




import unittest

import torch

from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism

from .test_modeling_common import ModelTesterMixin, UNetTesterMixin


enable_full_determinism()







class __snake_case			(			a ,  a ,  unittest.TestCase		):
   UpperCAmelCase__  :    List[str]          =  VQModel
   UpperCAmelCase__  :    Optional[Any]          =  '''sample'''







   @property
   def lowerCamelCase						(      self		:						Optional[int]					,						_snake_case		:						List[str]=(32, 32)):

        """simple docstring"""


        UpperCAmelCase_          =							4
        UpperCAmelCase_          =							3

        UpperCAmelCase_          =							floats_tensor((batch_size, num_channels) + sizes).to(_snake_case)

        return {"sample": image}







   @property
   def lowerCamelCase						(      self		:						Optional[int]):

        """simple docstring"""


        return (3, 32, 32)







   @property
   def lowerCamelCase						(      self		:						Dict):

        """simple docstring"""


        return (3, 32, 32)







   def lowerCamelCase						(      self		:						Optional[Any]):

        """simple docstring"""


        UpperCAmelCase_          =							{
            '''block_out_channels''': [32, 64],
            '''in_channels''': 3,
            '''out_channels''': 3,
            '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
            '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
            '''latent_channels''': 3,
        }
        UpperCAmelCase_          =							self.dummy_input
        return init_dict, inputs_dict







   def lowerCamelCase						(      self		:						List[str]):

        """simple docstring"""


        pass







   def lowerCamelCase						(      self		:						Optional[int]):

        """simple docstring"""


        pass







   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        UpperCAmelCase_     ,       UpperCAmelCase_          =							VQModel.from_pretrained('''fusing/vqgan-dummy'''					,						output_loading_info=_snake_case)
        self.assertIsNotNone(_snake_case)
        self.assertEqual(len(loading_info['''missing_keys'''])					,						0)

        model.to(_snake_case)
        UpperCAmelCase_          =							model(**self.dummy_input)

        assert image is not None, "Make sure output is not None"







   def lowerCamelCase						(      self		:						Optional[int]):

        """simple docstring"""


        UpperCAmelCase_          =							VQModel.from_pretrained('''fusing/vqgan-dummy''')
        model.to(_snake_case).eval()

        torch.manual_seed(0)
        if torch.cuda.is_available():
             torch.cuda.manual_seed_all(0)

        UpperCAmelCase_          =							torch.randn(1					,						model.config.in_channels					,						model.config.sample_size					,						model.config.sample_size)
        UpperCAmelCase_          =							image.to(_snake_case)
        with torch.no_grad():
             UpperCAmelCase_          =							model(_snake_case).sample

        UpperCAmelCase_          =							output[0, -1, -3:, -3:].flatten().cpu()
        # fmt: off
        UpperCAmelCase_          =							torch.tensor([-0.0_1_5_3, -0.4_0_4_4, -0.1_8_8_0, -0.5_1_6_1, -0.2_4_1_8, -0.4_0_7_2, -0.1_6_1_2, -0.0_6_3_3, -0.0_1_4_3])
        # fmt: on
        self.assertTrue(torch.allclose(_snake_case					,						_snake_case					,						atol=1e-3))









# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.






def        UpperCamelCase_(							_snake_case   :  Tuple	):




			"""simple docstring"""






			__a        =[False] * len(_snake_case	)
			__a        =[-1] * len(_snake_case	)

			def dfs(_snake_case   :  Dict       ,     _snake_case   :  Any	):
						__a        =True
						__a        =c
						for u in graph[v]:
									if not visited[u]:
												dfs(_snake_case       ,     1 - c	)

			for i in range(len(_snake_case	)	):
						if not visited[i]:
									dfs(_snake_case       ,     0	)

			for i in range(len(_snake_case	)	):
						for j in graph[i]:
									if color[i] == color[j]:
												return False

			return True


# Adjacency list of graph
_lowerCAmelCase					:			int  				=			{0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}


print(check_bipartite_dfs(graph))






