

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__				(			_A      : List[str]	,      _A      : Tuple	,      _A      : Tuple	,      _A      : Optional[int]	,      _A      : List[Any]	,      _A      : Union[str, Any]	,      _A      : Union[str, Any]	,      _A      : Optional[int]	,      _A      : Any	,      _A      : Union[str, Any]	,      _A      : str	,      _A      : Dict	,      ):





  '''simple docstring'''







  a__  ={
      '''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),
  }
  a__,      a__  =input_paths_and_base_extractors[compression_format]
  if input_path is None:
    a__  =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(_A							)
  assert base_extractor.is_extractable(_A							)
  a__  =tmp_path / ('''extracted''' if is_archive else '''extracted.txt''')
  base_extractor.extract(_A	,      _A							)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      a__  =file_path.read_text(encoding='''utf-8'''							)
  else:
    a__  =output_path.read_text(encoding='''utf-8'''							)
  a__  =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__				(			_A      : int	,      _A      : Optional[int]	,      _A      : int	,      _A      : Optional[int]	,      _A      : Union[str, Any]	,      _A      : List[Any]	,      _A      : str	,      _A      : Tuple	,      _A      : List[Any]	,      _A      : List[Any]	,      _A      : List[Any]	,      _A      : List[Any]	,      ):





  '''simple docstring'''







  a__  ={
      '''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,
  }
  a__  =input_paths[compression_format]
  if input_path is None:
    a__  =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(_A							)
  a__  =Extractor.infer_extractor_format(_A							)
  assert extractor_format is not None
  a__  =tmp_path / ('''extracted''' if is_archive else '''extracted.txt''')
  Extractor.extract(_A	,      _A	,      _A							)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      a__  =file_path.read_text(encoding='''utf-8'''							)
  else:
    a__  =output_path.read_text(encoding='''utf-8'''							)
  a__  =text_file.read_text(encoding='''utf-8'''							)
  assert extracted_file_content == expected_file_content




@pytest.fixture
def 			UpperCAmelCase__				(			_A      : Tuple	,      _A      : int							):





  '''simple docstring'''







  import tarfile

  a__  =tmp_path / '''data_dot_dot'''
  directory.mkdir()
  a__  =directory / '''tar_file_with_dot_dot.tar'''
  with tarfile.TarFile(_A	,      '''w'''							) as f:
    f.add(_A	,      arcname=os.path.join('''..'''	,      text_file.name							)							)
  return path




@pytest.fixture
def 			UpperCAmelCase__				(			_A      : Any							):





  '''simple docstring'''







  import tarfile

  a__  =tmp_path / '''data_sym_link'''
  directory.mkdir()
  a__  =directory / '''tar_file_with_sym_link.tar'''
  os.symlink('''..'''	,      directory / '''subdir'''	,      target_is_directory=_A							)
  with tarfile.TarFile(_A	,      '''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__				(			_A      : str	,      _A      : Any	,      _A      : Tuple	,      _A      : Dict	,      _A      : int	,      _A      : Tuple							):





  '''simple docstring'''







  a__  ={
      '''tar_file_with_dot_dot''': tar_file_with_dot_dot,
      '''tar_file_with_sym_link''': tar_file_with_sym_link,
  }
  a__  =insecure_tar_files[insecure_tar_file]
  a__  =tmp_path / '''extracted'''
  TarExtractor.extract(_A	,      _A							)
  assert caplog.text
  for record in caplog.records:
    assert record.levelname == "ERROR"
    assert error_log in record.msg




def 			UpperCAmelCase__				(			_A      : List[Any]							):





  '''simple docstring'''







  a__  =tmpdir / '''not_a_zip_file'''
  # From: https://github.com/python/cpython/pull/5053
  a__  =(
      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(_A							)
  assert zipfile.is_zipfile(str(_A							)							)  # is a false positive for `zipfile`
  assert not ZipExtractor.is_extractable(_A							)  # but we're right



import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin







@skip_mps
class 						__magic_name__			(							lowerCamelCase__		,       lowerCamelCase__		,       unittest.TestCase							):

   '''simple docstring'''




   lowerCamelCase__ :	List[Any]    =   IFInpaintingSuperResolutionPipeline
   lowerCamelCase__ :	str    =   TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'width', 'height'}
   lowerCamelCase__ :	List[Any]    =   TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({'original_image'}							)
   lowerCamelCase__ :	str    =   PipelineTesterMixin.required_optional_params - {'latents'}



   def  _UpperCAmelCase (				self       )							->    Optional[int]:






     """simple docstring"""






     return self._get_superresolution_dummy_components()



   def  _UpperCAmelCase (				self,    lowercase_,    lowercase_=0       )							->    Tuple:






     """simple docstring"""






     if str(lowercase_       ).startswith('''mps'''       ):
       a__  =torch.manual_seed(lowercase_       )
     else:
       a__  =torch.Generator(device=lowercase_       ).manual_seed(lowercase_       )

     a__  =floats_tensor((1, 3, 16, 16),    rng=random.Random(lowercase_       )       ).to(lowercase_       )
     a__  =floats_tensor((1, 3, 32, 32),    rng=random.Random(lowercase_       )       ).to(lowercase_       )
     a__  =floats_tensor((1, 3, 32, 32),    rng=random.Random(lowercase_       )       ).to(lowercase_       )

     a__  ={
         '''prompt''': '''A painting of a squirrel eating a burger''',
         '''image''': image,
         '''original_image''': original_image,
         '''mask_image''': mask_image,
         '''generator''': generator,
         '''num_inference_steps''': 2,
         '''output_type''': '''numpy''',
     }

     return inputs



   @unittest.skipIf(
       torch_device != '''cuda''' or not is_xformers_available(),    reason='''XFormers attention is only available with CUDA and `xformers` installed''',    )
   def  _UpperCAmelCase (				self       )							->    List[str]:






     """simple docstring"""






     self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3       )



   def  _UpperCAmelCase (				self       )							->    int:






     """simple docstring"""






     self._test_save_load_optional_components()



   @unittest.skipIf(torch_device != '''cuda''',    reason='''float16 requires CUDA'''       )
   def  _UpperCAmelCase (				self       )							->    List[Any]:






     """simple docstring"""






     super().test_save_load_floataa(expected_max_diff=1E-1       )



   def  _UpperCAmelCase (				self       )							->    int:






     """simple docstring"""






     self._test_attention_slicing_forward_pass(expected_max_diff=1E-2       )



   def  _UpperCAmelCase (				self       )							->    Optional[Any]:






     """simple docstring"""






     self._test_save_load_local()



   def  _UpperCAmelCase (				self       )							->    str:






     """simple docstring"""






     self._test_inference_batch_single_identical(
         expected_max_diff=1E-2,    )
