


'''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   __lowerCAmelCase						(lowercase_  ,     lowercase_  ,     unittest.TestCase     ):





      '''simple docstring'''






      lowerCAmelCase__					:     int  					=							IFInpaintingPipeline
      lowerCAmelCase__					:     int  					=							TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
      lowerCAmelCase__					:     int  					=							TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
      lowerCAmelCase__					:     List[str]  					=							PipelineTesterMixin.required_optional_params - {"""latents"""}



      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             return self._get_dummy_components()



      def       UpperCamelCase__		(self    :    List[Any]   ,						UpperCamelCase    :    Union[str, Any]   ,						UpperCamelCase    :    Optional[Any]=0 ):

             '''simple docstring'''







             if str(UpperCamelCase ).startswith('''mps''' ):
                    lowercase__      			= torch.manual_seed(UpperCamelCase )
             else:
                    lowercase__      			= torch.Generator(device=UpperCamelCase ).manual_seed(UpperCamelCase )

             lowercase__      			= floats_tensor((1, 3, 32, 32)   ,						rng=random.Random(UpperCamelCase ) ).to(UpperCamelCase )
             lowercase__      			= floats_tensor((1, 3, 32, 32)   ,						rng=random.Random(UpperCamelCase ) ).to(UpperCamelCase )

             lowercase__      			= {
                 '''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       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







             self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3 )



      def       UpperCamelCase__		(self    :    Dict ):

             '''simple docstring'''







             self._test_save_load_optional_components()



      @unittest.skipIf(torch_device != '''cuda'''   ,						reason='''float16 requires CUDA''' )
      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







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



      def       UpperCamelCase__		(self    :    Dict ):

             '''simple docstring'''







             self._test_attention_slicing_forward_pass(expected_max_diff=1E-2 )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             self._test_save_load_local()






      def       UpperCamelCase__		(self    :    Optional[int] ):

             '''simple docstring'''







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








'''simple docstring'''

# Lint as: python3
import itertools
import os
import re


lowerCamelCase							:   Any  						=	re.compile(R'([A-Z]+)([A-Z][a-z])')
lowerCamelCase							:   str  						=	re.compile(R'([a-z\d])([A-Z])')

lowerCamelCase							:   Optional[int]  						=	re.compile(R'(?<!_)_(?!_)')
lowerCamelCase							:   List[Any]  						=	re.compile(R'(_{2,})')

lowerCamelCase							:   str  						=	R'^\w+(\.\w+)*$'

lowerCamelCase							:   Dict  						=	R'<>:/\|?*'

def _SCREAMING_SNAKE_CASE      (A       )       ->       Any:






       """simple docstring"""







       lowercase__      			= _uppercase_uppercase_re.sub(R'''\1_\2'''  , A       )
       lowercase__      			= _lowercase_uppercase_re.sub(R'''\1_\2'''  , A       )
       return name.lower()

def _SCREAMING_SNAKE_CASE      (A       )       ->       Tuple:






       """simple docstring"""







       lowercase__      			= _single_underscore_re.split(A       )
       lowercase__      			= [_multiple_underscores_re.split(A       ) for n in name]
       return "".join(n.capitalize() for n in itertools.chain.from_iterable(A       ) if n != ''''''       )

def _SCREAMING_SNAKE_CASE      (A       )       ->       Tuple:






       """simple docstring"""







       if os.path.basename(A       ) != name:
              raise ValueError(f"Should be a dataset name, not a path: {name}"       )
       return camelcase_to_snakecase(A       )

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       Optional[Any]:






       """simple docstring"""







       if os.path.basename(A       ) != name:
              raise ValueError(f"Should be a dataset name, not a path: {name}"       )
       if not re.match(_split_re  , A       ):
              raise ValueError(f"Split name should match '{_split_re}'' but got '{split}'."       )
       return f"{filename_prefix_for_name(A       )}-{split}"

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , A=None       )       ->       List[str]:






       """simple docstring"""







       lowercase__      			= filename_prefix_for_split(A  , A       )
       if filetype_suffix:
              prefix += f".{filetype_suffix}"
       lowercase__      			= os.path.join(A  , A       )
       return f"{filepath}*"

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , A=None  , A=None       )       ->       Optional[Any]:






       """simple docstring"""







       lowercase__      			= filename_prefix_for_split(A  , A       )
       lowercase__      			= os.path.join(A  , A       )

       if shard_lengths:
              lowercase__      			= len(A       )
              lowercase__      			= [f"{prefix}-{shard_id:05d}-of-{num_shards:05d}" for shard_id in range(A       )]
              if filetype_suffix:
                     lowercase__      			= [filename + f".{filetype_suffix}" for filename in filenames]
              return filenames
       else:
              lowercase__      			= prefix
              if filetype_suffix:
                     filename += f".{filetype_suffix}"
              return [filename]




