






"""simple docstring"""
import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
			from .tokenization_deberta_va import DebertaVaTokenizer
else:
			lowerCAmelCase__							= None

lowerCAmelCase__							= logging.get_logger(__name__)

lowerCAmelCase__							= {'vocab_file': 'spm.model', 'tokenizer_file': 'tokenizer.json'}

lowerCAmelCase__							= {
    'vocab_file': {
        'microsoft/deberta-v2-xlarge': 'https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model',
        'microsoft/deberta-v2-xxlarge': 'https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model',
        'microsoft/deberta-v2-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'
        ),
        'microsoft/deberta-v2-xxlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'
        ),
    }
}

lowerCAmelCase__							= {
    'microsoft/deberta-v2-xlarge': 512,
    'microsoft/deberta-v2-xxlarge': 512,
    'microsoft/deberta-v2-xlarge-mnli': 512,
    'microsoft/deberta-v2-xxlarge-mnli': 512,
}

lowerCAmelCase__							= {
    'microsoft/deberta-v2-xlarge': {'do_lower_case': False},
    'microsoft/deberta-v2-xxlarge': {'do_lower_case': False},
    'microsoft/deberta-v2-xlarge-mnli': {'do_lower_case': False},
    'microsoft/deberta-v2-xxlarge-mnli': {'do_lower_case': False},
}


class _lowerCAmelCase	(						__UpperCAmelCase					):
						SCREAMING_SNAKE_CASE_:				Tuple   				=							VOCAB_FILES_NAMES
						SCREAMING_SNAKE_CASE_:				Tuple   				=							PRETRAINED_VOCAB_FILES_MAP
						SCREAMING_SNAKE_CASE_:				Optional[Any]   				=							PRETRAINED_INIT_CONFIGURATION
						SCREAMING_SNAKE_CASE_:				Optional[Any]   				=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						SCREAMING_SNAKE_CASE_:				List[str]   				=							DebertaVaTokenizer







						def __init__(						self      ,							lowerCAmelCase_=None      ,							lowerCAmelCase_=None      ,							lowerCAmelCase_=False      ,							lowerCAmelCase_=False      ,							lowerCAmelCase_="[CLS]"      ,							lowerCAmelCase_="[SEP]"      ,							lowerCAmelCase_="[UNK]"      ,							lowerCAmelCase_="[SEP]"      ,							lowerCAmelCase_="[PAD]"      ,							lowerCAmelCase_="[CLS]"      ,							lowerCAmelCase_="[MASK]"      ,							**lowerCAmelCase_      ,							)		->       None:
										super().__init__(
										    lowerCAmelCase_      ,							tokenizer_file=lowerCAmelCase_      ,							do_lower_case=lowerCAmelCase_      ,							bos_token=lowerCAmelCase_      ,							eos_token=lowerCAmelCase_      ,							unk_token=lowerCAmelCase_      ,							sep_token=lowerCAmelCase_      ,							pad_token=lowerCAmelCase_      ,							cls_token=lowerCAmelCase_      ,							mask_token=lowerCAmelCase_      ,							split_by_punct=lowerCAmelCase_      ,							**lowerCAmelCase_      ,							)

										_SCREAMING_SNAKE_CASE      :		str							=						do_lower_case
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						split_by_punct
										_SCREAMING_SNAKE_CASE      :		Dict							=						vocab_file
										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						False if not self.vocab_file else True







						def  A			(						self      ,							lowerCAmelCase_      ,							lowerCAmelCase_=None       )		->       str:

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







						def  A			(						self      ,							lowerCAmelCase_      ,							lowerCAmelCase_=None      ,							lowerCAmelCase_=False       )		->       Tuple:

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

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







						def  A			(						self      ,							lowerCAmelCase_      ,							lowerCAmelCase_=None       )		->       int:
										_SCREAMING_SNAKE_CASE      :		Optional[int]							=						[self.sep_token_id]
										_SCREAMING_SNAKE_CASE      :		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  A			(						self      ,							lowerCAmelCase_      ,							lowerCAmelCase_ = None       )		->       Tuple[str]:
										if not self.can_save_slow_tokenizer:
														raise ValueError(
														    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
														    'tokenizer.'       )

										if not os.path.isdir(lowerCAmelCase_       ):
														logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
														return
										_SCREAMING_SNAKE_CASE      :		Any							=						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,)









"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


lowerCAmelCase__							= logging.get_logger(__name__)


class _lowerCAmelCase	(						__UpperCAmelCase					):







						def __init__(						self      ,							*lowerCAmelCase_      ,							**lowerCAmelCase_       )		->       None:
										warnings.warn(
										    'The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use ViTImageProcessor instead.'      ,							lowerCAmelCase_      ,							)
										super().__init__(*lowerCAmelCase_      ,							**lowerCAmelCase_       )

