
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


_A						      =				get_logger(__name__)







class   lowerCamelCase	:





					def __init__(self   :					Dict       ,					_A   :					Optional[str] = None     )		->		List[Any]:
									snake_case				  =      (
									    os.path.join(__A       ,					config.EXTRACTED_DATASETS_DIR     ) if cache_dir else config.EXTRACTED_DATASETS_PATH
									)
									snake_case				  =      Extractor





					def 	UpperCAmelCase(self   :					Union[str, Any]       ,					_A   :					str     )		->		str:
									from .file_utils import hash_url_to_filename

									# Path where we extract compressed archives
									# We extract in the cache dir, and get the extracted path name by hashing the original path"
									snake_case				  =      os.path.abspath(__A     )
									return os.path.join(self.extract_dir       ,					hash_url_to_filename(__A     )     )





					def 	UpperCAmelCase(self   :					str       ,					_A   :					str       ,					_A   :					bool     )		->		bool:
									return force_extract or (
									    not os.path.isfile(__A     ) and not (os.path.isdir(__A     ) and os.listdir(__A     ))
									)





					def 	UpperCAmelCase(self   :					List[str]       ,					_A   :					str       ,					_A   :					bool = False     )		->		str:
									snake_case				  =      self.extractor.infer_extractor_format(__A     )
									if not extractor_format:
													return input_path
									snake_case				  =      self._get_output_path(__A     )
									if self._do_extract(__A       ,					__A     ):
													self.extractor.extract(__A       ,					__A       ,					__A     )
									return output_path







class   lowerCamelCase	(						A_						):





					@classmethod
					@abstractmethod
					def 	UpperCAmelCase(cls   :					str       ,					_A   :					Union[Path, str]       ,					**_A   :					Any     )		->		bool:
									...





					@staticmethod
					@abstractmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									...







class   lowerCamelCase	(						A_							,				A_						):
					UpperCAmelCase__       :							Tuple     =	[]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					int     )		->		List[Any]:
									with open(__A       ,					"rb"     ) as f:
													return f.read(__A     )





					@classmethod
					def 	UpperCAmelCase(cls   :					Any       ,					_A   :					Union[Path, str]       ,					_A   :					bytes = b""     )		->		bool:
									if not magic_number:
													snake_case				  =      max(len(__A     ) for cls_magic_number in cls.magic_numbers     )
													try:
																	snake_case				  =      cls.read_magic_number(__A       ,					__A     )
													except OSError:
																	return False
									return any(magic_number.startswith(__A     ) for cls_magic_number in cls.magic_numbers     )







class   lowerCamelCase	(						A_						):





					@classmethod
					def 	UpperCAmelCase(cls   :					Union[str, Any]       ,					_A   :					Union[Path, str]       ,					**_A   :					str     )		->		bool:
									return tarfile.is_tarfile(__A     )





					@staticmethod
					def 	UpperCAmelCase(_A   :					Optional[Any]       ,					_A   :					Any     )		->		str:

									def resolved(_A   :					str     ) -> str:
													return os.path.realpath(os.path.abspath(__A     )     )

									def badpath(_A   :					str       ,					_A   :					str     ) -> bool:
													# joinpath will ignore base if path is absolute
													return not resolved(os.path.join(__A       ,					__A     )     ).startswith(__A     )

									def badlink(_A   :					Optional[int]       ,					_A   :					str     ) -> bool:
													# Links are interpreted relative to the directory containing the link
													snake_case				  =      resolved(os.path.join(__A       ,					os.path.dirname(info.name     )     )     )
													return badpath(info.linkname       ,					base=__A     )

									snake_case				  =      resolved(__A     )

									for finfo in members:
													if badpath(finfo.name       ,					__A     ):
																	logger.error(f'Extraction of {finfo.name} is blocked (illegal path)'     )
													elif finfo.issym() and badlink(__A       ,					__A     ):
																	logger.error(f'Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}'     )
													elif finfo.islnk() and badlink(__A       ,					__A     ):
																	logger.error(f'Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}'     )
													else:
																	yield finfo





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									os.makedirs(__A       ,					exist_ok=__A     )
									snake_case				  =      tarfile.open(__A     )
									tar_file.extractall(__A       ,					members=TarExtractor.safemembers(__A       ,					__A     )     )
									tar_file.close()







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							str     =	[B"\x1F\x8B"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									with gzip.open(__A       ,					"rb"     ) as gzip_file:
													with open(__A       ,					"wb"     ) as extracted_file:
																	shutil.copyfileobj(__A       ,					__A     )







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							List[str]     =	[
					    B"PK\x03\x04",
					    B"PK\x05\x06",  # empty archive
					    B"PK\x07\x08",  # spanned archive
					]





					@classmethod
					def 	UpperCAmelCase(cls   :					List[str]       ,					_A   :					Union[Path, str]       ,					_A   :					bytes = b""     )		->		bool:
									if super().is_extractable(__A       ,					magic_number=__A     ):
													return True
									try:
													# Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
													# From: https://github.com/python/cpython/pull/5053
													from zipfile import (
													    _CD_SIGNATURE,
													    _ECD_DISK_NUMBER,
													    _ECD_DISK_START,
													    _ECD_ENTRIES_TOTAL,
													    _ECD_OFFSET,
													    _ECD_SIZE,
													    _EndRecData,
													    sizeCentralDir,
													    stringCentralDir,
													    structCentralDir,
													)

													with open(__A       ,					"rb"     ) as fp:
																	snake_case				  =      _EndRecData(__A     )
																	if endrec:
																					if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
																									return True  # Empty zipfiles are still zipfiles
																					elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
																									fp.seek(endrec[_ECD_OFFSET]     )  # Central directory is on the same disk
																									if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
																													snake_case				  =      fp.read(__A     )  # CD is where we expect it to be
																													if len(__A     ) == sizeCentralDir:
																																	snake_case				  =      struct.unpack(__A       ,					__A     )  # CD is the right size
																																	if centdir[_CD_SIGNATURE] == stringCentralDir:
																																					return True  # First central directory entry  has correct magic number
													return False
									except Exception:  # catch all errors in case future python versions change the zipfile internals
													return False





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									os.makedirs(__A       ,					exist_ok=__A     )
									with zipfile.ZipFile(__A       ,					"r"     ) as zip_file:
													zip_file.extractall(__A     )
													zip_file.close()







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							Dict     =	[B"\xFD\x37\x7A\x58\x5A\x00"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									with lzma.open(__A     ) as compressed_file:
													with open(__A       ,					"wb"     ) as extracted_file:
																	shutil.copyfileobj(__A       ,					__A     )







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							str     =	[B"Rar!\x1a\x07\x00", B"Rar!\x1a\x07\x01\x00"]  # RAR_ID  # RAR5_ID





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									if not config.RARFILE_AVAILABLE:
													raise ImportError("Please pip install rarfile"     )
									import rarfile

									os.makedirs(__A       ,					exist_ok=__A     )
									snake_case				  =      rarfile.RarFile(__A     )
									rf.extractall(__A     )
									rf.close()







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							int     =	[B"\x28\xb5\x2F\xFD"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									if not config.ZSTANDARD_AVAILABLE:
													raise ImportError("Please pip install zstandard"     )
									import zstandard as zstd

									snake_case				  =      zstd.ZstdDecompressor()
									with open(__A       ,					"rb"     ) as ifh, open(__A       ,					"wb"     ) as ofh:
													dctx.copy_stream(__A       ,					__A     )







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							Optional[Any]     =	[B"\x42\x5A\x68"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									with bza.open(__A       ,					"rb"     ) as compressed_file:
													with open(__A       ,					"wb"     ) as extracted_file:
																	shutil.copyfileobj(__A       ,					__A     )







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							Any     =	[B"\x37\x7A\xBC\xAF\x27\x1C"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									if not config.PY7ZR_AVAILABLE:
													raise ImportError("Please pip install py7zr"     )
									import pyazr

									os.makedirs(__A       ,					exist_ok=__A     )
									with pyazr.SevenZipFile(__A       ,					"r"     ) as archive:
													archive.extractall(__A     )







class   lowerCamelCase	(						A_						):
					UpperCAmelCase__       :							Union[str, Any]     =	[B"\x04\x22\x4D\x18"]





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]     )		->		None:
									if not config.LZ4_AVAILABLE:
													raise ImportError("Please pip install lz4"     )
									import lza.frame

									with lza.frame.open(__A       ,					"rb"     ) as compressed_file:
													with open(__A       ,					"wb"     ) as extracted_file:
																	shutil.copyfileobj(__A       ,					__A     )







class   lowerCamelCase	:
					UpperCAmelCase__       :							Any     =	{
					    "tar": TarExtractor,
					    "gzip": GzipExtractor,
					    "zip": ZipExtractor,
					    "xz": XzExtractor,
					    "rar": RarExtractor,
					    "zstd": ZstdExtractor,
					    "bz2": BzipaExtractor,
					    "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
					    "lz4": LzaExtractor,  # <Added version="2.4.0"/>
					}





					@classmethod
					def 	UpperCAmelCase(cls   :					Any     )		->		List[Any]:
									return max(
									    len(__A     )
									    for extractor in cls.extractors.values()
									    if issubclass(__A       ,					__A     )
									    for extractor_magic_number in extractor.magic_numbers     )





					@staticmethod
					def 	UpperCAmelCase(_A   :					Union[Path, str]       ,					_A   :					int     )		->		Tuple:
									try:
													return MagicNumberBaseExtractor.read_magic_number(__A       ,					magic_number_length=__A     )
									except OSError:
													return b""





					@classmethod
					def 	UpperCAmelCase(cls   :					int       ,					_A   :					Union[Path, str]       ,					_A   :					bool = False     )		->		bool:
									warnings.warn(
									    "Method \'is_extractable\' was deprecated in version 2.4.0 and will be removed in 3.0.0. "
									    "Use \'infer_extractor_format\' instead."       ,					category=__A       ,					)
									snake_case				  =      cls.infer_extractor_format(__A     )
									if extractor_format:
													return True if not return_extractor else (True, cls.extractors[extractor_format])
									return False if not return_extractor else (False, None)





					@classmethod
					def 	UpperCAmelCase(cls   :					Any       ,					_A   :					Union[Path, str]     )		->		str:  # <Added version="2.4.0"/>
									snake_case				  =      cls._get_magic_number_max_length()
									snake_case				  =      cls._read_magic_number(__A       ,					__A     )
									for extractor_format, extractor in cls.extractors.items():
													if extractor.is_extractable(__A       ,					magic_number=__A     ):
																	return extractor_format





					@classmethod
					def 	UpperCAmelCase(cls   :					Any       ,					_A   :					Union[Path, str]       ,					_A   :					Union[Path, str]       ,					_A   :					Optional[str] = None       ,					_A   :					Optional[BaseExtractor] = "deprecated"       ,					)		->		None:
									os.makedirs(os.path.dirname(__A     )       ,					exist_ok=__A     )
									# Prevent parallel extractions
									snake_case				  =      str(Path(__A     ).with_suffix(".lock"     )     )
									with FileLock(__A     ):
													shutil.rmtree(__A       ,					ignore_errors=__A     )
													if extractor_format or extractor != "deprecated":
																	if extractor != "deprecated" or not isinstance(__A       ,					__A     ):  # passed as positional arg
																					warnings.warn(
																					    "Parameter \'extractor\' was deprecated in version 2.4.0 and will be removed in 3.0.0. "
																					    "Use \'extractor_format\' instead."       ,					category=__A       ,					)
																					snake_case				  =      extractor if extractor != "deprecated" else extractor_format
																	else:
																					snake_case				  =      cls.extractors[extractor_format]
																	return extractor.extract(__A       ,					__A     )
													else:
																	warnings.warn(
																	    "Parameter \'extractor_format\' was made required in version 2.4.0 and not passing it will raise an "
																	    "exception in 3.0.0."       ,					category=__A       ,					)
																	for extractor in cls.extractors.values():
																					if extractor.is_extractable(__A     ):
																									return extractor.extract(__A       ,					__A     )



import unittest

import numpy as np

from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
   import torch

if is_pytesseract_available():
   from PIL import Image

   from transformers import LayoutLMvaImageProcessor







class   lowerCamelCase	(						unittest.TestCase						):





     def __init__(self   :					Optional[Any]       ,					_A   :					List[str]       ,					_A   :					Tuple=7       ,					_A   :					List[str]=3       ,					_A   :					Dict=1_8       ,					_A   :					int=3_0       ,					_A   :					str=4_0_0       ,					_A   :					List[str]=True       ,					_A   :					Optional[int]=None       ,					_A   :					Optional[int]=True       ,					)		->		Dict:
         snake_case				  =      size if size is not None else {"height": 1_8, "width": 1_8}
         snake_case				  =      parent
         snake_case				  =      batch_size
         snake_case				  =      num_channels
         snake_case				  =      image_size
         snake_case				  =      min_resolution
         snake_case				  =      max_resolution
         snake_case				  =      do_resize
         snake_case				  =      size
         snake_case				  =      apply_ocr





     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		int:
         return {"do_resize": self.do_resize, "size": self.size, "apply_ocr": self.apply_ocr}







@require_torch
@require_pytesseract
class   lowerCamelCase	(						A_							,				unittest.TestCase						):
     UpperCAmelCase__       :							str     =	LayoutLMvaImageProcessor if is_pytesseract_available() else None





     def 	UpperCAmelCase(self   :					List[str]     )		->		Dict:
         snake_case				  =      LayoutLMvaImageProcessingTester(self     )





     @property
     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		int:
         return self.image_processor_tester.prepare_image_processor_dict()





     def 	UpperCAmelCase(self   :					Any     )		->		Optional[int]:
         snake_case				  =      self.image_processing_class(**self.image_processor_dict     )
         self.assertTrue(hasattr(_A       ,					"do_resize"     )     )
         self.assertTrue(hasattr(_A       ,					"size"     )     )
         self.assertTrue(hasattr(_A       ,					"apply_ocr"     )     )





     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		List[Any]:
         snake_case				  =      self.image_processing_class.from_dict(self.image_processor_dict     )
         self.assertEqual(image_processor.size       ,					{"height": 1_8, "width": 1_8}     )

         snake_case				  =      self.image_processing_class.from_dict(self.image_processor_dict       ,					size=4_2     )
         self.assertEqual(image_processor.size       ,					{"height": 4_2, "width": 4_2}     )





     def 	UpperCAmelCase(self   :					List[Any]     )		->		Optional[Any]:
         pass





     def 	UpperCAmelCase(self   :					Dict     )		->		Optional[int]:
         # Initialize image_processing
         snake_case				  =      self.image_processing_class(**self.image_processor_dict     )
         # create random PIL images
         snake_case				  =      prepare_image_inputs(self.image_processor_tester       ,					equal_resolution=_A     )
         for image in image_inputs:
             self.assertIsInstance(_A       ,					Image.Image     )

         # Test not batched input
         snake_case				  =      image_processing(image_inputs[0]       ,					return_tensors="pt"     )
         self.assertEqual(
             encoding.pixel_values.shape       ,					(
                 1,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)

         self.assertIsInstance(encoding.words       ,					_A     )
         self.assertIsInstance(encoding.boxes       ,					_A     )

         # Test batched
         snake_case				  =      image_processing(_A       ,					return_tensors="pt"     ).pixel_values
         self.assertEqual(
             encoded_images.shape       ,					(
                 self.image_processor_tester.batch_size,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)





     def 	UpperCAmelCase(self   :					Tuple     )		->		List[str]:
         # Initialize image_processing
         snake_case				  =      self.image_processing_class(**self.image_processor_dict     )
         # create random numpy tensors
         snake_case				  =      prepare_image_inputs(self.image_processor_tester       ,					equal_resolution=_A       ,					numpify=_A     )
         for image in image_inputs:
             self.assertIsInstance(_A       ,					np.ndarray     )

         # Test not batched input
         snake_case				  =      image_processing(image_inputs[0]       ,					return_tensors="pt"     ).pixel_values
         self.assertEqual(
             encoded_images.shape       ,					(
                 1,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)

         # Test batched
         snake_case				  =      image_processing(_A       ,					return_tensors="pt"     ).pixel_values
         self.assertEqual(
             encoded_images.shape       ,					(
                 self.image_processor_tester.batch_size,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)





     def 	UpperCAmelCase(self   :					Optional[Any]     )		->		Tuple:
         # Initialize image_processing
         snake_case				  =      self.image_processing_class(**self.image_processor_dict     )
         # create random PyTorch tensors
         snake_case				  =      prepare_image_inputs(self.image_processor_tester       ,					equal_resolution=_A       ,					torchify=_A     )
         for image in image_inputs:
             self.assertIsInstance(_A       ,					torch.Tensor     )

         # Test not batched input
         snake_case				  =      image_processing(image_inputs[0]       ,					return_tensors="pt"     ).pixel_values
         self.assertEqual(
             encoded_images.shape       ,					(
                 1,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)

         # Test batched
         snake_case				  =      image_processing(_A       ,					return_tensors="pt"     ).pixel_values
         self.assertEqual(
             encoded_images.shape       ,					(
                 self.image_processor_tester.batch_size,
                 self.image_processor_tester.num_channels,
                 self.image_processor_tester.size["height"],
                 self.image_processor_tester.size["width"],
             )       ,					)





     def 	UpperCAmelCase(self   :					Any     )		->		List[str]:
         # with apply_OCR = True
         snake_case				  =      LayoutLMvaImageProcessor()

         from datasets import load_dataset

         snake_case				  =      load_dataset("hf-internal-testing/fixtures_docvqa"       ,					split="test"     )

         snake_case				  =      Image.open(ds[0]["file"]     ).convert("RGB"     )

         snake_case				  =      image_processing(_A       ,					return_tensors="pt"     )

         self.assertEqual(encoding.pixel_values.shape       ,					(1, 3, 2_2_4, 2_2_4)     )
         self.assertEqual(len(encoding.words     )       ,					len(encoding.boxes     )     )

         # fmt: off
         # the words and boxes were obtained with Tesseract 4.1.1
         snake_case				  =      [["11:14", "to", "11:39", "a.m", "11:39", "to", "11:44", "a.m.", "11:44", "a.m.", "to", "12:25", "p.m.", "12:25", "to", "12:58", "p.m.", "12:58", "to", "4:00", "p.m.", "2:00", "to", "5:00", "p.m.", "Coffee", "Break", "Coffee", "will", "be", "served", "for", "men", "and", "women", "in", "the", "lobby", "adjacent", "to", "exhibit", "area.", "Please", "move", "into", "exhibit", "area.", "(Exhibits", "Open)", "TRRF", "GENERAL", "SESSION", "(PART", "|)", "Presiding:", "Lee", "A.", "Waller", "TRRF", "Vice", "President", "“Introductory", "Remarks”", "Lee", "A.", "Waller,", "TRRF", "Vice", "Presi-", "dent", "Individual", "Interviews", "with", "TRRF", "Public", "Board", "Members", "and", "Sci-", "entific", "Advisory", "Council", "Mem-", "bers", "Conducted", "by", "TRRF", "Treasurer", "Philip", "G.", "Kuehn", "to", "get", "answers", "which", "the", "public", "refrigerated", "warehousing", "industry", "is", "looking", "for.", "Plus", "questions", "from", "the", "floor.", "Dr.", "Emil", "M.", "Mrak,", "University", "of", "Cal-", "ifornia,", "Chairman,", "TRRF", "Board;", "Sam", "R.", "Cecil,", "University", "of", "Georgia", "College", "of", "Agriculture;", "Dr.", "Stanley", "Charm,", "Tufts", "University", "School", "of", "Medicine;", "Dr.", "Robert", "H.", "Cotton,", "ITT", "Continental", "Baking", "Company;", "Dr.", "Owen", "Fennema,", "University", "of", "Wis-", "consin;", "Dr.", "Robert", "E.", "Hardenburg,", "USDA.", "Questions", "and", "Answers", "Exhibits", "Open", "Capt.", "Jack", "Stoney", "Room", "TRRF", "Scientific", "Advisory", "Council", "Meeting", "Ballroom", "Foyer"]]  # noqa: E231
         snake_case				  =      [[[1_4_1, 5_7, 2_1_4, 6_9], [2_2_8, 5_8, 2_5_2, 6_9], [1_4_1, 7_5, 2_1_6, 8_8], [2_3_0, 7_9, 2_8_0, 8_8], [1_4_2, 2_6_0, 2_1_8, 2_7_3], [2_3_0, 2_6_1, 2_5_5, 2_7_3], [1_4_3, 2_7_9, 2_1_8, 2_9_0], [2_3_1, 2_8_2, 2_9_0, 2_9_1], [1_4_3, 3_4_2, 2_1_8, 3_5_4], [2_3_1, 3_4_5, 2_8_9, 3_5_5], [2_0_2, 3_6_2, 2_2_7, 3_7_3], [1_4_3, 3_7_9, 2_2_0, 3_9_2], [2_3_1, 3_8_2, 2_9_1, 3_9_4], [1_4_4, 7_1_4, 2_2_0, 7_2_6], [2_3_1, 7_1_5, 2_5_6, 7_2_6], [1_4_4, 7_3_2, 2_2_0, 7_4_5], [2_3_2, 7_3_6, 2_9_1, 7_4_7], [1_4_4, 7_6_9, 2_1_8, 7_8_2], [2_3_1, 7_7_0, 2_5_6, 7_8_2], [1_4_1, 7_8_8, 2_0_2, 8_0_1], [2_1_5, 7_9_1, 2_7_4, 8_0_4], [1_4_3, 8_2_6, 2_0_4, 8_3_8], [2_1_5, 8_2_6, 2_4_0, 8_3_8], [1_4_2, 8_4_4, 2_0_2, 8_5_7], [2_1_5, 8_4_7, 2_7_4, 8_5_9], [3_3_4, 5_7, 4_2_7, 6_9], [4_4_0, 5_7, 5_2_2, 6_9], [3_6_9, 7_5, 4_6_1, 8_8], [4_6_9, 7_5, 5_1_6, 8_8], [5_2_8, 7_6, 5_6_2, 8_8], [5_7_0, 7_6, 6_6_7, 8_8], [6_7_5, 7_5, 7_1_1, 8_7], [7_2_1, 7_9, 7_7_8, 8_8], [7_8_9, 7_5, 8_4_0, 8_8], [3_6_9, 9_7, 4_7_0, 1_0_7], [4_8_4, 9_4, 5_0_7, 1_0_6], [5_1_8, 9_4, 5_6_2, 1_0_7], [5_7_6, 9_4, 6_5_5, 1_1_0], [6_6_8, 9_4, 7_9_2, 1_0_9], [8_0_4, 9_5, 8_2_9, 1_0_7], [3_6_9, 1_1_3, 4_6_5, 1_2_5], [4_7_7, 1_1_6, 5_4_7, 1_2_5], [5_6_2, 1_1_3, 6_5_8, 1_2_5], [6_7_1, 1_1_6, 7_4_8, 1_2_5], [7_6_1, 1_1_3, 8_1_1, 1_2_5], [3_6_9, 1_3_1, 4_6_5, 1_4_3], [4_7_7, 1_3_3, 5_4_8, 1_4_3], [5_6_3, 1_3_0, 6_9_8, 1_4_5], [7_1_0, 1_3_0, 8_0_2, 1_4_6], [3_3_6, 1_7_1, 4_1_2, 1_8_3], [4_2_3, 1_7_1, 5_7_2, 1_8_3], [5_8_2, 1_7_0, 7_1_6, 1_8_4], [7_2_8, 1_7_1, 8_1_7, 1_8_7], [8_2_9, 1_7_1, 8_4_4, 1_8_6], [3_3_8, 1_9_7, 4_8_2, 2_1_2], [5_0_7, 1_9_6, 5_5_7, 2_0_9], [5_6_9, 1_9_6, 5_9_5, 2_0_8], [6_1_0, 1_9_6, 7_0_2, 2_0_9], [5_0_5, 2_1_4, 5_8_3, 2_2_6], [5_9_5, 2_1_4, 6_5_6, 2_2_7], [6_7_0, 2_1_5, 8_0_7, 2_2_7], [3_3_5, 2_5_9, 5_4_3, 2_7_4], [5_5_6, 2_5_9, 7_0_8, 2_7_2], [3_7_2, 2_7_9, 4_2_2, 2_9_1], [4_3_5, 2_7_9, 4_6_0, 2_9_1], [4_7_4, 2_7_9, 5_7_4, 2_9_2], [5_8_7, 2_7_8, 6_6_4, 2_9_1], [6_7_6, 2_7_8, 7_3_8, 2_9_1], [7_5_1, 2_7_9, 8_3_4, 2_9_1], [3_7_2, 2_9_8, 4_3_4, 3_1_0], [3_3_5, 3_4_1, 4_8_3, 3_5_4], [4_9_7, 3_4_1, 6_5_5, 3_5_4], [6_6_7, 3_4_1, 7_2_8, 3_5_4], [7_4_0, 3_4_1, 8_2_5, 3_5_4], [3_3_5, 3_6_0, 4_3_0, 3_7_2], [4_4_2, 3_6_0, 5_3_4, 3_7_2], [5_4_5, 3_5_9, 6_8_7, 3_7_2], [6_9_7, 3_6_0, 7_5_4, 3_7_2], [7_6_5, 3_6_0, 8_2_3, 3_7_3], [3_3_4, 3_7_8, 4_2_8, 3_9_1], [4_4_0, 3_7_8, 5_7_7, 3_9_4], [5_9_0, 3_7_8, 7_0_5, 3_9_1], [7_2_0, 3_7_8, 8_0_1, 3_9_1], [3_3_4, 3_9_7, 4_0_0, 4_0_9], [3_7_0, 4_1_6, 5_2_9, 4_2_9], [5_4_4, 4_1_6, 5_7_6, 4_3_2], [5_8_7, 4_1_6, 6_6_5, 4_2_8], [6_7_7, 4_1_6, 8_1_4, 4_2_9], [3_7_2, 4_3_5, 4_5_2, 4_5_0], [4_6_5, 4_3_4, 4_9_5, 4_4_7], [5_1_1, 4_3_4, 6_0_0, 4_4_7], [6_1_1, 4_3_6, 6_3_7, 4_4_7], [6_4_9, 4_3_6, 6_9_4, 4_5_1], [7_0_5, 4_3_8, 8_2_4, 4_4_7], [3_6_9, 4_5_3, 4_5_2, 4_6_6], [4_6_4, 4_5_4, 5_0_9, 4_6_6], [5_2_2, 4_5_3, 6_1_1, 4_6_9], [6_2_5, 4_5_3, 7_9_2, 4_6_9], [3_7_0, 4_7_2, 5_5_6, 4_8_8], [5_7_0, 4_7_2, 6_8_4, 4_8_7], [6_9_7, 4_7_2, 7_1_8, 4_8_5], [7_3_2, 4_7_2, 8_3_5, 4_8_8], [3_6_9, 4_9_0, 4_1_1, 5_0_3], [4_2_5, 4_9_0, 4_8_4, 5_0_3], [4_9_6, 4_9_0, 6_3_5, 5_0_6], [6_4_5, 4_9_0, 7_0_7, 5_0_3], [7_1_8, 4_9_1, 7_6_1, 5_0_3], [7_7_1, 4_9_0, 8_4_0, 5_0_3], [3_3_6, 5_1_0, 3_7_4, 5_2_1], [3_8_8, 5_1_0, 4_4_7, 5_2_2], [4_6_0, 5_1_0, 4_8_9, 5_2_1], [5_0_3, 5_1_0, 5_8_0, 5_2_2], [5_9_2, 5_0_9, 7_3_6, 5_2_5], [7_4_5, 5_0_9, 7_7_0, 5_2_2], [7_8_1, 5_0_9, 8_4_0, 5_2_2], [3_3_8, 5_2_8, 4_3_4, 5_4_1], [4_4_8, 5_2_8, 5_9_6, 5_4_1], [6_0_9, 5_2_7, 6_8_7, 5_4_0], [7_0_0, 5_2_8, 7_9_2, 5_4_1], [3_3_6, 5_4_6, 3_9_7, 5_5_9], [4_0_7, 5_4_6, 4_3_1, 5_5_9], [4_4_3, 5_4_6, 5_2_5, 5_6_0], [5_3_7, 5_4_6, 6_8_0, 5_6_2], [6_8_8, 5_4_6, 7_1_4, 5_5_9], [7_2_2, 5_4_6, 8_3_7, 5_6_2], [3_3_6, 5_6_5, 4_4_9, 5_8_1], [4_6_1, 5_6_5, 4_8_5, 5_7_7], [4_9_7, 5_6_5, 6_6_5, 5_8_1], [6_8_1, 5_6_5, 7_1_8, 5_7_7], [7_3_2, 5_6_5, 8_3_7, 5_8_0], [3_3_7, 5_8_4, 4_3_8, 5_9_7], [4_5_2, 5_8_3, 5_2_1, 5_9_6], [5_3_5, 5_8_4, 6_7_7, 5_9_9], [6_9_0, 5_8_3, 7_8_7, 5_9_6], [8_0_1, 5_8_3, 8_2_5, 5_9_6], [3_3_8, 6_0_2, 4_7_8, 6_1_5], [4_9_2, 6_0_2, 5_3_0, 6_1_4], [5_4_3, 6_0_2, 6_3_8, 6_1_5], [6_5_0, 6_0_2, 6_7_6, 6_1_4], [6_8_8, 6_0_2, 7_8_8, 6_1_5], [8_0_2, 6_0_2, 8_4_3, 6_1_4], [3_3_7, 6_2_1, 5_0_2, 6_3_3], [5_1_6, 6_2_1, 6_1_5, 6_3_7], [6_2_9, 6_2_1, 7_7_4, 6_3_6], [7_8_9, 6_2_1, 8_2_7, 6_3_3], [3_3_7, 6_3_9, 4_1_8, 6_5_2], [4_3_2, 6_4_0, 5_7_1, 6_5_3], [5_8_7, 6_3_9, 7_3_1, 6_5_5], [7_4_3, 6_3_9, 7_6_9, 6_5_2], [7_8_0, 6_3_9, 8_4_1, 6_5_2], [3_3_8, 6_5_8, 4_4_0, 6_7_3], [4_5_5, 6_5_8, 4_9_1, 6_7_0], [5_0_8, 6_5_8, 6_0_2, 6_7_1], [6_1_6, 6_5_8, 6_3_8, 6_7_0], [6_5_4, 6_5_8, 8_3_5, 6_7_4], [3_3_7, 6_7_7, 4_2_9, 6_8_9], [3_3_7, 7_1_4, 4_8_2, 7_2_6], [4_9_5, 7_1_4, 5_4_8, 7_2_6], [5_6_1, 7_1_4, 6_8_3, 7_2_6], [3_3_8, 7_7_0, 4_6_1, 7_8_2], [4_7_4, 7_6_9, 5_5_4, 7_8_5], [4_8_9, 7_8_8, 5_6_2, 8_0_3], [5_7_6, 7_8_8, 6_4_3, 8_0_1], [6_5_6, 7_8_7, 7_5_1, 8_0_4], [7_6_4, 7_8_8, 8_4_4, 8_0_1], [3_3_4, 8_2_5, 4_2_1, 8_3_8], [4_3_0, 8_2_4, 5_7_4, 8_3_8], [5_8_4, 8_2_4, 7_2_3, 8_4_1], [3_3_5, 8_4_4, 4_5_0, 8_5_7], [4_6_4, 8_4_3, 5_8_3, 8_6_0], [6_2_8, 8_6_2, 7_5_5, 8_7_5], [7_6_9, 8_6_1, 8_4_8, 8_7_8]]]  # noqa: E231
         # fmt: on

         self.assertListEqual(encoding.words       ,					_A     )
         self.assertListEqual(encoding.boxes       ,					_A     )

         # with apply_OCR = False
         snake_case				  =      LayoutLMvaImageProcessor(apply_ocr=_A     )

         snake_case				  =      image_processing(_A       ,					return_tensors="pt"     )

         self.assertEqual(encoding.pixel_values.shape       ,					(1, 3, 2_2_4, 2_2_4)     )

