





'''simple docstring'''


import os
import zipfile

import pytest

from datasets.utils.extract import (
    BzipaExtractor,
    Extractor,
    GzipExtractor,
    LzaExtractor,
    SevenZipExtractor,
    TarExtractor,
    XzExtractor,
    ZipExtractor,
    ZstdExtractor,
)

from .utils import require_lza, require_pyazr, require_zstandard
@pytest.mark.parametrize(
    "compression_format, is_archive"     ,[
        ("7z", True),
        ("bz2", False),
        ("gzip", False),
        ("lz4", False),
        ("tar", True),
        ("xz", False),
        ("zip", True),
        ("zstd", False),
    ]     ,)
def 							UpperCAmelCase_  (						__lowerCamelCase : List[Any]     ,__lowerCamelCase : Optional[int]     ,__lowerCamelCase : Optional[int]     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : Any     ,__lowerCamelCase : Union[str, Any]     ,__lowerCamelCase : List[Any]     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : Any     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : Optional[int]     ,__lowerCamelCase : List[str]     ,):
   lowercase_      :Union[str, Any]         =			{
       "7z": (seven_zip_file, SevenZipExtractor),
       "bz2": (bza_file, BzipaExtractor),
       "gzip": (gz_file, GzipExtractor),
       "lz4": (lza_file, LzaExtractor),
       "tar": (tar_file, TarExtractor),
       "xz": (xz_file, XzExtractor),
       "zip": (zip_file, ZipExtractor),
       "zstd": (zstd_file, ZstdExtractor),
   }
   lowercase_      ,							lowercase_      :Union[str, Any]         =			input_paths_and_base_extractors[compression_format]
   if input_path is None:
      lowercase_      :Optional[Any]         =			F'for \'{compression_format}\' compression_format, '
      if compression_format == "7z":
         reason += require_pyazr.kwargs["reason"]
      elif compression_format == "lz4":
         reason += require_lza.kwargs["reason"]
      elif compression_format == "zstd":
         reason += require_zstandard.kwargs["reason"]
      pytest.skip(__lowerCamelCase			)
   assert base_extractor.is_extractable(__lowerCamelCase			)
   lowercase_      :Dict         =			tmp_path / ("extracted" if is_archive else "extracted.txt")
   base_extractor.extract(__lowerCamelCase     ,__lowerCamelCase			)
   if is_archive:
      assert output_path.is_dir()
      for file_path in output_path.iterdir():
         assert file_path.name == text_file.name
         lowercase_      :Optional[int]         =			file_path.read_text(encoding="utf-8"			)
   else:
      lowercase_      :Union[str, Any]         =			output_path.read_text(encoding="utf-8"			)
   lowercase_      :Union[str, Any]         =			text_file.read_text(encoding="utf-8"			)
   assert extracted_file_content == expected_file_content
@pytest.mark.parametrize(
    "compression_format, is_archive"     ,[
        ("7z", True),
        ("bz2", False),
        ("gzip", False),
        ("lz4", False),
        ("tar", True),
        ("xz", False),
        ("zip", True),
        ("zstd", False),
    ]     ,)
def 							UpperCAmelCase_  (						__lowerCamelCase : Tuple     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : Optional[int]     ,__lowerCamelCase : Optional[Any]     ,__lowerCamelCase : int     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : Union[str, Any]     ,__lowerCamelCase : Any     ,__lowerCamelCase : Union[str, Any]     ,__lowerCamelCase : Tuple     ,__lowerCamelCase : Any     ,__lowerCamelCase : Union[str, Any]     ,):
   lowercase_      :str         =			{
       "7z": seven_zip_file,
       "bz2": bza_file,
       "gzip": gz_file,
       "lz4": lza_file,
       "tar": tar_file,
       "xz": xz_file,
       "zip": zip_file,
       "zstd": zstd_file,
   }
   lowercase_      :List[str]         =			input_paths[compression_format]
   if input_path is None:
      lowercase_      :Optional[Any]         =			F'for \'{compression_format}\' compression_format, '
      if compression_format == "7z":
         reason += require_pyazr.kwargs["reason"]
      elif compression_format == "lz4":
         reason += require_lza.kwargs["reason"]
      elif compression_format == "zstd":
         reason += require_zstandard.kwargs["reason"]
      pytest.skip(__lowerCamelCase			)
   lowercase_      :Tuple         =			Extractor.infer_extractor_format(__lowerCamelCase			)
   assert extractor_format is not None
   lowercase_      :List[str]         =			tmp_path / ("extracted" if is_archive else "extracted.txt")
   Extractor.extract(__lowerCamelCase     ,__lowerCamelCase     ,__lowerCamelCase			)
   if is_archive:
      assert output_path.is_dir()
      for file_path in output_path.iterdir():
         assert file_path.name == text_file.name
         lowercase_      :Optional[Any]         =			file_path.read_text(encoding="utf-8"			)
   else:
      lowercase_      :List[str]         =			output_path.read_text(encoding="utf-8"			)
   lowercase_      :Tuple         =			text_file.read_text(encoding="utf-8"			)
   assert extracted_file_content == expected_file_content
@pytest.fixture
def 							UpperCAmelCase_  (						__lowerCamelCase : str     ,__lowerCamelCase : int			):
   import tarfile

   lowercase_      :Tuple         =			tmp_path / "data_dot_dot"
   directory.mkdir()
   lowercase_      :Union[str, Any]         =			directory / "tar_file_with_dot_dot.tar"
   with tarfile.TarFile(__lowerCamelCase     ,"w"			) as f:
      f.add(__lowerCamelCase     ,arcname=os.path.join(".."     ,text_file.name			)			)
   return path
@pytest.fixture
def 							UpperCAmelCase_  (						__lowerCamelCase : Union[str, Any]			):
   import tarfile

   lowercase_      :Tuple         =			tmp_path / "data_sym_link"
   directory.mkdir()
   lowercase_      :Tuple         =			directory / "tar_file_with_sym_link.tar"
   os.symlink(".."     ,directory / "subdir"     ,target_is_directory=__lowerCamelCase			)
   with tarfile.TarFile(__lowerCamelCase     ,"w"			) as f:
      f.add(str(directory / "subdir"			)     ,arcname="subdir"			)  # str required by os.readlink on Windows and Python < 3.8
   return path
@pytest.mark.parametrize(
    "insecure_tar_file, error_log"     ,[("tar_file_with_dot_dot", "illegal path"), ("tar_file_with_sym_link", "Symlink")]     ,)
def 							UpperCAmelCase_  (						__lowerCamelCase : Optional[Any]     ,__lowerCamelCase : str     ,__lowerCamelCase : Optional[int]     ,__lowerCamelCase : Any     ,__lowerCamelCase : Optional[Any]     ,__lowerCamelCase : List[str]			):
   lowercase_      :Tuple         =			{
       "tar_file_with_dot_dot": tar_file_with_dot_dot,
       "tar_file_with_sym_link": tar_file_with_sym_link,
   }
   lowercase_      :Dict         =			insecure_tar_files[insecure_tar_file]
   lowercase_      :int         =			tmp_path / "extracted"
   TarExtractor.extract(__lowerCamelCase     ,__lowerCamelCase			)
   assert caplog.text
   for record in caplog.records:
      assert record.levelname == "ERROR"
      assert error_log in record.msg


def 							UpperCAmelCase_  (						__lowerCamelCase : int			):
   # We should have less false positives than zipfile.is_zipfile
   # We do that by checking only the magic number
   lowercase_      :Any         =			tmpdir / "not_a_zip_file"
   # From: https://github.com/python/cpython/pull/5053
   lowercase_      :Any         =			(
       B"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00"
       B"\x00\x02\x08\x06\x00\x00\x00\x99\x81\xb6'\x00\x00\x00\x15I"
       B"DATx\x01\x01\n\x00\xf5\xff\x00PK\x05\x06\x00PK\x06\x06\x07"
       B"\xac\x01N\xc6|a\r\x00\x00\x00\x00IEND\xaeB`\x82"
   )
   with not_a_zip_file.open("wb"			) as f:
      f.write(__lowerCamelCase			)
   assert zipfile.is_zipfile(str(__lowerCamelCase			)			)  # is a false positive for `zipfile`
   assert not ZipExtractor.is_extractable(__lowerCamelCase			)  # but we're right









'''simple docstring'''


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 				a_       (    _lowerCAmelCase							):
     __A								=      ["image_processor", "tokenizer"]
     __A								=      "LayoutLMv3ImageProcessor"
     __A								=      ("LayoutLMv3Tokenizer", "LayoutLMv3TokenizerFast")





     def __init__(			self		: int     ,				lowercase		: Optional[Any]=None     ,				lowercase		: List[str]=None     ,				**lowercase		: Optional[int]						):





        """simple docstring"""




        lowercase_      :int         =			None
        if "feature_extractor" in kwargs:
           warnings.warn(
               "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
               " instead."     ,				lowercase     ,				)
           lowercase_      :Optional[int]         =			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__(lowercase     ,				lowercase						)





     def __call__(			self		: Optional[Any]     ,				lowercase		: List[str]     ,				lowercase		: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     ,				lowercase		: Optional[Union[PreTokenizedInput, List[PreTokenizedInput]]] = None     ,				lowercase		: Union[List[List[int]], List[List[List[int]]]] = None     ,				lowercase		: Optional[Union[List[int], List[List[int]]]] = None     ,				lowercase		: bool = True     ,				lowercase		: Union[bool, str, PaddingStrategy] = False     ,				lowercase		: Union[bool, str, TruncationStrategy] = None     ,				lowercase		: Optional[int] = None     ,				lowercase		: int = 0     ,				lowercase		: Optional[int] = None     ,				lowercase		: Optional[bool] = None     ,				lowercase		: Optional[bool] = None     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = False     ,				lowercase		: bool = True     ,				lowercase		: Optional[Union[str, TensorType]] = None     ,				**lowercase		: List[Any]     ,				):





        """simple docstring"""




        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."						)

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

        # second, apply the tokenizer
        if text is not None and self.image_processor.apply_ocr and text_pair is None:
           if isinstance(lowercase     ,				lowercase						):
              lowercase_      :str         =			[text]  # add batch dimension (as the image processor always adds a batch dimension)
           lowercase_      :Union[str, Any]         =			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=lowercase     ,				add_special_tokens=lowercase     ,				padding=lowercase     ,				truncation=lowercase     ,				max_length=lowercase     ,				stride=lowercase     ,				pad_to_multiple_of=lowercase     ,				return_token_type_ids=lowercase     ,				return_attention_mask=lowercase     ,				return_overflowing_tokens=lowercase     ,				return_special_tokens_mask=lowercase     ,				return_offsets_mapping=lowercase     ,				return_length=lowercase     ,				verbose=lowercase     ,				return_tensors=lowercase     ,				**lowercase     ,				)

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

        return encoded_inputs





     def 							lowercase__				(			self		: List[Any]     ,				lowercase		: Any     ,				lowercase		: Optional[Any]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			[]
        for sample_idx in overflow_to_sample_mapping:
           images_with_overflow.append(images[sample_idx]						)

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

        return images_with_overflow





     def 							lowercase__				(			self		: Union[str, Any]     ,				*lowercase		: List[Any]     ,				**lowercase		: Optional[Any]						):





        """simple docstring"""




        return self.tokenizer.batch_decode(*lowercase     ,				**lowercase						)





     def 							lowercase__				(			self		: List[Any]     ,				*lowercase		: Any     ,				**lowercase		: str						):





        """simple docstring"""




        return self.tokenizer.decode(*lowercase     ,				**lowercase						)





     @property
     def 							lowercase__				(			self		: Optional[Any]						):





        """simple docstring"""




        return ["input_ids", "bbox", "attention_mask", "pixel_values"]





     @property
     def 							lowercase__				(			self		: str						):





        """simple docstring"""




        warnings.warn(
            "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."     ,				lowercase     ,				)
        return self.image_processor_class







     @property
     def 							lowercase__				(			self		: Tuple						):





        """simple docstring"""




        warnings.warn(
            "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."     ,				lowercase     ,				)
        return self.image_processor


