



import random
import unittest

import torch

from diffusers import IFImgaImgPipeline
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 lowerCAmelCase_       (   __lowerCamelCase ,__lowerCamelCase ,unittest.TestCase			):







	'''simple docstring'''




	A_       :     Tuple									=		IFImgaImgPipeline
	A_       :     int									=		TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {'width', 'height'}
	A_       :     Optional[int]									=		TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
	A_       :     Optional[int]									=		PipelineTesterMixin.required_optional_params - {'latents'}

	def 				_A			(	self       ):



				'''simple docstring'''


				return self._get_dummy_components()

	def 				_A			(	self   ,       lowerCamelCase   ,       lowerCamelCase=0       ):



				'''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__					=  {
				    """prompt""": """A painting of a squirrel eating a burger""",
				    """image""": image,
				    """generator""": generator,
				    """num_inference_steps""": 2,
				    """output_type""": """numpy""",
				}

				return inputs

	def 				_A			(	self       ):



				'''simple docstring'''


				self._test_save_load_optional_components()

	@unittest.skipIf(
	    torch_device != """cuda""" or not is_xformers_available()   ,       reason="""XFormers attention is only available with CUDA and `xformers` installed"""   ,       )
	def 				_A			(	self       ):



				'''simple docstring'''


				self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3       )

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



				'''simple docstring'''


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

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



				'''simple docstring'''


				super().test_floataa_inference(expected_max_diff=1e-1       )

	def 				_A			(	self       ):



				'''simple docstring'''


				self._test_attention_slicing_forward_pass(expected_max_diff=1e-2       )

	def 				_A			(	self       ):



				'''simple docstring'''


				self._test_save_load_local()







	def 				_A			(	self       ):



				'''simple docstring'''


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


'''simple docstring'''

from hashlib import mda, shaaaa

lowerCAmelCase_			:			Union[str, Any]    	=   (shaaaa, mda)





class 				lowercase    :


   def __init__( self					:						Optional[Any] ,		__lowerCAmelCase					:						int = 8)   ->       None:
         lowercase_     			=   0B0
         lowercase_     			=   size


   def __UpperCAmelCase							( self					:						Dict ,		__lowerCAmelCase					:						str)   ->       None:
         lowercase_     			=   self.hash_(__lowerCAmelCase)
         self.bitarray |= h


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						str)   ->       bool:
         lowercase_     			=   self.hash_(__lowerCAmelCase)
         return (h & self.bitarray) == h


   def __contains__( self					:						str ,		__lowerCAmelCase					:						str)   ->       bool:
         return self.exists(__lowerCAmelCase)


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						int)   ->       str:
         lowercase_     			=   bin(__lowerCAmelCase)[2:]
         return res.zfill(self.size)


   @property
   def __UpperCAmelCase							( self					:						Dict)   ->       str:
         return self.format_bin(self.bitarray)


   def __UpperCAmelCase							( self					:						Any ,		__lowerCAmelCase					:						str)   ->       int:
         lowercase_     			=   0B0
         for func in HASH_FUNCTIONS:
               lowercase_     			=   (
                   int.from_bytes(func(value.encode()).digest() ,		"little") % self.size
               )
               res |= 2**position
         return res


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						str)   ->       str:
         return self.format_bin(self.hash_(__lowerCAmelCase))


   @property
   def __UpperCAmelCase							( self					:						str)   ->       float:
         lowercase_     			=   bin(self.bitarray).count("1")
         return (n_ones / self.size) ** len(__lowerCAmelCase)






