

import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
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 				UpperCAmelCase_		(			UpperCAmelCase__				,       UpperCAmelCase__				,       unittest.TestCase   ):
							"""simple docstring"""







							UpperCAmelCase__       :						Union[str, Any]	    =    IFInpaintingSuperResolutionPipeline
							UpperCAmelCase__       :						Optional[Any]	    =    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
							UpperCAmelCase__       :						int	    =    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"original_image"}   )
							UpperCAmelCase__       :						List[Any]	    =    PipelineTesterMixin.required_optional_params - {"""latents"""}


							def 				__lowercase				(			self       )    ->    Dict:
												return self._get_superresolution_dummy_components()


							def 				__lowercase				(			self       ,							_a       ,							_a=0       )    ->    Union[str, Any]:

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

												_a	:    Any         =		floats_tensor((1, 3, 1_6, 1_6)       ,							rng=random.Random(snake_case_       )       ).to(snake_case_       )
												_a	:    Optional[Any]         =		floats_tensor((1, 3, 3_2, 3_2)       ,							rng=random.Random(snake_case_       )       ).to(snake_case_       )
												_a	:    Tuple         =		floats_tensor((1, 3, 3_2, 3_2)       ,							rng=random.Random(snake_case_       )       ).to(snake_case_       )

												_a	:    List[Any]         =		{
												    'prompt': 'A painting of a squirrel eating a burger',
												    'image': image,
												    'original_image': original_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 				__lowercase				(			self       )    ->    Optional[int]:
												self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3       )


							def 				__lowercase				(			self       )    ->    Tuple:
												self._test_save_load_optional_components()


							@unittest.skipIf(torch_device != '''cuda'''       ,							reason='''float16 requires CUDA'''       )
							def 				__lowercase				(			self       )    ->    List[str]:
												super().test_save_load_floataa(expected_max_diff=1e-1       )


							def 				__lowercase				(			self       )    ->    Union[str, Any]:
												self._test_attention_slicing_forward_pass(expected_max_diff=1e-2       )


							def 				__lowercase				(			self       )    ->    List[Any]:
												self._test_save_load_local()




							def 				__lowercase				(			self       )    ->    List[Any]:
												self._test_inference_batch_single_identical(
												    expected_max_diff=1e-2       ,							)










"""simple docstring"""




from copy import deepcopy

class  _UpperCAmelCase  :



      '''simple docstring'''

      def __init__(     self					,      snake_case_ = None					,      snake_case_ = None  ):

        """simple docstring"""

        if arr is None and size is not None:
          A_  :       Union[str, Any]										=  size
          A_  :       List[str]										=  [0] * size
        elif arr is not None:
          self.init(snake_case_  )
        else:
          raise ValueError('Either arr or size must be specified'  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        A_  :       Union[str, Any]										=  len(snake_case_  )
        A_  :       Optional[int]										=  deepcopy(snake_case_  )
        for i in range(1					,      self.size  ):
          A_  :       Optional[Any]										=  self.next_(snake_case_  )
          if j < self.size:
            self.tree[j] += self.tree[i]

      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        A_  :       int										=  self.tree[:]
        for i in range(self.size - 1					,      0					,      -1  ):
          A_  :       Optional[int]										=  self.next_(snake_case_  )
          if j < self.size:
            arr[j] -= arr[i]
        return arr

      @staticmethod
      def 					lowerCamelCase_			(     snake_case_  ):

        """simple docstring"""

        return index + (index & (-index))

      @staticmethod
      def 					lowerCamelCase_			(     snake_case_  ):

        """simple docstring"""

        return index - (index & (-index))

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        if index == 0:
          self.tree[0] += value
          return
        while index < self.size:
          self.tree[index] += value
          A_  :       List[str]										=  self.next_(snake_case_  )

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        self.add(snake_case_					,      value - self.get(snake_case_  )  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        if right == 0:
          return 0
        A_  :       Any										=  self.tree[0]
        right -= 1  # make right inclusive
        while right > 0:
          result += self.tree[right]
          A_  :       Tuple										=  self.prev(snake_case_  )
        return result

      def 					lowerCamelCase_			(     self					,      snake_case_					,      snake_case_  ):

        """simple docstring"""

        return self.prefix(snake_case_  ) - self.prefix(snake_case_  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        return self.query(snake_case_					,      index + 1  )

      def 					lowerCamelCase_			(     self					,      snake_case_  ):

        """simple docstring"""

        value -= self.tree[0]
        if value < 0:
          return -1

        A_  :       List[Any]										=  1  # Largest power of 2 <= size
        while j * 2 < self.size:
          j *= 2

        A_  :       Tuple										=  0

        while j > 0:
          if i + j < self.size and self.tree[i + j] <= value:
            value -= self.tree[i + j]
            i += j
          j //= 2
        return i


if __name__ == "__main__":
   import doctest

   doctest.testmod()