase							=							vocab_size
										_lowerCAmelCase							=							hidden_size
										_lowerCAmelCase							=							num_hidden_layers
										_lowerCAmelCase							=							num_attention_heads
										_lowerCAmelCase							=							hidden_act
										_lowerCAmelCase							=							intermediate_size
										_lowerCAmelCase							=							hidden_dropout_prob
										_lowerCAmelCase							=							attention_probs_dropout_prob
										_lowerCAmelCase							=							max_position_embeddings
										_lowerCAmelCase							=							type_vocab_size
										_lowerCAmelCase							=							initializer_range
										_lowerCAmelCase							=							layer_norm_eps
										_lowerCAmelCase							=							position_embedding_type
										_lowerCAmelCase							=							use_cache
										_lowerCAmelCase							=							classifier_dropout







class        lowerCamelCase__				(   UpperCAmelCase				):





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	List[str]						):
										if self.task == "multiple-choice":
																	_lowerCAmelCase							=							{0: 'batch', 1: 'choice', 2: 'sequence'}
										else:
																	_lowerCAmelCase							=							{0: 'batch', 1: 'sequence'}
										return OrderedDict(
										    [
										        ('input_ids', dynamic_axis),
										        ('attention_mask', dynamic_axis),
										    ]						)






