code: 
  
  
  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 					__lowercase					(       a_ ,       a_ ,       unittest.TestCase     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				Tuple 					=		IFImgaImgPipeline
  		UpperCamelCase    :				Dict 					=		TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"width", "height"}
  		UpperCamelCase    :				Dict 					=		TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
  		UpperCamelCase    :				List[str] 					=		PipelineTesterMixin.required_optional_params - {"latents"}
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Optional[int]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return self._get_dummy_components()
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A		,			A=0  )     ->   int:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					if str(A  ).startswith("""mps"""  ):
  								lowerCamelCase								=     torch.manual_seed(A  )
  					else:
  								lowerCamelCase								=     torch.Generator(device=A  ).manual_seed(A  )
  
  					lowerCamelCase								=     floats_tensor((1, 3, 32, 32)		,			rng=random.Random(A  )  ).to(A  )
  
  					lowerCamelCase								=     {
  					    """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  )     ->   Tuple:
  
  
  
  
  
  
  
  					'''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  )     ->   Union[str, Any]:
  
  
  
  
  
  
  
  					'''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  )     ->   Union[str, Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					super().test_save_load_floataa(expected_max_diff=1e-1  )
  
  
  
  
  
  
  
  		@unittest.skipIf(torch_device != """cuda"""		,			reason="""float16 requires CUDA"""  )
  		def 				__A      (   self  )     ->   Optional[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					super().test_floataa_inference(expected_max_diff=1e-1  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					self._test_attention_slicing_forward_pass(expected_max_diff=1e-2  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					self._test_save_load_local()
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Optional[int]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					self._test_inference_batch_single_identical(
  					    expected_max_diff=1e-2		,			)
  
  
style_context: 
  
  
  import unittest
  
  from cer import CER
  
  
  UpperCAmelCase      :						Union[str, Any]    =		CER()
  
  
  
  
  
  
  
  class 					__lowercase					(       unittest.TestCase     ):
  
  
  
  		"""simple docstring"""
  
  		def 				__A      (   self  )     ->   Optional[int]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""White House"""]
  					lowerCamelCase								=     ["""white house"""]
  					# S = 2, D = 0, I = 0, N = 11, CER = 2 / 11
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.1818181818  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[str]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""were wolf"""]
  					lowerCamelCase								=     ["""werewolf"""]
  					# S = 0, D = 0, I = 1, N = 9, CER = 1 / 9
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.1111111  ) < 1e-6  )
  
  					lowerCamelCase								=     ["""werewolf"""]
  					lowerCamelCase								=     ["""weae     wolf"""]
  					# S = 1, D = 1, I = 0, N = 8, CER = 0.25
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.25  ) < 1e-6  )
  
  					# consecutive whitespaces case 1
  					lowerCamelCase								=     ["""were wolf"""]
  					lowerCamelCase								=     ["""were               wolf"""]
  					# S = 0, D = 0, I = 0, N = 9, CER = 0
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.0  ) < 1e-6  )
  
  					# consecutive whitespaces case 2
  					lowerCamelCase								=     ["""were   wolf"""]
  					lowerCamelCase								=     ["""were               wolf"""]
  					# S = 0, D = 0, I = 0, N = 9, CER = 0
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.0  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""werewolf"""]
  					lowerCamelCase								=     ["""weaewolf"""]
  					# S = 1, D = 0, I = 0, N = 8, CER = 0.125
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.125  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Tuple:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""werewolf"""]
  					lowerCamelCase								=     ["""wereawolf"""]
  					# S = 0, D = 1, I = 0, N = 8, CER = 0.125
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.125  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""werewolf"""]
  					lowerCamelCase								=     ["""wereolf"""]
  					# S = 0, D = 0, I = 1, N = 8, CER = 0.125
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.125  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Tuple:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""werewolf"""]
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertEqual(A		,			0.0  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[str]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""werewolf""", """I am your father"""]
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertEqual(A		,			0.0  )
  
  					lowerCamelCase								=     ["""werewolf""", """I am your father""", """doge"""]
  					lowerCamelCase								=     ["""werxwolf""", """I       am your father""", """doge"""]
  					# S = 1, D = 0, I = 0, N = 28, CER = 1 / 28
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.03571428  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""My hovercraft""", """is full of eels"""]
  					lowerCamelCase								=     ["""My hovercraft is full""", """ of eels"""]
  					# S = 0, D = 0, I = 2, N = 28, CER = 2 / 28
  					# whitespace at the front of " of eels" will be strip during preporcessing
  					# so need to insert 2 whitespaces
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A		,			concatenate_texts=A  )
  					self.assertTrue(abs(char_error_rate - 0.071428  ) < 1e-6  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Optional[int]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""我能吞下玻璃而不伤身体"""]
  					lowerCamelCase								=     [""" 能吞虾玻璃而 不霜身体啦"""]
  					# S = 3, D = 2, I = 0, N = 11, CER = 5 / 11
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.4545454545  ) < 1e-6  )
  
  					lowerCamelCase								=     ["""我能吞下玻璃""", """而不伤身体"""]
  					lowerCamelCase								=     ["""我    能 吞 下 玻 璃""", """而不伤身体"""]
  					# S = 0, D = 5, I = 0, N = 11, CER = 5 / 11
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertTrue(abs(char_error_rate - 0.454545454545  ) < 1e-6  )
  
  					lowerCamelCase								=     ["""我能吞下玻璃而不伤身体"""]
  					lowerCamelCase								=     cer.compute(predictions=A		,			references=A  )
  					self.assertFalse(A		,			0.0  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Optional[int]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     [""""""]
  					lowerCamelCase								=     ["""Hypothesis"""]
  					with self.assertRaises(A  ):
  								cer.compute(predictions=A		,			references=A  )
  
  
  if __name__ == "__main__":
  		unittest.main()
  
  