





'''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 				UpperCAmelCase__   (self      :	Union[str, Any]				)					-> Optional[Any]:
						return (
						    "CUDAExecutionProvider",
						    {
						        "gpu_mem_limit": "15000000000",  # 15GB
						        "arena_extend_strategy": "kSameAsRequested",
						    },
						)




		@property
		def 				UpperCAmelCase__   (self      :	str				)					-> List[Any]:
						lowercase         = ort.SessionOptions()
						lowercase         = False
						return options





		def 				UpperCAmelCase__   (self      :	str				)					-> List[Any]:
						lowercase         = load_image(
						    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
						    "/in_paint/overture-creations-5sI6fQgYIuo.png"				)
						lowercase         = load_image(
						    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
						    "/in_paint/overture-creations-5sI6fQgYIuo_mask.png"				)
						lowercase         = 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         = 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         = "A red cat sitting on a park bench"

						lowercase         = np.random.RandomState(0				)
						lowercase         = pipe(
						    prompt=A__							,			image=A__							,			mask_image=A__							,			strength=0.7_5							,			guidance_scale=7.5							,			num_inference_steps=1_5							,			generator=A__							,			output_type="np"							,			)

						lowercase         = output.images[0]

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











'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCamelCase : List[str]											=			logging.get_logger(__name__)

__lowerCamelCase : str											=			{
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}

class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	List[str] 			=		'''data2vec-text'''




		def __init__(self      :	List[str]							,			A__      :	str=3_0_5_2_2							,			A__      :	Tuple=7_6_8							,			A__      :	Any=1_2							,			A__      :	Optional[int]=1_2							,			A__      :	str=3_0_7_2							,			A__      :	List[str]="gelu"							,			A__      :	List[Any]=0.1							,			A__      :	Optional[int]=0.1							,			A__      :	Union[str, Any]=5_1_2							,			A__      :	Any=2							,			A__      :	str=0.0_2							,			A__      :	int=1e-12							,			A__      :	Union[str, Any]=1							,			A__      :	Optional[int]=0							,			A__      :	Union[str, Any]=2							,			A__      :	Optional[int]="absolute"							,			A__      :	Tuple=True							,			A__      :	int=None							,			**A__      :	Any							,			)					-> Any:
						super().__init__(pad_token_id=A__							,			bos_token_id=A__							,			eos_token_id=A__							,			**A__				)

						lowercase         = vocab_size
						lowercase         = hidden_size
						lowercase         = num_hidden_layers
						lowercase         = num_attention_heads
						lowercase         = hidden_act
						lowercase         = intermediate_size
						lowercase         = hidden_dropout_prob
						lowercase         = attention_probs_dropout_prob
						lowercase         = max_position_embeddings
						lowercase         = type_vocab_size
						lowercase         = initializer_range
						lowercase         = layer_norm_eps
						lowercase         = position_embedding_type
						lowercase         = use_cache
						lowercase         = classifier_dropout




class       UpperCAmelCase (						_lowercase  ):




		@property
		def 				UpperCAmelCase__   (self      :	List[str]				)					-> Mapping[str, Mapping[int, str]]:
						if self.task == "multiple-choice":
										lowercase         = {0: "batch", 1: "choice", 2: "sequence"}
						else:
										lowercase         = {0: "batch", 1: "sequence"}
						return OrderedDict(
						    [
						        ("input_ids", dynamic_axis),
						        ("attention_mask", dynamic_axis),
						    ]				)




