
"""simple docstring"""




from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class 						a__		:
   def __init__(     self      ,       _a							):
          lowercase       :							Any									=				data
          lowercase       :							Node | None									=				None


class 						a__		:
   def __init__(     self							):
          lowercase       :							Any									=				None
          lowercase       :							Tuple									=				None
   def __iter__(     self							):
          lowercase       :							Union[str, Any]									=				self.head
          while self.head:
                 yield node.data
                 lowercase       :							Optional[Any]									=				node.next
                 if node == self.head:
                        break
   def __len__(     self							):
          return sum(1 for _ in self							)
   def __repr__(     self							):
          return "->".join(str(_a							) for item in iter(self							)							)
   def      __magic_name__     (     self      ,       _a							):
          self.insert_nth(len(self							)      ,       _a							)
   def      __magic_name__     (     self      ,       _a							):
          self.insert_nth(0      ,       _a							)
   def      __magic_name__     (     self      ,       _a      ,       _a							):
          if index < 0 or index > len(self							):
                 raise IndexError("list index out of range."							)
          lowercase       :							Any									=				Node(_a							)
          if self.head is None:
                 lowercase       :							str									=				new_node  # first node points itself
                 lowercase       :							Union[str, Any]									=				new_node
          elif index == 0:  # insert at head
                 lowercase       :							Optional[int]									=				self.head
                 lowercase       :							str									=				new_node
          else:
                 lowercase       :							List[str]									=				self.head
                 for _ in range(index - 1							):
                        lowercase       :							Tuple									=				temp.next
                 lowercase       :							Optional[int]									=				temp.next
                 lowercase       :							Dict									=				new_node
                 if index == len(self							) - 1:  # insert at tail
                        lowercase       :							Union[str, Any]									=				new_node
   def      __magic_name__     (     self							):
          return self.delete_nth(0							)
   def      __magic_name__     (     self							):
          return self.delete_nth(len(self							) - 1							)
   def      __magic_name__     (     self      ,       _a = 0							):
          if not 0 <= index < len(self							):
                 raise IndexError("list index out of range."							)
          lowercase       :							int									=				self.head
          if self.head == self.tail:  # just one node
                 lowercase       :							List[str]									=				None
          elif index == 0:  # delete head node
                 lowercase       :							List[Any]									=				self.tail.next.next
                 lowercase       :							Dict									=				self.head.next
          else:
                 lowercase       :							Dict									=				self.head
                 for _ in range(index - 1							):
                        lowercase       :							Any									=				temp.next
                 lowercase       :							List[str]									=				temp.next
                 lowercase       :							Any									=				temp.next.next
                 if index == len(self							) - 1:  # delete at tail
                        lowercase       :							List[str]									=				temp
          return delete_node.data

   def      __magic_name__     (     self							):
          return len(self							) == 0


def     __magic_name__      ( )					->							None:
       lowercase       :							int									=				CircularLinkedList()
       assert len(__snake_case    ) == 0
       assert circular_linked_list.is_empty() is True
       assert str(__snake_case    ) == ""

       try:
              circular_linked_list.delete_front()
              raise AssertionError  # This should not happen
       except IndexError:
              assert True  # This should happen

       try:
              circular_linked_list.delete_tail()
              raise AssertionError  # This should not happen
       except IndexError:
              assert True  # This should happen

       try:
              circular_linked_list.delete_nth(-1    )
              raise AssertionError
       except IndexError:
              assert True

       try:
              circular_linked_list.delete_nth(0    )
              raise AssertionError
       except IndexError:
              assert True

       assert circular_linked_list.is_empty() is True
       for i in range(5    ):
              assert len(__snake_case    ) == i
              circular_linked_list.insert_nth(__snake_case	,					i + 1    )
       assert str(__snake_case    ) == "->".join(str(__snake_case    ) for i in range(1	,					6    )    )

       circular_linked_list.insert_tail(6    )
       assert str(__snake_case    ) == "->".join(str(__snake_case    ) for i in range(1	,					7    )    )
       circular_linked_list.insert_head(0    )
       assert str(__snake_case    ) == "->".join(str(__snake_case    ) for i in range(0	,					7    )    )

       assert circular_linked_list.delete_front() == 0
       assert circular_linked_list.delete_tail() == 6
       assert str(__snake_case    ) == "->".join(str(__snake_case    ) for i in range(1	,					6    )    )
       assert circular_linked_list.delete_nth(2    ) == 3

       circular_linked_list.insert_nth(2	,					3    )
       assert str(__snake_case    ) == "->".join(str(__snake_case    ) for i in range(1	,					6    )    )

       assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
   import doctest

   doctest.testmod()




"""simple docstring"""




import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class 						a__		( unittest.TestCase		):
   @property
   def      __magic_name__     (     self							):
          torch.manual_seed(0							)
          lowercase       :							str									=				UNetaDModel(
              block_out_channels=(32, 64)      ,       layers_per_block=2      ,       sample_size=32      ,       in_channels=3      ,       out_channels=3      ,       down_block_types=("DownBlock2D", "AttnDownBlock2D")      ,       up_block_types=("AttnUpBlock2D", "UpBlock2D")      ,       )
          return model

   def      __magic_name__     (     self							):
          lowercase       :							List[str]									=				self.dummy_uncond_unet
          lowercase       :							Dict									=				KarrasVeScheduler()

          lowercase       :							Any									=				KarrasVePipeline(unet=_a      ,       scheduler=_a							)
          pipe.to(_a							)
          pipe.set_progress_bar_config(disable=_a							)

          lowercase       :							Tuple									=				torch.manual_seed(0							)
          lowercase       :							Tuple									=				pipe(num_inference_steps=2      ,       generator=_a      ,       output_type="numpy"							).images

          lowercase       :							int									=				torch.manual_seed(0							)
          lowercase       :							Tuple									=				pipe(num_inference_steps=2      ,       generator=_a      ,       output_type="numpy"      ,       return_dict=_a							)[0]

          lowercase       :							Any									=				image[0, -3:, -3:, -1]
          lowercase       :							Dict									=				image_from_tuple[0, -3:, -3:, -1]

          assert image.shape == (1, 32, 32, 3)
          lowercase       :							Tuple									=				np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]							)

          assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-2
          assert np.abs(image_from_tuple_slice.flatten() - expected_slice							).max() < 1E-2


@slow
@require_torch
class 						a__		( unittest.TestCase		):
   def      __magic_name__     (     self							):
          lowercase       :							Tuple									=				"google/ncsnpp-celebahq-256"
          lowercase       :							str									=				UNetaDModel.from_pretrained(_a							)
          lowercase       :							Optional[Any]									=				KarrasVeScheduler()

          lowercase       :							Union[str, Any]									=				KarrasVePipeline(unet=_a      ,       scheduler=_a							)
          pipe.to(_a							)
          pipe.set_progress_bar_config(disable=_a							)

          lowercase       :							Tuple									=				torch.manual_seed(0							)
          lowercase       :							Dict									=				pipe(num_inference_steps=20      ,       generator=_a      ,       output_type="numpy"							).images

          lowercase       :							Optional[Any]									=				image[0, -3:, -3:, -1]
          assert image.shape == (1, 256, 256, 3)
          lowercase       :							Optional[Any]									=				np.array([0.5_7_8, 0.5_8_1_1, 0.5_9_2_4, 0.5_8_0_9, 0.5_8_7, 0.5_8_8_6, 0.5_8_6_1, 0.5_8_0_2, 0.5_8_6]							)

          assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-2


