

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 a(lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, ):





	'''simple docstring'''
	snake_case_      		= {
	    '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),
	}
	snake_case_		,       snake_case_      		= input_paths_and_base_extractors[compression_format]
	if input_path is None:
		snake_case_      		= 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(lowercase__	)
	assert base_extractor.is_extractable(lowercase__	)
	snake_case_      		= tmp_path / ('extracted' if is_archive else 'extracted.txt')
	base_extractor.extract(lowercase__			, lowercase__	)
	if is_archive:
		assert output_path.is_dir()
		for file_path in output_path.iterdir():
			assert file_path.name == text_file.name
			snake_case_      		= file_path.read_text(encoding='utf-8'	)
	else:
		snake_case_      		= output_path.read_text(encoding='utf-8'	)
	snake_case_      		= 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 a(lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, ):





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





@pytest.fixture
def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	import tarfile

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





@pytest.fixture
def a(lowercase__	):





	'''simple docstring'''
	import tarfile

	snake_case_      		= tmp_path / 'data_sym_link'
	directory.mkdir()
	snake_case_      		= directory / 'tar_file_with_sym_link.tar'
	os.symlink('..'			, directory / 'subdir'			, target_is_directory=lowercase__	)
	with tarfile.TarFile(lowercase__			, '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 a(lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__	):





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






def a(lowercase__	):





	'''simple docstring'''
	# We should have less false positives than zipfile.is_zipfile
	# We do that by checking only the magic number
	snake_case_      		= tmpdir / 'not_a_zip_file'
	# From: https://github.com/python/cpython/pull/5053
	snake_case_      		= (
	    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(lowercase__	)
	assert zipfile.is_zipfile(str(lowercase__	)	)  # is a false positive for `zipfile`
	assert not ZipExtractor.is_extractable(lowercase__	)  # but we're right



import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


A											=     argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argument('--dpm', action='store_true', help='Enable DPMSolver or not')
parser.add_argument('--steps', default=None, type=int, help='Num inference steps')
A											=     parser.parse_args()


A											=     'cpu'
A											=     'a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings'

A											=     'path-to-your-trained-model'
A											=     StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
		A											=     DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
A											=     pipe.to(device)

# to channels last
A											=     pipe.unet.to(memory_format=torch.channels_last)
A											=     pipe.vae.to(memory_format=torch.channels_last)
A											=     pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
		A											=     pipe.safety_checker.to(memory_format=torch.channels_last)

# optimize with ipex
A											=     torch.randn(2, 4, 64, 64)
A											=     torch.rand(1) * 999
A											=     torch.randn(2, 77, 768)
A											=     (sample, timestep, encoder_hidden_status)
try:
		A											=     ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
		A											=     ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
A											=     ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
A											=     ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
		A											=     ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
A											=     666
A											=     torch.Generator(device).manual_seed(seed)
A											=     {'generator': generator}
if args.steps is not None:
		A											=     args.steps

with torch.cpu.amp.autocast(enabled=True, dtype=torch.bfloataa):
		A											=     pipe(prompt, **generate_kwargs).images[0]

# save image
image.save('generated.png')
