
"""simple docstring"""







import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


_SCREAMING_SNAKE_CASE	       =      """http://www.mocksite.com/file1.txt"""
_SCREAMING_SNAKE_CASE	       =      """\"text\": [\"foo\", \"foo\"]"""
_SCREAMING_SNAKE_CASE	       =      """6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"""







class 							__magic_name__     :
					_SCREAMING_SNAKE_CASE     							=   200
					_SCREAMING_SNAKE_CASE     							=   {'Content-Length': '100'}
					_SCREAMING_SNAKE_CASE     							=   {}





					def 							lowerCAmelCase      (				self   :							Union[str, Any]							,						**snake_case_   :							Tuple    ):
												return [bytes(_lowercase							,						"utf-8"    )]




def   __UpperCamelCase   (					*SCREAMING_SNAKE_CASE							,    **SCREAMING_SNAKE_CASE )  ->     List[str]:







							"""simple docstring"""


							return MockResponse()
@pytest.mark.parametrize("urls_type"							,    [str, list, dict] )
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     int:







							"""simple docstring"""


							import requests

							monkeypatch.setattr(_lowerCamelCase							,    "request"							,    _lowerCamelCase )

							__snake_case     			=       URL
							if issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       url
							elif issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       [url]
							elif issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       {"""train""": url}
							__snake_case     			=       """dummy"""
							__snake_case     			=       """downloads"""
							__snake_case     			=       tmp_path
							__snake_case     			=       DownloadConfig(
							    cache_dir=os.path.join(_lowerCamelCase							,    _lowerCamelCase )							,    use_etag=_lowerCamelCase							,    )
							__snake_case     			=       DownloadManager(dataset_name=_lowerCamelCase							,    download_config=_lowerCamelCase )
							__snake_case     			=       dl_manager.download(_lowerCamelCase )
							__snake_case     			=       urls
							for downloaded_paths in [downloaded_paths]:
														if isinstance(_lowerCamelCase							,    _lowerCamelCase ):
																					__snake_case     			=       [downloaded_paths]
																					__snake_case     			=       [urls]
														elif isinstance(_lowerCamelCase							,    _lowerCamelCase ):
																					assert "train" in downloaded_paths.keys()
																					__snake_case     			=       downloaded_paths.values()
																					__snake_case     			=       urls.values()
														assert downloaded_paths
														for downloaded_path, input_url in zip(_lowerCamelCase							,    _lowerCamelCase ):
																					assert downloaded_path == dl_manager.downloaded_paths[input_url]
																					__snake_case     			=       Path(_lowerCamelCase )
																					__snake_case     			=       downloaded_path.parts
																					assert parts[-1] == HASH
																					assert parts[-2] == cache_subdir
																					assert downloaded_path.exists()
																					__snake_case     			=       downloaded_path.read_text()
																					assert content == CONTENT
																					__snake_case     			=       downloaded_path.with_suffix(".json" )
																					assert metadata_downloaded_path.exists()
																					__snake_case     			=       json.loads(metadata_downloaded_path.read_text() )
																					assert metadata_content == {"url": URL, "etag": None}
@pytest.mark.parametrize("paths_type"							,    [str, list, dict] )
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Union[str, Any]:







							"""simple docstring"""


							__snake_case     			=       str(_lowerCamelCase )
							if issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       filename
							elif issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       [filename]
							elif issubclass(_lowerCamelCase							,    _lowerCamelCase ):
														__snake_case     			=       {"""train""": filename}
							__snake_case     			=       """dummy"""
							__snake_case     			=       xz_file.parent
							__snake_case     			=       """extracted"""
							__snake_case     			=       DownloadConfig(
							    cache_dir=_lowerCamelCase							,    use_etag=_lowerCamelCase							,    )
							__snake_case     			=       DownloadManager(dataset_name=_lowerCamelCase							,    download_config=_lowerCamelCase )
							__snake_case     			=       dl_manager.extract(_lowerCamelCase )
							__snake_case     			=       paths
							for extracted_paths in [extracted_paths]:
														if isinstance(_lowerCamelCase							,    _lowerCamelCase ):
																					__snake_case     			=       [extracted_paths]
																					__snake_case     			=       [paths]
														elif isinstance(_lowerCamelCase							,    _lowerCamelCase ):
																					assert "train" in extracted_paths.keys()
																					__snake_case     			=       extracted_paths.values()
																					__snake_case     			=       paths.values()
														assert extracted_paths
														for extracted_path, input_path in zip(_lowerCamelCase							,    _lowerCamelCase ):
																					assert extracted_path == dl_manager.extracted_paths[input_path]
																					__snake_case     			=       Path(_lowerCamelCase )
																					__snake_case     			=       extracted_path.parts
																					assert parts[-1] == hash_url_to_filename(_lowerCamelCase							,    etag=_lowerCamelCase )
																					assert parts[-2] == extracted_subdir
																					assert extracted_path.exists()
																					__snake_case     			=       extracted_path.read_text()
																					__snake_case     			=       text_file.read_text()
																					assert extracted_file_content == expected_file_content
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Optional[int]:







							"""simple docstring"""


							assert path.endswith(".jsonl" )
							for num_items, line in enumerate(_lowerCamelCase							,    start=1 ):
														__snake_case     			=       json.loads(line.decode("utf-8" ) )
														assert item.keys() == {"col_1", "col_2", "col_3"}
							assert num_items == 4
@pytest.mark.parametrize("archive_jsonl"							,    ["tar_jsonl_path", "zip_jsonl_path"] )
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     int:







							"""simple docstring"""


							__snake_case     			=       request.getfixturevalue(_lowerCamelCase )
							__snake_case     			=       DownloadManager()
							for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(_lowerCamelCase )							,    start=1 ):
														_test_jsonl(_lowerCamelCase							,    _lowerCamelCase )
							assert num_jsonl == 2
@pytest.mark.parametrize("archive_nested_jsonl"							,    ["tar_nested_jsonl_path", "zip_nested_jsonl_path"] )
def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE							,    SCREAMING_SNAKE_CASE )  ->     Dict:







							"""simple docstring"""


							__snake_case     			=       request.getfixturevalue(_lowerCamelCase )
							__snake_case     			=       DownloadManager()
							for num_tar, (path, file) in enumerate(dl_manager.iter_archive(_lowerCamelCase )							,    start=1 ):
														for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(_lowerCamelCase )							,    start=1 ):
																					_test_jsonl(_lowerCamelCase							,    _lowerCamelCase )
							assert num_tar == 1
							assert num_jsonl == 2



def   __UpperCamelCase   (					SCREAMING_SNAKE_CASE )  ->     Tuple:







							"""simple docstring"""


							__snake_case     			=       DownloadManager()
							for num_file, file in enumerate(dl_manager.iter_files(_lowerCamelCase )							,    start=1 ):
														assert os.path.basename(_lowerCamelCase ) == ("test.txt" if num_file == 1 else "train.txt")
							assert num_file == 2


"""simple docstring"""







import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
		import onnxruntime as ort







@nightly
@require_onnxruntime
@require_torch_gpu
class 							__magic_name__     (		unittest.TestCase   ):





					@property
					def 							lowerCAmelCase      (				self   :							Union[str, Any]    ):
												return (
												    "CUDAExecutionProvider",
												    {
												        "gpu_mem_limit": "15000000000",  # 15GB
												        "arena_extend_strategy": "kSameAsRequested",
												    },
												)





					@property
					def 							lowerCAmelCase      (				self   :							str    ):
												__snake_case     			=       ort.SessionOptions()
												__snake_case     			=       False
												return options





					def 							lowerCAmelCase      (				self   :							Tuple    ):
												__snake_case     			=       load_image(
												    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
												    "/in_paint/overture-creations-5sI6fQgYIuo.png"    )
												__snake_case     			=       load_image(
												    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
												    "/in_paint/overture-creations-5sI6fQgYIuo_mask.png"    )
												__snake_case     			=       load_numpy(
												    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
												    "/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy"    )

												# using the PNDM scheduler by default
												__snake_case     			=       OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
												    "CompVis/stable-diffusion-v1-4"							,						revision="onnx"							,						safety_checker=snake_case_							,						feature_extractor=snake_case_							,						provider=self.gpu_provider							,						sess_options=self.gpu_options							,						)
												pipe.set_progress_bar_config(disable=snake_case_    )

												__snake_case     			=       "A red cat sitting on a park bench"

												__snake_case     			=       np.random.RandomState(0    )
												__snake_case     			=       pipe(
												    prompt=snake_case_							,						image=snake_case_							,						mask_image=snake_case_							,						strength=0.75							,						guidance_scale=7.5							,						num_inference_steps=15							,						generator=snake_case_							,						output_type="np"							,						)

												__snake_case     			=       output.images[0]

												assert image.shape == (512, 512, 3)
												assert np.abs(expected_image - image    ).max() < 1e-2
