


"""simple docstring"""







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       SCREAMING_SNAKE_CASE__				(		lowercase   ,    lowercase   ,    unittest.TestCase				):
       """simple docstring"""


       a  :				Dict   =VQModel
       a  :				str   ="sample"

       @property
       def        lowercase__							(						self		,     snake_case__=(32, 32)						):






         """simple docstring"""





         lowerCAmelCase     :     List[str]								=							4
         lowerCAmelCase     :     int								=							3

         lowerCAmelCase     :     Optional[Any]								=							floats_tensor((batch_size, num_channels) + sizes						).to(snake_case__						)

         return {"sample": image}

       @property
       def        lowercase__							(						self						):






         """simple docstring"""





         return (3, 32, 32)

       @property
       def        lowercase__							(						self						):






         """simple docstring"""





         return (3, 32, 32)

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[int]								=							{
             "block_out_channels": [32, 64],
             "in_channels": 3,
             "out_channels": 3,
             "down_block_types": ["DownEncoderBlock2D", "DownEncoderBlock2D"],
             "up_block_types": ["UpDecoderBlock2D", "UpDecoderBlock2D"],
             "latent_channels": 3,
         }
         lowerCAmelCase     :     List[str]								=							self.dummy_input
         return init_dict, inputs_dict

       def        lowercase__							(						self						):






         """simple docstring"""





         pass

       def        lowercase__							(						self						):






         """simple docstring"""





         pass

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase						,  lowerCAmelCase     :     Optional[int]								=							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__						)
         lowerCAmelCase     :     Optional[int]								=							model(**self.dummy_input						)

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







       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Union[str, Any]								=							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						)

         lowerCAmelCase     :     List[str]								=							torch.randn(1		,     model.config.in_channels		,     model.config.sample_size		,     model.config.sample_size						)
         lowerCAmelCase     :     Union[str, Any]								=							image.to(snake_case__						)
         with torch.no_grad():
           lowerCAmelCase     :     int								=							model(snake_case__						).sample

         lowerCAmelCase     :     Any								=							output[0, -1, -3:, -3:].flatten().cpu()
         # fmt: off
         lowerCAmelCase     :     Tuple								=							torch.tensor([-0.0153, -0.4044, -0.1880, -0.5161, -0.2418, -0.4072, -0.1612, -0.0633, -0.0143]						)
         # fmt: on
         self.assertTrue(torch.allclose(snake_case__		,     snake_case__		,     atol=1e-3						)						)









"""simple docstring"""







def 					a__			(				SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    List[Any]				,      SCREAMING_SNAKE_CASE    :    str				,      SCREAMING_SNAKE_CASE    :    List[Any]				):


  '''simple docstring'''







  if height >= 1:
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_disk(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Tuple				,      SCREAMING_SNAKE_CASE    :    Optional[int]				):


  '''simple docstring'''







  print("moving disk from"				,      SCREAMING_SNAKE_CASE				,      "to"				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				):


  '''simple docstring'''







  lowerCAmelCase     :     Optional[int]								=							int(input("Height of hanoi: "				).strip()				)
  move_tower(SCREAMING_SNAKE_CASE				,      "A"				,      "B"				,      "C"				)


if __name__ == "__main__":
     main()





