




"""simple docstring"""







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 							snake_case_ (				lowerCamelCase_  ,   lowerCamelCase_  ,   unittest.TestCase ):







   """simple docstring"""




   A_										=					IFImgaImgPipeline
   A_										=					TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {'''width''', '''height'''}
   A_										=					TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
   A_										=					PipelineTesterMixin.required_optional_params - {'''latents'''}







   def      UpperCAmelCase__ (		self)							->      Optional[Any]:
       return self._get_dummy_components()







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_					,				lowerCamelCase_=0)							->      Tuple:
       if str(lowerCamelCase_).startswith('''mps'''):
           UpperCamelCase										=  torch.manual_seed(lowerCamelCase_)
       else:
           UpperCamelCase										=  torch.Generator(device=lowerCamelCase_).manual_seed(lowerCamelCase_)

       UpperCamelCase										=  floats_tensor((1, 3, 3_2, 3_2)					,				rng=random.Random(lowerCamelCase_)).to(lowerCamelCase_)

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

       return inputs







   def      UpperCAmelCase__ (		self)							->      List[Any]:
       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      UpperCAmelCase__ (		self)							->      List[Any]:
       self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3)







   @unittest.skipIf(torch_device != '''cuda'''					,				reason='''float16 requires CUDA''')
   def      UpperCAmelCase__ (		self)							->      Dict:
       # Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
       super().test_save_load_floataa(expected_max_diff=1e-1)







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







   def      UpperCAmelCase__ (		self)							->      Tuple:
       self._test_attention_slicing_forward_pass(expected_max_diff=1e-2)







   def      UpperCAmelCase__ (		self)							->      Union[str, Any]:
       self._test_save_load_local()







   def      UpperCAmelCase__ (		self)							->      Any:
       self._test_inference_batch_single_identical(
           expected_max_diff=1e-2					,				)





"""simple docstring"""







class 							snake_case_ :







   """simple docstring"""




   def __init__(		self					,				lowerCamelCase_=None)							->      Tuple:
       UpperCamelCase										=  data
       UpperCamelCase										=  None







   def __repr__(		self)							->      Union[str, Any]:
       UpperCamelCase										=  ''''''
       UpperCamelCase										=  self
       while temp:
           string_rep += F'<{temp.data}> ---> '
           UpperCamelCase										=  temp.next
       string_rep += "<END>"
       return string_rep





def     __snake_case   (							_lowercase						):


    """simple docstring"""







    if not elements_list:
        raise Exception('''The Elements List is empty'''						)

    # Set first element as Head
    UpperCamelCase										=  Node(elements_list[0]						)
    UpperCamelCase										=  head
    # Loop through elements from position 1
    for data in elements_list[1:]:
        UpperCamelCase										=  Node(_lowercase						)
        UpperCamelCase										=  current.next
    return head


SCREAMING_SNAKE_CASE_      =					[1, 3, 5, 32, 44, 12, 43]
print(f'List: {list_data}')
print('Creating Linked List from List.')
SCREAMING_SNAKE_CASE_      =					make_linked_list(list_data)
print('Linked List:')


print(linked_list)