






'''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


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




class      A     :






 """simple docstring"""





 __a      :    str			  =    200
 __a      :    Tuple			  =    {'Content-Length': '100'}
 __a      :    List[Any]			  =    {}
 def 	_UpperCAmelCase							(				self      ,  **__lowerCAmelCase			):
       return [bytes(__lowerCAmelCase      ,  """utf-8"""			)]






def 				snake_case       (  *a_				:			int     , **a_				:			Any						)							->					Optional[int]:





      """simple docstring"""

      return MockResponse()



@pytest.mark.parametrize("""urls_type"""     , [str, list, dict]						)
def 				snake_case       (  a_				:			Optional[int]     , a_				:			Any     , a_				:			Union[str, Any]						)							->					str:





      """simple docstring"""

      import requests

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

      UpperCamelCase_					: Union[str, Any]            =				URL
      if issubclass(_UpperCamelCase     , _UpperCamelCase						):
            UpperCamelCase_					: Optional[Any]            =				url
      elif issubclass(_UpperCamelCase     , _UpperCamelCase						):
            UpperCamelCase_					: Tuple            =				[url]
      elif issubclass(_UpperCamelCase     , _UpperCamelCase						):
            UpperCamelCase_					: Optional[int]            =				{"train": url}
      UpperCamelCase_					: Union[str, Any]            =				"dummy"
      UpperCamelCase_					: Tuple            =				"downloads"
      UpperCamelCase_					: Tuple            =				tmp_path
      UpperCamelCase_					: Any            =				DownloadConfig(
          cache_dir=os.path.join(_UpperCamelCase     , _UpperCamelCase						)     , use_etag=_UpperCamelCase     , )
      UpperCamelCase_					: Union[str, Any]            =				DownloadManager(dataset_name=_UpperCamelCase     , download_config=_UpperCamelCase						)
      UpperCamelCase_					: Optional[Any]            =				dl_manager.download(_UpperCamelCase						)
      UpperCamelCase_					: Dict            =				urls
      for downloaded_paths in [downloaded_paths]:
            if isinstance(_UpperCamelCase     , _UpperCamelCase						):
                  UpperCamelCase_					: List[Any]            =				[downloaded_paths]
                  UpperCamelCase_					: List[Any]            =				[urls]
            elif isinstance(_UpperCamelCase     , _UpperCamelCase						):
                  assert "train" in downloaded_paths.keys()
                  UpperCamelCase_					: Tuple            =				downloaded_paths.values()
                  UpperCamelCase_					: List[str]            =				urls.values()
            assert downloaded_paths
            for downloaded_path, input_url in zip(_UpperCamelCase     , _UpperCamelCase						):
                  assert downloaded_path == dl_manager.downloaded_paths[input_url]
                  UpperCamelCase_					: int            =				Path(_UpperCamelCase						)
                  UpperCamelCase_					: str            =				downloaded_path.parts
                  assert parts[-1] == HASH
                  assert parts[-2] == cache_subdir
                  assert downloaded_path.exists()
                  UpperCamelCase_					: Tuple            =				downloaded_path.read_text()
                  assert content == CONTENT
                  UpperCamelCase_					: Any            =				downloaded_path.with_suffix(""".json"""						)
                  assert metadata_downloaded_path.exists()
                  UpperCamelCase_					: Union[str, Any]            =				json.loads(metadata_downloaded_path.read_text()						)
                  assert metadata_content == {"url": URL, "etag": None}



@pytest.mark.parametrize("""paths_type"""     , [str, list, dict]						)
def 				snake_case       (  a_				:			List[Any]     , a_				:			List[str]     , a_				:			Dict						)							->					Dict:





      """simple docstring"""

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



def 				snake_case       (  a_				:			List[Any]     , a_				:			List[str]						)							->					Optional[int]:





      """simple docstring"""

      assert path.endswith(""".jsonl"""						)
      for num_items, line in enumerate(_UpperCamelCase     , start=1						):
            UpperCamelCase_					: Optional[int]            =				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 				snake_case       (  a_				:			Dict     , a_				:			List[Any]						)							->					List[Any]:





      """simple docstring"""

      UpperCamelCase_					: Tuple            =				request.getfixturevalue(_UpperCamelCase						)
      UpperCamelCase_					: Dict            =				DownloadManager()
      for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(_UpperCamelCase						)     , start=1						):
            _test_jsonl(_UpperCamelCase     , _UpperCamelCase						)
      assert num_jsonl == 2



@pytest.mark.parametrize("""archive_nested_jsonl"""     , ["""tar_nested_jsonl_path""", """zip_nested_jsonl_path"""]						)
def 				snake_case       (  a_				:			List[str]     , a_				:			List[Any]						)							->					List[str]:





      """simple docstring"""

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



def 				snake_case       (  a_				:			Any						)							->					List[Any]:





      """simple docstring"""

      UpperCamelCase_					: Tuple            =				DownloadManager()
      for num_file, file in enumerate(dl_manager.iter_files(_UpperCamelCase						)     , start=1						):
            assert os.path.basename(_UpperCamelCase						) == ("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 							_UpperCAmelCase    (		unittest.TestCase      ):




    @property
    def 					lowerCAmelCase__					(      self	:							Union[str, Any]      ):






       '''simple docstring'''






       return (
           "CUDAExecutionProvider",
           {
               "gpu_mem_limit": "15000000000",  # 15GB
               "arena_extend_strategy": "kSameAsRequested",
           },
       )




    @property
    def 					lowerCAmelCase__					(      self	:							List[Any]      ):






       '''simple docstring'''






       lowercase_						:     Union[str, Any]							     =  ort.SessionOptions()
       lowercase_						:     Optional[int]							     =  False
       return options





    def 					lowerCAmelCase__					(      self	:							str      ):






       '''simple docstring'''






       lowercase_						:     List[Any]							     =  load_image(
           "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
           "/in_paint/overture-creations-5sI6fQgYIuo.png"      )
       lowercase_						:     Tuple							     =  load_image(
           "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
           "/in_paint/overture-creations-5sI6fQgYIuo_mask.png"      )
       lowercase_						:     List[str]							     =  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
       lowercase_						:     List[Any]							     =  OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
           "CompVis/stable-diffusion-v1-4"	,  revision="onnx"	,  safety_checker=a	,  feature_extractor=a	,  provider=self.gpu_provider	,  sess_options=self.gpu_options	,  )
       pipe.set_progress_bar_config(disable=a      )

       lowercase_						:     List[str]							     =  "A red cat sitting on a park bench"

       lowercase_						:     int							     =  np.random.RandomState(0      )
       lowercase_						:     int							     =  pipe(
           prompt=a	,  image=a	,  mask_image=a	,  strength=0.75	,  guidance_scale=7.5	,  num_inference_steps=1_5	,  generator=a	,  output_type="np"	,  )

       lowercase_						:     Tuple							     =  output.images[0]

       assert image.shape == (5_1_2, 5_1_2, 3)
       assert np.abs(expected_image - image      ).max() < 1e-2




