


"""simple docstring"""







import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput






@dataclass
class 		_A    (    lowercase_    ):







    """simple docstring"""




    UpperCAmelCase			:				Any      =			4_2






class 		_A    (    unittest.TestCase    ):







    """simple docstring"""




    def       __snake_case				(   self							:       Tuple):
      a		:						Optional[int] 				=     CustomOutput(images=np.random.rand(1							,					3							,					4							,					4))

      # check every way of getting the attribute
      assert isinstance(outputs.images							,					np.ndarray)
      assert outputs.images.shape == (1, 3, 4, 4)
      assert isinstance(outputs["images"]							,					np.ndarray)
      assert outputs["images"].shape == (1, 3, 4, 4)
      assert isinstance(outputs[0]							,					np.ndarray)
      assert outputs[0].shape == (1, 3, 4, 4)

      # test with a non-tensor attribute
      a		:						List[str] 				=     CustomOutput(images=[PIL.Image.new("RGB"							,					(4, 4))])

      # check every way of getting the attribute
      assert isinstance(outputs.images							,					a__)
      assert isinstance(outputs.images[0]							,					PIL.Image.Image)
      assert isinstance(outputs["images"]							,					a__)
      assert isinstance(outputs["images"][0]							,					PIL.Image.Image)
      assert isinstance(outputs[0]							,					a__)
      assert isinstance(outputs[0][0]							,					PIL.Image.Image)






    def       __snake_case				(   self							:       List[str]):
      # test output reinitialization with a `dict` for compatibility with `accelerate`
      a		:						Optional[int] 				=     CustomOutput({"images": np.random.rand(1							,					3							,					4							,					4)})

      # check every way of getting the attribute
      assert isinstance(outputs.images							,					np.ndarray)
      assert outputs.images.shape == (1, 3, 4, 4)
      assert isinstance(outputs["images"]							,					np.ndarray)
      assert outputs["images"].shape == (1, 3, 4, 4)
      assert isinstance(outputs[0]							,					np.ndarray)
      assert outputs[0].shape == (1, 3, 4, 4)

      # test with a non-tensor attribute
      a		:						Tuple 				=     CustomOutput({"images": [PIL.Image.new("RGB"							,					(4, 4))]})

      # check every way of getting the attribute
      assert isinstance(outputs.images							,					a__)
      assert isinstance(outputs.images[0]							,					PIL.Image.Image)
      assert isinstance(outputs["images"]							,					a__)
      assert isinstance(outputs["images"][0]							,					PIL.Image.Image)
      assert isinstance(outputs[0]							,					a__)
      assert isinstance(outputs[0][0]							,					PIL.Image.Image)








from __future__ import annotations

from collections.abc import Iterable
from dataclasses import dataclass
from typing import Any

class 		__magic_name__				:


  """simple docstring"""





  _UpperCamelCase						 = ("_front", "_back", "_len")

  @dataclass
  class 		__magic_name__				:


    """simple docstring"""





    _UpperCamelCase						 = None
    _UpperCamelCase						 = None
    _UpperCamelCase						 = None







  class 		__magic_name__				:


    """simple docstring"""





    _UpperCamelCase						 = ("_cur",)


    def __init__(					self	,		a__		):
      _lowerCamelCase      =						cur


    def __iter__(					self		):
      return self


    def     _UpperCAmelCase  (					self		):
      if self._cur is None:
        # finished iterating
        raise StopIteration
      _lowerCamelCase      =						self._cur.val
      _lowerCamelCase      =						self._cur.next_node

      return val







  def __init__(					self	,		a__ = None		):
    _lowerCamelCase      =						None
    _lowerCamelCase      =						None
    _lowerCamelCase      =						0

    if iterable is not None:
      # append every value to the deque
      for val in iterable:
        self.append(a__		)


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						self._Node(a__	,		a__	,		a__		)
    if self.is_empty():
      # front = back
      _lowerCamelCase      =						_lowerCamelCase      =						node
      _lowerCamelCase      =						1
    else:
      # connect nodes
      _lowerCamelCase      =						node
      _lowerCamelCase      =						self._back
      _lowerCamelCase      =						node  # assign new back to the new node

      self._len += 1

      # make sure there were no errors
      assert not self.is_empty(), "Error on appending value."


  def     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						self._Node(a__	,		a__	,		a__		)
    if self.is_empty():
      # front = back
      _lowerCamelCase      =						_lowerCamelCase      =						node
      _lowerCamelCase      =						1
    else:
      # connect nodes
      _lowerCamelCase      =						self._front
      _lowerCamelCase      =						node
      _lowerCamelCase      =						node  # assign new front to the new node

      self._len += 1

      # make sure there were no errors
      assert not self.is_empty(), "Error on appending value."


  def     _UpperCAmelCase  (					self	,		a__		):
    for val in iterable:
      self.append(a__		)


  def     _UpperCAmelCase  (					self	,		a__		):
    for val in iterable:
      self.appendleft(a__		)


  def     _UpperCAmelCase  (					self		):
    assert not self.is_empty(), "Deque is empty."

    _lowerCamelCase      =						self._back
    _lowerCamelCase      =						self._back.prev_node  # set new back
    # drop the last node - python will deallocate memory automatically
    _lowerCamelCase      =						None

    self._len -= 1

    return topop.val


  def     _UpperCAmelCase  (					self		):
    assert not self.is_empty(), "Deque is empty."

    _lowerCamelCase      =						self._front
    _lowerCamelCase      =						self._front.next_node  # set new front and drop the first node
    _lowerCamelCase      =						None

    self._len -= 1

    return topop.val


  def     _UpperCAmelCase  (					self		):
    return self._front is None


  def __len__(					self		):
    return self._len


  def __eq__(					self	,		a__		):

    if not isinstance(a__	,		a__		):
      return NotImplemented

    _lowerCamelCase      =						self._front
    _lowerCamelCase      =						other._front

    # if the length of the dequeues are not the same, they are not equal
    if len(self		) != len(a__		):
      return False

    while me is not None and oth is not None:
      # compare every value
      if me.val != oth.val:
        return False
      _lowerCamelCase      =						me.next_node
      _lowerCamelCase      =						oth.next_node

    return True


  def __iter__(					self		):
    return Deque._Iterator(self._front		)


  def __repr__(					self		):
    _lowerCamelCase      =						[]
    _lowerCamelCase      =						self._front
    while aux is not None:
      # append the values in a list to display
      values_list.append(aux.val		)
      _lowerCamelCase      =						aux.next_node

    return f'''[{', '.join(repr(a__		) for val in values_list		)}]'''


if __name__ == "__main__":
  import doctest

  doctest.testmod()




