
"""simple docstring"""



import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
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        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase      ,				UpperCAmelCase      ,				unittest.TestCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							int							=					IFInpaintingPipeline
				SCREAMING_SNAKE_CASE_:							Union[str, Any]							=					TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"width", "height"}
				SCREAMING_SNAKE_CASE_:							int							=					TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
				SCREAMING_SNAKE_CASE_:							Union[str, Any]							=					PipelineTesterMixin.required_optional_params - {"latents"}


				def 				__lowerCamelCase	(					self	:			Any  )		->  Tuple:







											"""simple docstring"""




											return self._get_dummy_components()


				def 				__lowerCamelCase	(					self	:			Any				,     UpperCAmelCase_	:			str				,     UpperCAmelCase_	:			Union[str, Any]=0  )		->  List[str]:







											"""simple docstring"""




											if str(UpperCAmelCase_  ).startswith('mps'  ):
																		_lowerCAmelCase  	=			torch.manual_seed(UpperCAmelCase_  )
											else:
																		_lowerCAmelCase  	=			torch.Generator(device=UpperCAmelCase_  ).manual_seed(UpperCAmelCase_  )

											_lowerCAmelCase  	=			floats_tensor((1, 3, 32, 32)				,     rng=random.Random(UpperCAmelCase_  )  ).to(UpperCAmelCase_  )
											_lowerCAmelCase  	=			floats_tensor((1, 3, 32, 32)				,     rng=random.Random(UpperCAmelCase_  )  ).to(UpperCAmelCase_  )

											_lowerCAmelCase  	=			{
											    'prompt': 'A painting of a squirrel eating a burger',
											    'image': 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 				__lowerCamelCase	(					self	:			str  )		->  int:







											"""simple docstring"""




											self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3  )


				def 				__lowerCamelCase	(					self	:			Tuple  )		->  Optional[int]:







											"""simple docstring"""




											self._test_save_load_optional_components()


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







											"""simple docstring"""




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


				def 				__lowerCamelCase	(					self	:			List[str]  )		->  List[str]:







											"""simple docstring"""




											self._test_attention_slicing_forward_pass(expected_max_diff=1E-2  )


				def 				__lowerCamelCase	(					self	:			Dict  )		->  List[Any]:







											"""simple docstring"""




											self._test_save_load_local()







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







											"""simple docstring"""




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








"""simple docstring"""



import pytest


_snake_case          =						'''__dummy_dataset1__'''

_snake_case          =						'''
import json
import os

import datasets


REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-bn-validation.jsonl"}


class __DummyDataset1__(datasets.GeneratorBasedBuilder):

    def _info(self):
        features = datasets.Features(
            {
                "tokens": datasets.Sequence(datasets.Value("string")),
                "ner_tags": datasets.Sequence(
                    datasets.features.ClassLabel(
                        names=[
                            "O",
                            "B-PER",
                            "I-PER",
                            "B-ORG",
                            "I-ORG",
                            "B-LOC",
                            "I-LOC",
                        ]
                    )
                ),
                "langs": datasets.Sequence(datasets.Value("string")),
                "spans": datasets.Sequence(datasets.Value("string")),
            }
        )
        return datasets.DatasetInfo(features=features)

    def _split_generators(self, dl_manager):
        dl_path = dl_manager.download(URLS)
        return [
            datasets.SplitGenerator(datasets.Split.TRAIN, gen_kwargs={"filepath": dl_path["train"]}),
            datasets.SplitGenerator(datasets.Split.VALIDATION, gen_kwargs={"filepath": dl_path["validation"]}),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, "r", encoding="utf-8") as f:
            for i, line in enumerate(f):
                yield i, json.loads(line)
'''






@pytest.fixture
def 	__snake_case  (    ):






							"""simple docstring"""



							return DATASET_LOADING_SCRIPT_NAME






@pytest.fixture
def 	__snake_case  (    ):






							"""simple docstring"""



							return DATASET_LOADING_SCRIPT_CODE






@pytest.fixture
def 	__snake_case  (    SCREAMING_SNAKE_CASE:					List[str]     ,  SCREAMING_SNAKE_CASE:					Optional[int]     ,  SCREAMING_SNAKE_CASE:					List[str]						):






							"""simple docstring"""



							_lowerCAmelCase  	=			dataset_loading_script_name
							_lowerCAmelCase  	=			tmp_path / 'datasets' / script_name
							script_dir.mkdir(parents=SCREAMING_SNAKE_CASE						)
							_lowerCAmelCase  	=			script_dir / f"""{script_name}.py"""
							with open(SCREAMING_SNAKE_CASE     ,  'w'						) as f:
														f.write(SCREAMING_SNAKE_CASE						)
							return str(SCREAMING_SNAKE_CASE						)






