





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case  :   str						   =  logging.get_logger(__name__)

_snake_case  :   List[Any]						   =  {
    'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}



class     _UpperCAmelCase   (   _UpperCamelCase   ):

  """simple docstring"""


  a_      =			"""roc_bert"""






  def __init__(    self			:		Union[str, Any] ,  lowerCAmelCase_			:		Optional[int]=3_0_5_2_2 ,  lowerCAmelCase_			:		Any=7_6_8 ,  lowerCAmelCase_			:		int=1_2 ,  lowerCAmelCase_			:		Optional[int]=1_2 ,  lowerCAmelCase_			:		int=3_0_7_2 ,  lowerCAmelCase_			:		List[Any]="gelu" ,  lowerCAmelCase_			:		str=0.1 ,  lowerCAmelCase_			:		List[str]=0.1 ,  lowerCAmelCase_			:		List[str]=5_1_2 ,  lowerCAmelCase_			:		Any=2 ,  lowerCAmelCase_			:		List[Any]=0.02 ,  lowerCAmelCase_			:		List[Any]=1e-12 ,  lowerCAmelCase_			:		Optional[Any]=True ,  lowerCAmelCase_			:		int=0 ,  lowerCAmelCase_			:		str="absolute" ,  lowerCAmelCase_			:		Optional[Any]=None ,  lowerCAmelCase_			:		Optional[int]=True ,  lowerCAmelCase_			:		Optional[int]=True ,  lowerCAmelCase_			:		Any=7_6_8 ,  lowerCAmelCase_			:		Dict=9_1_0 ,  lowerCAmelCase_			:		List[str]=5_1_2 ,  lowerCAmelCase_			:		List[str]=2_4_8_5_8 ,  lowerCAmelCase_			:		Optional[int]=True ,  **lowerCAmelCase_			:		Any ,  )							->						Any:
     __lowerCAmelCase							     =     vocab_size
     __lowerCAmelCase							     =     max_position_embeddings
     __lowerCAmelCase							     =     hidden_size
     __lowerCAmelCase							     =     num_hidden_layers
     __lowerCAmelCase							     =     num_attention_heads
     __lowerCAmelCase							     =     intermediate_size
     __lowerCAmelCase							     =     hidden_act
     __lowerCAmelCase							     =     hidden_dropout_prob
     __lowerCAmelCase							     =     attention_probs_dropout_prob
     __lowerCAmelCase							     =     initializer_range
     __lowerCAmelCase							     =     type_vocab_size
     __lowerCAmelCase							     =     layer_norm_eps
     __lowerCAmelCase							     =     use_cache
     __lowerCAmelCase							     =     enable_pronunciation
     __lowerCAmelCase							     =     enable_shape
     __lowerCAmelCase							     =     pronunciation_embed_dim
     __lowerCAmelCase							     =     pronunciation_vocab_size
     __lowerCAmelCase							     =     shape_embed_dim
     __lowerCAmelCase							     =     shape_vocab_size
     __lowerCAmelCase							     =     concat_input
     __lowerCAmelCase							     =     position_embedding_type
     __lowerCAmelCase							     =     classifier_dropout
     super().__init__(pad_token_id=lowerCAmelCase_ ,  **lowerCAmelCase_					)








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   ):

  """simple docstring"""


  @property
  def     lowercase		(    self			:		Union[str, Any]					)							->						Tuple:
     return (
         "CUDAExecutionProvider",
         {
             "gpu_mem_limit": "15000000000",  # 15GB
             "arena_extend_strategy": "kSameAsRequested",
         },
     )






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






  def     lowercase		(    self			:		Tuple					)							->						List[Any]:
     __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=lowerCAmelCase_ ,  feature_extractor=lowerCAmelCase_ ,  provider=self.gpu_provider ,  sess_options=self.gpu_options ,  )
     pipe.set_progress_bar_config(disable=lowerCAmelCase_					)

     __lowerCAmelCase							     =     'A red cat sitting on a park bench'

     __lowerCAmelCase							     =     np.random.RandomState(0					)
     __lowerCAmelCase							     =     pipe(
         prompt=lowerCAmelCase_ ,  image=lowerCAmelCase_ ,  mask_image=lowerCAmelCase_ ,  strength=0.75 ,  guidance_scale=7.5 ,  num_inference_steps=1_5 ,  generator=lowerCAmelCase_ ,  output_type='np' ,  )

     __lowerCAmelCase							     =     output.images[0]

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

