

'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case         =  logging.get_logger(__name__)

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


class        a__  (							lowerCamelCase_  ):






   """simple docstring"""




   _SCREAMING_SNAKE_CASE   :					Any     	=							'roc_bert'


   def __init__(			self      ,    _UpperCamelCase=30522      ,    _UpperCamelCase=768      ,    _UpperCamelCase=12      ,    _UpperCamelCase=12      ,    _UpperCamelCase=3072      ,    _UpperCamelCase="gelu"      ,    _UpperCamelCase=0.1      ,    _UpperCamelCase=0.1      ,    _UpperCamelCase=512      ,    _UpperCamelCase=2      ,    _UpperCamelCase=0.0_2      ,    _UpperCamelCase=1E-1_2      ,    _UpperCamelCase=True      ,    _UpperCamelCase=0      ,    _UpperCamelCase="absolute"      ,    _UpperCamelCase=None      ,    _UpperCamelCase=True      ,    _UpperCamelCase=True      ,    _UpperCamelCase=768      ,    _UpperCamelCase=910      ,    _UpperCamelCase=512      ,    _UpperCamelCase=24858      ,    _UpperCamelCase=True      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      _lowercase      :				str      					=       vocab_size
      _lowercase      :				List[str]      					=       max_position_embeddings
      _lowercase      :				List[Any]      					=       hidden_size
      _lowercase      :				Dict      					=       num_hidden_layers
      _lowercase      :				str      					=       num_attention_heads
      _lowercase      :				int      					=       intermediate_size
      _lowercase      :				Optional[Any]      					=       hidden_act
      _lowercase      :				Union[str, Any]      					=       hidden_dropout_prob
      _lowercase      :				Dict      					=       attention_probs_dropout_prob
      _lowercase      :				Dict      					=       initializer_range
      _lowercase      :				List[Any]      					=       type_vocab_size
      _lowercase      :				Tuple      					=       layer_norm_eps
      _lowercase      :				Optional[int]      					=       use_cache
      _lowercase      :				Tuple      					=       enable_pronunciation
      _lowercase      :				Optional[int]      					=       enable_shape
      _lowercase      :				int      					=       pronunciation_embed_dim
      _lowercase      :				List[str]      					=       pronunciation_vocab_size
      _lowercase      :				int      					=       shape_embed_dim
      _lowercase      :				str      					=       shape_vocab_size
      _lowercase      :				str      					=       concat_input
      _lowercase      :				Dict      					=       position_embedding_type
      _lowercase      :				Optional[Any]      					=       classifier_dropout
      super().__init__(pad_token_id=_UpperCamelCase      ,    **_UpperCamelCase  )









'''simple docstring'''
import random
import unittest

import torch

from diffusers import IFImgaImgSuperResolutionPipeline
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_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin


@skip_mps
class        a__  (							lowerCamelCase_  ,				lowerCamelCase_  ,				unittest.TestCase  ):
   _SCREAMING_SNAKE_CASE   :					List[str]     	=							IFImgaImgSuperResolutionPipeline
   _SCREAMING_SNAKE_CASE   :					int     	=							TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {'width', 'height'}
   _SCREAMING_SNAKE_CASE   :					List[str]     	=							TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS.union({'original_image'}  )
   _SCREAMING_SNAKE_CASE   :					Optional[int]     	=							PipelineTesterMixin.required_optional_params - {'latents'}


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      return self._get_superresolution_dummy_components()


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase      ,    _UpperCamelCase=0  ):





      """simple docstring"""





      if str(_UpperCamelCase  ).startswith("mps"  ):
         _lowercase      :				Tuple      					=       torch.manual_seed(_UpperCamelCase  )
      else:
         _lowercase      :				int      					=       torch.Generator(device=_UpperCamelCase  ).manual_seed(_UpperCamelCase  )

      _lowercase      :				List[Any]      					=       floats_tensor((1, 3, 32, 32)      ,    rng=random.Random(_UpperCamelCase  )  ).to(_UpperCamelCase  )
      _lowercase      :				Optional[int]      					=       floats_tensor((1, 3, 16, 16)      ,    rng=random.Random(_UpperCamelCase  )  ).to(_UpperCamelCase  )

      _lowercase      :				List[str]      					=       {
          "prompt": "A painting of a squirrel eating a burger",
          "image": image,
          "original_image": original_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  ):





      """simple docstring"""





      self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self._test_save_load_optional_components()


   @unittest.skipIf(torch_device != "cuda"      ,    reason="float16 requires CUDA"  )
   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self._test_attention_slicing_forward_pass(expected_max_diff=1E-2  )


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      self._test_save_load_local()






   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





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






