'''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 lowerCamelCase							(	unittest.TestCase					):




  '''simple docstring'''



  @property
  def  lowerCAmelCase__ (      self			:       int  )				->List[str]:
        return (
            "CUDAExecutionProvider",
            {
                "gpu_mem_limit": "15000000000",  # 15GB
                "arena_extend_strategy": "kSameAsRequested",
            },
        )






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






  def  lowerCAmelCase__ (      self			:       str  )				->int:
        UpperCAmelCase_            =  load_image(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
            '''/in_paint/overture-creations-5sI6fQgYIuo.png'''  )
        UpperCAmelCase_            =  load_image(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
            '''/in_paint/overture-creations-5sI6fQgYIuo_mask.png'''  )
        UpperCAmelCase_            =  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
        UpperCAmelCase_            =  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  )

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

        UpperCAmelCase_            =  np.random.RandomState(0  )
        UpperCAmelCase_            =  pipe(
            prompt=__A  ,							image=__A  ,							mask_image=__A  ,							strength=0.75  ,							guidance_scale=7.5  ,							num_inference_steps=15  ,							generator=__A  ,							output_type='''np'''  ,							)

        UpperCAmelCase_            =  output.images[0]

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






'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


lowercase__  :      Dict        =					logging.get_logger(__name__)

lowercase__  :      List[Any]        =					"T5Config"







class lowerCamelCase							(	lowerCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	'''mt5'''
  lowerCAmelCase__										=	MTaConfig







class lowerCamelCase							(	lowerCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	'''mt5'''
  lowerCAmelCase__										=	MTaConfig







class lowerCamelCase							(	lowerCamelCase					):




  '''simple docstring'''



  lowerCAmelCase__										=	'''mt5'''
  lowerCAmelCase__										=	MTaConfig





