

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 					lowercase							(			lowercase_      ,    lowercase_      ,    unittest.TestCase     ):
				__SCREAMING_SNAKE_CASE   :					Optional[int]			     =     VQModel
				__SCREAMING_SNAKE_CASE   :					Any			     =     '''sample'''




				@property
				def        a				(   self ,  snake_case=(32, 32)			):
											snake_case_     							=       4
											snake_case_     							=       3

											snake_case_     							=       floats_tensor((batch_size, num_channels) + sizes			).to(snake_case			)

											return {"sample": image}




				@property
				def        a				(   self			):
											return (3, 32, 32)




				@property
				def        a				(   self			):
											return (3, 32, 32)




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




				def        a				(   self			):
											pass




				def        a				(   self			):
											pass




				def        a				(   self			):
											snake_case_							,       snake_case_     							=       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			)
											snake_case_     							=       model(**self.dummy_input			)

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




				def        a				(   self			):
											snake_case_     							=       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			)

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

											snake_case_     							=       output[0, -1, -3:, -3:].flatten().cpu()
											# fmt: off
											snake_case_     							=       torch.tensor([-0.01_53, -0.40_44, -0.18_80, -0.51_61, -0.24_18, -0.40_72, -0.16_12, -0.06_33, -0.01_43]			)
											# fmt: on
											self.assertTrue(torch.allclose(snake_case ,  snake_case ,  atol=1e-3			)			)







from collections.abc import Callable







class 					lowercase							:




				def __init__(   self ,  snake_case = None			):
											# Stores actual heap items.
											snake_case_     							=       []
											# Stores indexes of each item for supporting updates and deletion.
											snake_case_     							=       {}
											# Stores current size of heap.
											snake_case_     							=       0
											# Stores function used to evaluate the score of an item on which basis ordering
											# will be done.
											snake_case_     							=       key or (lambda snake_case			: x)




				def        a				(   self ,  snake_case			):
											return int((i - 1) / 2			) if i > 0 else None




				def        a				(   self ,  snake_case			):
											snake_case_     							=       int(2 * i + 1			)
											return left if 0 < left < self.size else None




				def        a				(   self ,  snake_case			):
											snake_case_     							=       int(2 * i + 2			)
											return right if 0 < right < self.size else None




				def        a				(   self ,  snake_case ,  snake_case			):
											snake_case_							,       snake_case_     							=       (
											    self.pos_map[self.arr[j][0]],
											    self.pos_map[self.arr[i][0]],
											)
											# Then swap the items in the list.
											snake_case_							,       snake_case_     							=       self.arr[j], self.arr[i]




				def        a				(   self ,  snake_case ,  snake_case			):
											return self.arr[i][1] < self.arr[j][1]




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._left(snake_case			)
											snake_case_     							=       self._right(snake_case			)
											snake_case_     							=       i

											if left is not None and not self._cmp(snake_case ,  snake_case			):
																		snake_case_     							=       left
											if right is not None and not self._cmp(snake_case ,  snake_case			):
																		snake_case_     							=       right

											return valid_parent




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._parent(snake_case			)
											while parent is not None and not self._cmp(snake_case ,  snake_case			):
																		self._swap(snake_case ,  snake_case			)
																		snake_case_							,       snake_case_     							=       parent, self._parent(snake_case			)




				def        a				(   self ,  snake_case			):
											snake_case_     							=       self._get_valid_parent(snake_case			)
											while valid_parent != index:
																		self._swap(snake_case ,  snake_case			)
																		snake_case_							,       snake_case_     							=       valid_parent, self._get_valid_parent(snake_case			)




				def        a				(   self ,  snake_case ,  snake_case			):
											if item not in self.pos_map:
																		return
											snake_case_     							=       self.pos_map[item]
											snake_case_     							=       [item, self.key(snake_case			)]
											# Make sure heap is right in both up and down direction.
											# Ideally only one of them will make any change.
											self._heapify_up(snake_case			)
											self._heapify_down(snake_case			)




				def        a				(   self ,  snake_case			):
											if item not in self.pos_map:
																		return
											snake_case_     							=       self.pos_map[item]
											del self.pos_map[item]
											snake_case_     							=       self.arr[self.size - 1]
											snake_case_     							=       index
											self.size -= 1
											# Make sure heap is right in both up and down direction. Ideally only one
											# of them will make any change- so no performance loss in calling both.
											if self.size > index:
																		self._heapify_up(snake_case			)
																		self._heapify_down(snake_case			)




				def        a				(   self ,  snake_case ,  snake_case			):
											snake_case_     							=       len(self.arr			)
											if arr_len == self.size:
																		self.arr.append([item, self.key(snake_case			)]			)
											else:
																		snake_case_     							=       [item, self.key(snake_case			)]
											snake_case_     							=       self.size
											self.size += 1
											self._heapify_up(self.size - 1			)




				def        a				(   self			):
											return self.arr[0] if self.size else None




				def        a				(   self			):
											snake_case_     							=       self.get_top()
											if top_item_tuple:
																		self.delete_item(top_item_tuple[0]			)
											return top_item_tuple





def    __lowerCamelCase      (					):







							'''simple docstring'''








if __name__ == "__main__":
					import doctest

					doctest.testmod()




