




import os
import unittest

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    BertTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english




@require_tokenizers
class    a__       (							lowerCAmelCase      , unittest.TestCase):
       _a 					=						BertTokenizer
       _a 					=						BertTokenizerFast
       _a 					=						True
       _a 					=						True
       _a 					=						filter_non_english






       def 					SCREAMING_SNAKE_CASE    (   self:					Union[str, Any]				):
         super().setUp()

         lowercase    :Dict      	=						[
             "[UNK]",
             "[CLS]",
             "[SEP]",
             "[PAD]",
             "[MASK]",
             "want",
             "##want",
             "##ed",
             "wa",
             "un",
             "runn",
             "##ing",
             ",",
             "low",
             "lowest",
         ]
         lowercase    :List[str]      	=						os.path.join(self.tmpdirname       ,					VOCAB_FILES_NAMES["vocab_file"]				)
         with open(self.vocab_file       ,					"w"       ,					encoding="utf-8"				) as vocab_writer:
           vocab_writer.write("".join([x + "\n" for x in vocab_tokens]				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					str       ,					_lowerCAmelCase:					int				):
         lowercase    :Any      	=						"UNwant\u00E9d,running"
         lowercase    :Any      	=						"unwanted, running"
         return input_text, output_text






       def 					SCREAMING_SNAKE_CASE    (   self:					Union[str, Any]				):
         lowercase    :Tuple      	=						self.tokenizer_class(self.vocab_file				)

         lowercase    :List[str]      	=						tokenizer.tokenize("UNwant\u00E9d,running"				)
         self.assertListEqual(_lowerCAmelCase       ,					["un", "##want", "##ed", ",", "runn", "##ing"]				)
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase				)       ,					[9, 6, 7, 12, 10, 11]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         if not self.test_rust_tokenizer:
           return

         lowercase    :Tuple      	=						self.get_tokenizer()
         lowercase    :List[Any]      	=						self.get_rust_tokenizer()

         lowercase    :Tuple      	=						"UNwant\u00E9d,running"

         lowercase    :str      	=						tokenizer.tokenize(_lowerCAmelCase				)
         lowercase    :List[str]      	=						rust_tokenizer.tokenize(_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :List[Any]      	=						tokenizer.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
         lowercase    :List[Any]      	=						rust_tokenizer.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :Union[str, Any]      	=						self.get_rust_tokenizer()
         lowercase    :Optional[int]      	=						tokenizer.encode(_lowerCAmelCase				)
         lowercase    :Tuple      	=						rust_tokenizer.encode(_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

         # With lower casing
         lowercase    :Any      	=						self.get_tokenizer(do_lower_case=_lowerCAmelCase				)
         lowercase    :List[Any]      	=						self.get_rust_tokenizer(do_lower_case=_lowerCAmelCase				)

         lowercase    :Union[str, Any]      	=						"UNwant\u00E9d,running"

         lowercase    :str      	=						tokenizer.tokenize(_lowerCAmelCase				)
         lowercase    :List[str]      	=						rust_tokenizer.tokenize(_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :Tuple      	=						tokenizer.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
         lowercase    :List[Any]      	=						rust_tokenizer.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

         lowercase    :List[str]      	=						self.get_rust_tokenizer()
         lowercase    :List[str]      	=						tokenizer.encode(_lowerCAmelCase				)
         lowercase    :Tuple      	=						rust_tokenizer.encode(_lowerCAmelCase				)
         self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         lowercase    :List[Any]      	=						BasicTokenizer()

         self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"				)       ,					["ah", "\u535A", "\u63A8", "zz"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple				):
         lowercase    :Optional[int]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "				)       ,					["hello", "!", "how", "are", "you", "?"]				)
         self.assertListEqual(tokenizer.tokenize("H\u00E9llo"				)       ,					["hello"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         lowercase    :Union[str, Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase       ,					strip_accents=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "				)       ,					["hällo", "!", "how", "are", "you", "?"]				)
         self.assertListEqual(tokenizer.tokenize("H\u00E9llo"				)       ,					["h\u00E9llo"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         lowercase    :List[Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase       ,					strip_accents=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "				)       ,					["hallo", "!", "how", "are", "you", "?"]				)
         self.assertListEqual(tokenizer.tokenize("H\u00E9llo"				)       ,					["hello"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Union[str, Any]				):
         lowercase    :Optional[int]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "				)       ,					["hallo", "!", "how", "are", "you", "?"]				)
         self.assertListEqual(tokenizer.tokenize("H\u00E9llo"				)       ,					["hello"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Union[str, Any]				):
         lowercase    :List[Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "				)       ,					["HeLLo", "!", "how", "Are", "yoU", "?"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					str				):
         lowercase    :List[Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase       ,					strip_accents=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "				)       ,					["HäLLo", "!", "how", "Are", "yoU", "?"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         lowercase    :Optional[Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase       ,					strip_accents=_lowerCAmelCase				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "				)       ,					["HaLLo", "!", "how", "Are", "yoU", "?"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         lowercase    :Optional[Any]      	=						BasicTokenizer(do_lower_case=_lowerCAmelCase       ,					never_split=["[UNK]"]				)

         self.assertListEqual(
             tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]"				)       ,					["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         lowercase    :Optional[Any]      	=						BasicTokenizer()
         lowercase    :Tuple      	=						"a\n'll !!to?'d of, can't."
         lowercase    :Tuple      	=						["a", "'", "ll", "!", "!", "to", "?", "'", "d", "of", ",", "can", "'", "t", "."]
         self.assertListEqual(tokenizer.tokenize(_lowerCAmelCase				)       ,					_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Any				):
         lowercase    :Any      	=						["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

         lowercase    :Dict      	=						{}
         for i, token in enumerate(_lowerCAmelCase				):
           lowercase    :Any      	=						i
         lowercase    :List[str]      	=						WordpieceTokenizer(vocab=_lowerCAmelCase       ,					unk_token="[UNK]"				)

         self.assertListEqual(tokenizer.tokenize(""				)       ,					[]				)

         self.assertListEqual(tokenizer.tokenize("unwanted running"				)       ,					["un", "##want", "##ed", "runn", "##ing"]				)

         self.assertListEqual(tokenizer.tokenize("unwantedX running"				)       ,					["[UNK]", "runn", "##ing"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple				):
         self.assertTrue(_is_whitespace(" "				)				)
         self.assertTrue(_is_whitespace("\t"				)				)
         self.assertTrue(_is_whitespace("\r"				)				)
         self.assertTrue(_is_whitespace("\n"				)				)
         self.assertTrue(_is_whitespace("\u00A0"				)				)

         self.assertFalse(_is_whitespace("A"				)				)
         self.assertFalse(_is_whitespace("-"				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					int				):
         self.assertTrue(_is_control("\u0005"				)				)

         self.assertFalse(_is_control("A"				)				)
         self.assertFalse(_is_control(" "				)				)
         self.assertFalse(_is_control("\t"				)				)
         self.assertFalse(_is_control("\r"				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]				):
         self.assertTrue(_is_punctuation("-"				)				)
         self.assertTrue(_is_punctuation("$"				)				)
         self.assertTrue(_is_punctuation("`"				)				)
         self.assertTrue(_is_punctuation("."				)				)

         self.assertFalse(_is_punctuation("A"				)				)
         self.assertFalse(_is_punctuation(" "				)				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]				):
         lowercase    :str      	=						self.get_tokenizer()
         lowercase    :Dict      	=						self.get_rust_tokenizer()

         # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
         self.assertListEqual([tokenizer.tokenize(_lowerCAmelCase				) for t in ["Test", "\xad", "test"]]       ,					[["[UNK]"], [], ["[UNK]"]]				)

         self.assertListEqual(
             [rust_tokenizer.tokenize(_lowerCAmelCase				) for t in ["Test", "\xad", "test"]]       ,					[["[UNK]"], [], ["[UNK]"]]				)






       @slow
       def 					SCREAMING_SNAKE_CASE    (   self:					str				):
         lowercase    :List[Any]      	=						self.tokenizer_class.from_pretrained("bert-base-uncased"				)

         lowercase    :List[Any]      	=						tokenizer.encode("sequence builders"       ,					add_special_tokens=_lowerCAmelCase				)
         lowercase    :Union[str, Any]      	=						tokenizer.encode("multi-sequence build"       ,					add_special_tokens=_lowerCAmelCase				)

         lowercase    :List[Any]      	=						tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase				)
         lowercase    :List[Any]      	=						tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase       ,					_lowerCAmelCase				)

         assert encoded_sentence == [1_01] + text + [1_02]
         assert encoded_pair == [1_01] + text + [1_02] + text_a + [1_02]






       def 					SCREAMING_SNAKE_CASE    (   self:					str				):
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
             lowercase    :Union[str, Any]      	=						self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)

             lowercase    :str      	=						F"A, naïve {tokenizer_r.mask_token} AllenNLP sentence."
             lowercase    :str      	=						tokenizer_r.encode_plus(
                 _lowerCAmelCase       ,					return_attention_mask=_lowerCAmelCase       ,					return_token_type_ids=_lowerCAmelCase       ,					return_offsets_mapping=_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase       ,					)

             lowercase    :Any      	=						tokenizer_r.do_lower_case if hasattr(_lowerCAmelCase       ,					"do_lower_case"				) else False
             lowercase    :Union[str, Any]      	=						(
                 [
                     ((0, 0), tokenizer_r.cls_token),
                     ((0, 1), "A"),
                     ((1, 2), ","),
                     ((3, 5), "na"),
                     ((5, 6), "##ï"),
                     ((6, 8), "##ve"),
                     ((9, 15), tokenizer_r.mask_token),
                     ((16, 21), "Allen"),
                     ((21, 23), "##NL"),
                     ((23, 24), "##P"),
                     ((25, 33), "sentence"),
                     ((33, 34), "."),
                     ((0, 0), tokenizer_r.sep_token),
                 ]
                 if not do_lower_case
                 else [
                     ((0, 0), tokenizer_r.cls_token),
                     ((0, 1), "a"),
                     ((1, 2), ","),
                     ((3, 8), "naive"),
                     ((9, 15), tokenizer_r.mask_token),
                     ((16, 21), "allen"),
                     ((21, 23), "##nl"),
                     ((23, 24), "##p"),
                     ((25, 33), "sentence"),
                     ((33, 34), "."),
                     ((0, 0), tokenizer_r.sep_token),
                 ]
             )

             self.assertEqual(
                 [e[1] for e in expected_results]       ,					tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]				)				)
             self.assertEqual([e[0] for e in expected_results]       ,					tokens["offset_mapping"]				)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         lowercase    :str      	=						["的", "人", "有"]
         lowercase    :Union[str, Any]      	=						"".join(_lowerCAmelCase				)
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
             lowercase    :List[Any]      	=						True
             lowercase    :Optional[Any]      	=						self.tokenizer_class.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)
             lowercase    :List[Any]      	=						self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)

             lowercase    :str      	=						tokenizer_p.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
             lowercase    :int      	=						tokenizer_r.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)

             lowercase    :Union[str, Any]      	=						tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase				)
             lowercase    :Tuple      	=						tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase				)

             # it is expected that each Chinese character is not preceded by "##"
             self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)
             self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)

             lowercase    :List[str]      	=						False
             lowercase    :Optional[int]      	=						self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)
             lowercase    :Optional[Any]      	=						self.tokenizer_class.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)

             lowercase    :str      	=						tokenizer_r.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)
             lowercase    :str      	=						tokenizer_p.encode(_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase				)

             lowercase    :Any      	=						tokenizer_r.convert_ids_to_tokens(_lowerCAmelCase				)
             lowercase    :Union[str, Any]      	=						tokenizer_p.convert_ids_to_tokens(_lowerCAmelCase				)

             # it is expected that only the first Chinese character is not preceded by "##".
             lowercase    :Dict      	=						[
                 F"##{token}" if idx != 0 else token for idx, token in enumerate(_lowerCAmelCase				)
             ]
             self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)
             self.assertListEqual(_lowerCAmelCase       ,					_lowerCAmelCase				)









import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType




class    __lowerCAmelCase       (							lowerCAmelCase):
       _a 					=						['''image_processor''', '''tokenizer''']
       _a 					=						'''LayoutLMv2ImageProcessor'''
       _a 					=						('''LayoutXLMTokenizer''', '''LayoutXLMTokenizerFast''')






       def __init__(   self:					int       ,					_lowerCAmelCase:					Any=None       ,					_lowerCAmelCase:					List[Any]=None       ,					**_lowerCAmelCase:					Optional[Any]				):
         if "feature_extractor" in kwargs:
           warnings.warn(
               "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
               " instead."       ,					_lowerCAmelCase       ,					)
           lowercase    :Optional[Any]      	=						kwargs.pop("feature_extractor"				)

         lowercase    :Union[str, Any]      	=						image_processor if image_processor is not None else feature_extractor
         if image_processor is None:
           raise ValueError("You need to specify an `image_processor`."				)
         if tokenizer is None:
           raise ValueError("You need to specify a `tokenizer`."				)

         super().__init__(_lowerCAmelCase       ,					_lowerCAmelCase				)






       def __call__(   self:					List[str]       ,					_lowerCAmelCase:					Optional[Any]       ,					_lowerCAmelCase:					Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None       ,					_lowerCAmelCase:					Optional[Union[PreTokenizedInput, List[PreTokenizedInput]]] = None       ,					_lowerCAmelCase:					Union[List[List[int]], List[List[List[int]]]] = None       ,					_lowerCAmelCase:					Optional[Union[List[int], List[List[int]]]] = None       ,					_lowerCAmelCase:					bool = True       ,					_lowerCAmelCase:					Union[bool, str, PaddingStrategy] = False       ,					_lowerCAmelCase:					Union[bool, str, TruncationStrategy] = None       ,					_lowerCAmelCase:					Optional[int] = None       ,					_lowerCAmelCase:					int = 0       ,					_lowerCAmelCase:					Optional[int] = None       ,					_lowerCAmelCase:					Optional[bool] = None       ,					_lowerCAmelCase:					Optional[bool] = None       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					bool = True       ,					_lowerCAmelCase:					Optional[Union[str, TensorType]] = None       ,					**_lowerCAmelCase:					Tuple       ,					):
         # verify input
         if self.image_processor.apply_ocr and (boxes is not None):
           raise ValueError(
               "You cannot provide bounding boxes "
               "if you initialized the image processor with apply_ocr set to True."				)

         if self.image_processor.apply_ocr and (word_labels is not None):
           raise ValueError(
               "You cannot provide word labels if you initialized the image processor with apply_ocr set to True."				)

         if return_overflowing_tokens is True and return_offsets_mapping is False:
           raise ValueError("You cannot return overflowing tokens without returning the offsets mapping."				)

         # first, apply the image processor
         lowercase    :int      	=						self.image_processor(images=_lowerCAmelCase       ,					return_tensors=_lowerCAmelCase				)

         # second, apply the tokenizer
         if text is not None and self.image_processor.apply_ocr and text_pair is None:
           if isinstance(_lowerCAmelCase       ,					_lowerCAmelCase				):
             lowercase    :int      	=						[text]  # add batch dimension (as the image processor always adds a batch dimension)
           lowercase    :int      	=						features["words"]

         lowercase    :Optional[Any]      	=						self.tokenizer(
             text=text if text is not None else features["words"]       ,					text_pair=text_pair if text_pair is not None else None       ,					boxes=boxes if boxes is not None else features["boxes"]       ,					word_labels=_lowerCAmelCase       ,					add_special_tokens=_lowerCAmelCase       ,					padding=_lowerCAmelCase       ,					truncation=_lowerCAmelCase       ,					max_length=_lowerCAmelCase       ,					stride=_lowerCAmelCase       ,					pad_to_multiple_of=_lowerCAmelCase       ,					return_token_type_ids=_lowerCAmelCase       ,					return_attention_mask=_lowerCAmelCase       ,					return_overflowing_tokens=_lowerCAmelCase       ,					return_special_tokens_mask=_lowerCAmelCase       ,					return_offsets_mapping=_lowerCAmelCase       ,					return_length=_lowerCAmelCase       ,					verbose=_lowerCAmelCase       ,					return_tensors=_lowerCAmelCase       ,					**_lowerCAmelCase       ,					)

         # add pixel values
         lowercase    :Any      	=						features.pop("pixel_values"				)
         if return_overflowing_tokens is True:
           lowercase    :Any      	=						self.get_overflowing_images(_lowerCAmelCase       ,					encoded_inputs["overflow_to_sample_mapping"]				)
         lowercase    :Optional[int]      	=						images

         return encoded_inputs






       def 					SCREAMING_SNAKE_CASE    (   self:					Tuple       ,					_lowerCAmelCase:					Tuple       ,					_lowerCAmelCase:					List[Any]				):
         # in case there's an overflow, ensure each `input_ids` sample is mapped to its corresponding image
         lowercase    :Dict      	=						[]
         for sample_idx in overflow_to_sample_mapping:
           images_with_overflow.append(images[sample_idx]				)

         if len(_lowerCAmelCase				) != len(_lowerCAmelCase				):
           raise ValueError(
               "Expected length of images to be the same as the length of `overflow_to_sample_mapping`, but got"
               F" {len(_lowerCAmelCase				)} and {len(_lowerCAmelCase				)}"				)

         return images_with_overflow






       def 					SCREAMING_SNAKE_CASE    (   self:					Dict       ,					*_lowerCAmelCase:					str       ,					**_lowerCAmelCase:					List[Any]				):
         return self.tokenizer.batch_decode(*_lowerCAmelCase       ,					**_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					str       ,					*_lowerCAmelCase:					Tuple       ,					**_lowerCAmelCase:					Union[str, Any]				):
         return self.tokenizer.decode(*_lowerCAmelCase       ,					**_lowerCAmelCase				)






       @property
       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         return ["input_ids", "bbox", "attention_mask", "image"]






       @property
       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]				):
         warnings.warn(
             "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."       ,					_lowerCAmelCase       ,					)
         return self.image_processor_class






       @property
       def 					SCREAMING_SNAKE_CASE    (   self:					List[Any]				):
         warnings.warn(
             "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."       ,					_lowerCAmelCase       ,					)
         return self.image_processor



