






import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
					import jax
					import jax.numpy as jnp
@slow
@require_flax
class      UpperCamelCase (				unittest.TestCase ):







		"""simple docstring"""



		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       Dict						,_SCREAMING_SNAKE_CASE		:       Dict		)    ->   Optional[int]:


						'''simple docstring'''
						return f'gaussian_noise_s={seed}_shape={"_".join([str(_SCREAMING_SNAKE_CASE		) for s in shape]		)}.npy'
		def       A(  self		:       Tuple		)    ->   Tuple:


						'''simple docstring'''
						# clean up the VRAM after each test
						super().tearDown()
						gc.collect()
		def       A(  self		:       str						,_SCREAMING_SNAKE_CASE		:       Dict=0						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=(4, 4, 6_4, 6_4)						,_SCREAMING_SNAKE_CASE		:       Union[str, Any]=False		)    ->   int:


						'''simple docstring'''
						A	 =      jnp.bfloataa if fpaa else jnp.floataa
						A	 =      jnp.array(load_hf_numpy(self.get_file_format(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)		)						,dtype=_SCREAMING_SNAKE_CASE		)
						return image
		def       A(  self		:       str						,_SCREAMING_SNAKE_CASE		:       int=False						,_SCREAMING_SNAKE_CASE		:       Tuple="CompVis/stable-diffusion-v1-4"		)    ->   Optional[int]:


						'''simple docstring'''
						A	 =      jnp.bfloataa if fpaa else jnp.floataa
						A	 =      'bf16' if fpaa else None

						A ,		A	 =      FlaxUNetaDConditionModel.from_pretrained(
						    _SCREAMING_SNAKE_CASE						,subfolder='unet'						,dtype=_SCREAMING_SNAKE_CASE						,revision=_SCREAMING_SNAKE_CASE		)
						return model, params
		def       A(  self		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=0						,_SCREAMING_SNAKE_CASE		:       str=(4, 7_7, 7_6_8)						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=False		)    ->   List[str]:


						'''simple docstring'''
						A	 =      jnp.bfloataa if fpaa else jnp.floataa
						A	 =      jnp.array(load_hf_numpy(self.get_file_format(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)		)						,dtype=_SCREAMING_SNAKE_CASE		)
						return hidden_states
		@parameterized.expand(
		    [
		        # fmt: off
		        [8_3, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
		        [1_7, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
		        [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
		        [3, 1_0_0_0, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
		        # fmt: on
		    ]		)
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       Tuple						,_SCREAMING_SNAKE_CASE		:       Dict						,_SCREAMING_SNAKE_CASE		:       List[str]		)    ->   Tuple:


						'''simple docstring'''
						A ,		A	 =      self.get_unet_model(model_id='CompVis/stable-diffusion-v1-4'						,fpaa=_SCREAMING_SNAKE_CASE		)
						A	 =      self.get_latents(_SCREAMING_SNAKE_CASE						,fpaa=_SCREAMING_SNAKE_CASE		)
						A	 =      self.get_encoder_hidden_states(_SCREAMING_SNAKE_CASE						,fpaa=_SCREAMING_SNAKE_CASE		)

						A	 =      model.apply(
						    {'params': params}						,_SCREAMING_SNAKE_CASE						,jnp.array(_SCREAMING_SNAKE_CASE						,dtype=jnp.intaa		)						,encoder_hidden_states=_SCREAMING_SNAKE_CASE						,).sample

						assert sample.shape == latents.shape

						A	 =      jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)						,dtype=jnp.floataa		)
						A	 =      jnp.array(_SCREAMING_SNAKE_CASE						,dtype=jnp.floataa		)

						# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
						assert jnp.allclose(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE						,atol=1E-2		)







		@parameterized.expand(
		    [
		        # fmt: off
		        [8_3, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
		        [1_7, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
		        [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
		        [3, 1_0_0_0, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
		        # fmt: on
		    ]		)
		def       A(  self		:       Any						,_SCREAMING_SNAKE_CASE		:       List[str]						,_SCREAMING_SNAKE_CASE		:       Dict						,_SCREAMING_SNAKE_CASE		:       Tuple		)    ->   Tuple:


						'''simple docstring'''
						A ,		A	 =      self.get_unet_model(model_id='stabilityai/stable-diffusion-2'						,fpaa=_SCREAMING_SNAKE_CASE		)
						A	 =      self.get_latents(_SCREAMING_SNAKE_CASE						,shape=(4, 4, 9_6, 9_6)						,fpaa=_SCREAMING_SNAKE_CASE		)
						A	 =      self.get_encoder_hidden_states(_SCREAMING_SNAKE_CASE						,shape=(4, 7_7, 1_0_2_4)						,fpaa=_SCREAMING_SNAKE_CASE		)

						A	 =      model.apply(
						    {'params': params}						,_SCREAMING_SNAKE_CASE						,jnp.array(_SCREAMING_SNAKE_CASE						,dtype=jnp.intaa		)						,encoder_hidden_states=_SCREAMING_SNAKE_CASE						,).sample

						assert sample.shape == latents.shape

						A	 =      jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())		)						,dtype=jnp.floataa		)
						A	 =      jnp.array(_SCREAMING_SNAKE_CASE						,dtype=jnp.floataa		)

						# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
						assert jnp.allclose(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE						,atol=1E-2		)













from collections.abc import Callable
class      UpperCamelCase :







		"""simple docstring"""



		def __init__(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       Callable | None = None		)    ->   None:


						'''simple docstring'''
						# Stores actual heap items.
						A	 =      []
						# Stores indexes of each item for supporting updates and deletion.
						A	 =      {}
						# Stores current size of heap.
						A	 =      0
						# Stores function used to evaluate the score of an item on which basis ordering
						# will be done.
						A	 =      key or (lambda _SCREAMING_SNAKE_CASE		: x)
		def       A(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						return int((i - 1) / 2		) if i > 0 else None
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						A	 =      int(2 * i + 1		)
						return left if 0 < left < self.size else None
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						A	 =      int(2 * i + 2		)
						return right if 0 < right < self.size else None
		def       A(  self		:       List[str]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A ,		A	 =      (
						    self.pos_map[self.arr[j][0]],
						    self.pos_map[self.arr[i][0]],
						)
						# Then swap the items in the list.
						A ,		A	 =      self.arr[j], self.arr[i]
		def       A(  self		:       List[str]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   bool:


						'''simple docstring'''
						return self.arr[i][1] < self.arr[j][1]
		def       A(  self		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int:


						'''simple docstring'''
						A	 =      self._left(_SCREAMING_SNAKE_CASE		)
						A	 =      self._right(_SCREAMING_SNAKE_CASE		)
						A	 =      i

						if left is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										A	 =      left
						if right is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										A	 =      right

						return valid_parent
		def       A(  self		:       Any						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      self._parent(_SCREAMING_SNAKE_CASE		)
						while parent is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										self._swap(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
										A ,		A	 =      parent, self._parent(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       List[Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      self._get_valid_parent(_SCREAMING_SNAKE_CASE		)
						while valid_parent != index:
										self._swap(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
										A ,		A	 =      valid_parent, self._get_valid_parent(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						if item not in self.pos_map:
										return
						A	 =      self.pos_map[item]
						A	 =      [item, self.key(_SCREAMING_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(_SCREAMING_SNAKE_CASE		)
						self._heapify_down(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						if item not in self.pos_map:
										return
						A	 =      self.pos_map[item]
						del self.pos_map[item]
						A	 =      self.arr[self.size - 1]
						A	 =      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(_SCREAMING_SNAKE_CASE		)
										self._heapify_down(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      len(self.arr		)
						if arr_len == self.size:
										self.arr.append([item, self.key(_SCREAMING_SNAKE_CASE		)]		)
						else:
										A	 =      [item, self.key(_SCREAMING_SNAKE_CASE		)]
						A	 =      self.size
						self.size += 1
						self._heapify_up(self.size - 1		)
		def       A(  self		:       str		)    ->   tuple | None:


						'''simple docstring'''
						return self.arr[0] if self.size else None







		def       A(  self		:       Any		)    ->   tuple | None:


						'''simple docstring'''
						A	 =      self.get_top()
						if top_item_tuple:
										self.delete_item(top_item_tuple[0]		)
						return top_item_tuple







def      snake_case		(							):
				pass


if __name__ == "__main__":
					import doctest

					doctest.testmod()





