"""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    a_   (  unittest.TestCase      ):




					@property
					def     _SCREAMING_SNAKE_CASE    (						self    :  Any  ):
							return (
							    "CUDAExecutionProvider",
							    {
							        "gpu_mem_limit": "15000000000",  # 15GB
							        "arena_extend_strategy": "kSameAsRequested",
							    },
							)




					@property
					def     _SCREAMING_SNAKE_CASE    (						self    :  Union[str, Any]  ):
							lowerCAmelCase__   = ort.SessionOptions()
							lowerCAmelCase__   = False
							return options




					def     _SCREAMING_SNAKE_CASE    (						self    :  Dict  ):
							lowerCAmelCase__   = load_image(
							    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
							    """/in_paint/overture-creations-5sI6fQgYIuo.png"""  )
							lowerCAmelCase__   = load_image(
							    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
							    """/in_paint/overture-creations-5sI6fQgYIuo_mask.png"""  )
							lowerCAmelCase__   = 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
							lowerCAmelCase__   = 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__  )

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

							lowerCAmelCase__   = np.random.RandomState(0  )
							lowerCAmelCase__   = 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"""	,    )

							lowerCAmelCase__   = output.images[0]

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





"""simple docstring"""




from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap







def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		return getitem, k







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		return setitem, k, v







def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		return delitem, k







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  ):





		"""simple docstring"""




		try:
				return fun(lowerCamelCase__      ,	*lowerCamelCase__  ), None
		except Exception as e:
				return None, e


__lowerCAmelCase     :				Optional[Any]    				=    (
    _set("key_a", "val_a"),
    _set("key_b", "val_b"),
)

__lowerCAmelCase     :				Optional[int]    				=    [
    _set("key_a", "val_a"),
    _set("key_a", "val_b"),
]

__lowerCAmelCase     :				List[Any]    				=    [
    _set("key_a", "val_a"),
    _set("key_b", "val_b"),
    _del("key_a"),
    _del("key_b"),
    _set("key_a", "val_a"),
    _del("key_a"),
]

__lowerCAmelCase     :				int    				=    [
    _get("key_a"),
    _del("key_a"),
    _set("key_a", "val_a"),
    _del("key_a"),
    _del("key_a"),
    _get("key_a"),
]

__lowerCAmelCase     :				Optional[Any]    				=    [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

__lowerCAmelCase     :				Any    				=    [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("key_a", "val_b"),
]







@pytest.mark.parametrize(
    """operations"""      ,	(
        pytest.param(_add_items      ,	id="""add items"""  ),
        pytest.param(_overwrite_items      ,	id="""overwrite items"""  ),
        pytest.param(_delete_items      ,	id="""delete items"""  ),
        pytest.param(_access_absent_items      ,	id="""access absent items"""  ),
        pytest.param(_add_with_resize_up      ,	id="""add with resize up"""  ),
        pytest.param(_add_with_resize_down      ,	id="""add with resize down"""  ),
    )      ,	)
def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		lowerCAmelCase__   = HashMap(initial_block_size=4  )
		lowerCAmelCase__   = {}
		for _, (fun, *args) in enumerate(lowerCamelCase__  ):
				lowerCAmelCase__ ,       lowerCAmelCase__   = _run_operation(lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  )
				lowerCAmelCase__ ,       lowerCAmelCase__   = _run_operation(lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  )
				assert my_res == py_res
				assert str(lowerCamelCase__  ) == str(lowerCamelCase__  )
				assert set(lowerCamelCase__  ) == set(lowerCamelCase__  )
				assert len(lowerCamelCase__  ) == len(lowerCamelCase__  )
				assert set(my.items()  ) == set(py.items()  )







def 				_UpperCAmelCase		(							):





		"""simple docstring"""




		def is_public(lowerCamelCase__  ) -> bool:
				return not name.startswith("""_"""  )

		lowerCAmelCase__   = {name for name in dir({}  ) if is_public(lowerCamelCase__  )}
		lowerCAmelCase__   = {name for name in dir(HashMap()  ) if is_public(lowerCamelCase__  )}

		assert dict_public_names > hash_public_names




