



'''simple docstring'''





import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
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_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin






@skip_mps
class __A			(  lowerCAmelCase__   ,   lowerCAmelCase__   ,   unittest.TestCase						):



 '''simple docstring'''







 __lowerCamelCase    :       Union[str, Any]          =       IFInpaintingPipeline
 __lowerCamelCase    :       Dict          =       TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'''width''', '''height'''}
 __lowerCamelCase    :       Tuple          =       TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
 __lowerCamelCase    :       Dict          =       PipelineTesterMixin.required_optional_params - {'''latents'''}



 def 					a__  (self       )    ->     List[Any]:


      """simple docstring"""



      return self._get_dummy_components()



 def 					a__  (self ,   A ,   A=0       )    ->     Optional[Any]:


      """simple docstring"""



      if str(__lowerCAmelCase       ).startswith('''mps'''       ):
           _a      =  torch.manual_seed(__lowerCAmelCase       )
      else:
           _a      =  torch.Generator(device=__lowerCAmelCase       ).manual_seed(__lowerCAmelCase       )

      _a      =  floats_tensor((1, 3, 32, 32) ,   rng=random.Random(__lowerCAmelCase       )       ).to(__lowerCAmelCase       )
      _a      =  floats_tensor((1, 3, 32, 32) ,   rng=random.Random(__lowerCAmelCase       )       ).to(__lowerCAmelCase       )

      _a      =  {
          '''prompt''': '''A painting of a squirrel eating a burger''',
          '''image''': image,
          '''mask_image''': mask_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 					a__  (self       )    ->     Tuple:


      """simple docstring"""



      self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3       )



 def 					a__  (self       )    ->     List[str]:


      """simple docstring"""



      self._test_save_load_optional_components()



 @unittest.skipIf(torch_device != '''cuda''' ,   reason='''float16 requires CUDA'''       )
 def 					a__  (self       )    ->     Union[str, Any]:


      """simple docstring"""



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



 def 					a__  (self       )    ->     int:


      """simple docstring"""



      self._test_attention_slicing_forward_pass(expected_max_diff=1E-2       )



 def 					a__  (self       )    ->     int:


      """simple docstring"""



      self._test_save_load_local()



 def 					a__  (self       )    ->     List[Any]:


      """simple docstring"""



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




'''simple docstring'''




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


__lowercase          =  logging.get_logger(__name__)

__lowercase          =  '''T5Config'''






class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     List[str]      =       '''mt5'''
			UpperCAmelCase_			:     Tuple      =       MTaConfig







class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     List[Any]      =       '''mt5'''
			UpperCAmelCase_			:     int      =       MTaConfig







class 				a__(					lowerCAmelCase__	):


			'''simple docstring'''






			UpperCAmelCase_			:     Tuple      =       '''mt5'''
			UpperCAmelCase_			:     Union[str, Any]      =       MTaConfig




