




import gc
import unittest

from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
					import jax
					import jax.numpy as jnp
					from flax.jax_utils import replicate
					from flax.training.common_utils import shard

@slow
@require_flax
class 			a					(		unittest.TestCase			):


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										super().tearDown()
										gc.collect()


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase						,							_UpperCAmelCase    :						List[str]							=      FlaxStableDiffusionPipeline.from_pretrained(
										    "stabilityai/stable-diffusion-2"  ,   revision="bf16"  ,   dtype=jnp.bfloataa  ,   )

										_UpperCAmelCase    :						int							=      "A painting of a squirrel eating a burger"
										_UpperCAmelCase    :						Optional[int]							=      jax.device_count()
										_UpperCAmelCase    :						Tuple							=      num_samples * [prompt]
										_UpperCAmelCase    :						Union[str, Any]							=      sd_pipe.prepare_inputs(__UpperCamelCase		)

										_UpperCAmelCase    :						List[Any]							=      replicate(__UpperCamelCase		)
										_UpperCAmelCase    :						Optional[Any]							=      shard(__UpperCamelCase		)

										_UpperCAmelCase    :						Dict							=      jax.random.PRNGKey(0		)
										_UpperCAmelCase    :						Tuple							=      jax.random.split(__UpperCamelCase  ,   jax.device_count()		)

										_UpperCAmelCase    :						int							=      sd_pipe(__UpperCamelCase  ,   __UpperCamelCase  ,   __UpperCamelCase  ,   num_inference_steps=25  ,   jit=__UpperCamelCase		)[0]
										assert images.shape == (jax.device_count(), 1, 768, 768, 3)

										_UpperCAmelCase    :						Any							=      images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
										_UpperCAmelCase    :						Optional[int]							=      images[0, 253:256, 253:256, -1]

										_UpperCAmelCase    :						Dict							=      jnp.asarray(jax.device_get(image_slice.flatten()		)		)
										_UpperCAmelCase    :						str							=      jnp.array([0.42_38, 0.44_14, 0.43_95, 0.44_53, 0.46_29, 0.45_90, 0.45_31, 0.4_55_08, 0.45_12]		)
										print(f'output_slice: {output_slice}'		)
										assert jnp.abs(output_slice - expected_slice		).max() < 1e-2





						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Any							=      "stabilityai/stable-diffusion-2"
										_UpperCAmelCase						,							_UpperCAmelCase    :						Optional[int]							=      FlaxDPMSolverMultistepScheduler.from_pretrained(__UpperCamelCase  ,   subfolder="scheduler"		)
										_UpperCAmelCase						,							_UpperCAmelCase    :						Optional[Any]							=      FlaxStableDiffusionPipeline.from_pretrained(
										    __UpperCamelCase  ,   scheduler=__UpperCamelCase  ,   revision="bf16"  ,   dtype=jnp.bfloataa  ,   )
										_UpperCAmelCase    :						str							=      scheduler_params

										_UpperCAmelCase    :						Optional[int]							=      "A painting of a squirrel eating a burger"
										_UpperCAmelCase    :						Any							=      jax.device_count()
										_UpperCAmelCase    :						Union[str, Any]							=      num_samples * [prompt]
										_UpperCAmelCase    :						Optional[Any]							=      sd_pipe.prepare_inputs(__UpperCamelCase		)

										_UpperCAmelCase    :						str							=      replicate(__UpperCamelCase		)
										_UpperCAmelCase    :						Any							=      shard(__UpperCamelCase		)

										_UpperCAmelCase    :						Optional[Any]							=      jax.random.PRNGKey(0		)
										_UpperCAmelCase    :						List[Any]							=      jax.random.split(__UpperCamelCase  ,   jax.device_count()		)

										_UpperCAmelCase    :						List[Any]							=      sd_pipe(__UpperCamelCase  ,   __UpperCamelCase  ,   __UpperCamelCase  ,   num_inference_steps=25  ,   jit=__UpperCamelCase		)[0]
										assert images.shape == (jax.device_count(), 1, 768, 768, 3)

										_UpperCAmelCase    :						Dict							=      images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]		)
										_UpperCAmelCase    :						int							=      images[0, 253:256, 253:256, -1]

										_UpperCAmelCase    :						Tuple							=      jnp.asarray(jax.device_get(image_slice.flatten()		)		)
										_UpperCAmelCase    :						Optional[Any]							=      jnp.array([0.43_36, 0.4_29_69, 0.44_53, 0.41_99, 0.42_97, 0.45_31, 0.44_34, 0.44_34, 0.42_97]		)
										print(f'output_slice: {output_slice}'		)
										assert jnp.abs(output_slice - expected_slice		).max() < 1e-2





from __future__ import annotations

import math
import random
from collections.abc import Collection
from typing import overload

class 			a					:


						def __init__(    self  ,   A_ = None		):







										'''simple docstring'''


										if components is None:
														_UpperCAmelCase    :						Dict							=      []
										_UpperCAmelCase    :						Dict							=      list(A_		)


						def __len__(    self		):







										'''simple docstring'''


										return len(self.__components		)


						def __str__(    self		):







										'''simple docstring'''


										return "(" + ",".join(map(A_  ,   self.__components		)		) + ")"


						def __add__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						int							=      len(self		)
										if size == len(A_		):
														_UpperCAmelCase    :						Union[str, Any]							=      [self.__components[i] + other.component(A_		) for i in range(A_		)]
														return Vector(A_		)
										else:
														raise Exception("must have the same size"		)


						def __sub__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[str]							=      len(self		)
										if size == len(A_		):
														_UpperCAmelCase    :						Optional[Any]							=      [self.__components[i] - other.component(A_		) for i in range(A_		)]
														return Vector(A_		)
										else:  # error case
														raise Exception("must have the same size"		)


						@overload
						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										...


						@overload
						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										...


						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										if isinstance(A_  ,   (float, int)		):
														_UpperCAmelCase    :						str							=      [c * other for c in self.__components]
														return Vector(A_		)
										elif isinstance(A_  ,   A_		) and len(self		) == len(A_		):
														_UpperCAmelCase    :						int							=      len(self		)
														_UpperCAmelCase    :						Any							=      [self.__components[i] * other.component(A_		) for i in range(A_		)]
														return sum(A_		)
										else:  # error case
														raise Exception("invalid operand!"		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return Vector(self.__components		)


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										if isinstance(A_  ,   A_		) and -len(self.__components		) <= i < len(self.__components		):
														return self.__components[i]
										else:
														raise Exception("index out of range"		)


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										assert -len(self.__components		) <= pos < len(self.__components		)
										_UpperCAmelCase    :						Any							=      value


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										if len(self.__components		) == 0:
														raise Exception("Vector is empty"		)
										_UpperCAmelCase    :						Dict							=      [c**2 for c in self.__components]
										return math.sqrt(sum(A_		)		)





						def     _UpperCAmelCase			(    self  ,   A_  ,   A_ = False		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      self * other
										_UpperCAmelCase    :						str							=      self.euclidean_length() * other.euclidean_length()
										if deg:
														return math.degrees(math.acos(num / den		)		)
										else:
														return math.acos(num / den		)







def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int	)				->    Vector:
				assert isinstance(lowerCAmelCase					, lowerCAmelCase	)
				return Vector([0] * dimension	)

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int					, lowerCAmelCase:					int	)				->    Vector:
				assert isinstance(lowerCAmelCase					, lowerCAmelCase	) and (isinstance(lowerCAmelCase					, lowerCAmelCase	))
				_UpperCAmelCase    :						Tuple							=      [0] * dimension
				_UpperCAmelCase    :						Optional[Any]							=      1
				return Vector(lowerCAmelCase	)

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					float					, lowerCAmelCase:					Vector					, lowerCAmelCase:					Vector	)				->    Vector:
				assert (
				    isinstance(lowerCAmelCase					, lowerCAmelCase	)
				    and isinstance(lowerCAmelCase					, lowerCAmelCase	)
				    and (isinstance(lowerCAmelCase					, (int, float)	))
				)
				return x * scalar + y

def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int					, lowerCAmelCase:					int					, lowerCAmelCase:					int	)				->    Vector:
				random.seed(lowerCAmelCase	)
				_UpperCAmelCase    :						Optional[int]							=      [random.randint(lowerCAmelCase					, lowerCAmelCase	) for _ in range(lowerCAmelCase	)]
				return Vector(lowerCAmelCase	)

class 			a					:


						def __init__(    self  ,   A_  ,   A_  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      matrix
										_UpperCAmelCase    :						Union[str, Any]							=      w
										_UpperCAmelCase    :						str							=      h


						def __str__(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Optional[int]							=      ""
										for i in range(self.__height		):
														ans += "|"
														for j in range(self.__width		):
																		if j < self.__width - 1:
																						ans += str(self.__matrix[i][j]		) + ","
																		else:
																						ans += str(self.__matrix[i][j]		) + "|\n"
										return ans


						def __add__(    self  ,   A_		):







										'''simple docstring'''


										if self.__width == other.width() and self.__height == other.height():
														_UpperCAmelCase    :						Optional[int]							=      []
														for i in range(self.__height		):
																		_UpperCAmelCase    :						List[str]							=      [
																		    self.__matrix[i][j] + other.component(A_  ,   A_		)
																		    for j in range(self.__width		)
																		]
																		matrix.append(A_		)
														return Matrix(A_  ,   self.__width  ,   self.__height		)
										else:
														raise Exception("matrix must have the same dimension!"		)


						def __sub__(    self  ,   A_		):







										'''simple docstring'''


										if self.__width == other.width() and self.__height == other.height():
														_UpperCAmelCase    :						Optional[Any]							=      []
														for i in range(self.__height		):
																		_UpperCAmelCase    :						Tuple							=      [
																		    self.__matrix[i][j] - other.component(A_  ,   A_		)
																		    for j in range(self.__width		)
																		]
																		matrix.append(A_		)
														return Matrix(A_  ,   self.__width  ,   self.__height		)
										else:
														raise Exception("matrices must have the same dimension!"		)


						@overload
						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										...


						@overload
						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										...


						def __mul__(    self  ,   A_		):







										'''simple docstring'''


										if isinstance(A_  ,   A_		):  # matrix-vector
														if len(A_		) == self.__width:
																		_UpperCAmelCase    :						Union[str, Any]							=      zero_vector(self.__height		)
																		for i in range(self.__height		):
																						_UpperCAmelCase    :						List[Any]							=      [
																						    self.__matrix[i][j] * other.component(A_		)
																						    for j in range(self.__width		)
																						]
																						ans.change_component(A_  ,   sum(A_		)		)
																		return ans
														else:
																		raise Exception(
																		    "vector must have the same size as the "
																		    "number of columns of the matrix!"		)
										elif isinstance(A_  ,   (int, float)		):  # matrix-scalar
														_UpperCAmelCase    :						Any							=      [
														    [self.__matrix[i][j] * other for j in range(self.__width		)]
														    for i in range(self.__height		)
														]
														return Matrix(A_  ,   self.__width  ,   self.__height		)
										return None


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return self.__height


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return self.__width


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										if 0 <= x < self.__height and 0 <= y < self.__width:
														return self.__matrix[x][y]
										else:
														raise Exception("change_component: indices out of bounds"		)


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_  ,   A_		):







										'''simple docstring'''


										if 0 <= x < self.__height and 0 <= y < self.__width:
														_UpperCAmelCase    :						Tuple							=      value
										else:
														raise Exception("change_component: indices out of bounds"		)


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										if self.__height != self.__width:
														raise Exception("Matrix is not square"		)
										_UpperCAmelCase    :						Union[str, Any]							=      self.__matrix[:x] + self.__matrix[x + 1 :]
										for i in range(len(A_		)		):
														_UpperCAmelCase    :						Tuple							=      minor[i][:y] + minor[i][y + 1 :]
										return Matrix(A_  ,   self.__width - 1  ,   self.__height - 1		).determinant()


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										if self.__height != self.__width:
														raise Exception("Matrix is not square"		)
										if 0 <= x < self.__height and 0 <= y < self.__width:
														return (-1) ** (x + y) * self.minor(A_  ,   A_		)
										else:
														raise Exception("Indices out of bounds"		)





						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										if self.__height != self.__width:
														raise Exception("Matrix is not square"		)
										if self.__height < 1:
														raise Exception("Matrix has no element"		)
										elif self.__height == 1:
														return self.__matrix[0][0]
										elif self.__height == 2:
														return (
														    self.__matrix[0][0] * self.__matrix[1][1]
														    - self.__matrix[0][1] * self.__matrix[1][0]
														)
										else:
														_UpperCAmelCase    :						Dict							=      [
														    self.__matrix[0][y] * self.cofactor(0  ,   A_		) for y in range(self.__width		)
														]
														return sum(A_		)







def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int	)				->    Matrix:
				_UpperCAmelCase    :						list[list[float]]							=      [[0] * n for _ in range(lowerCAmelCase	)]
				return Matrix(lowerCAmelCase					, lowerCAmelCase					, lowerCAmelCase	)





def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int					, lowerCAmelCase:					int					, lowerCAmelCase:					int					, lowerCAmelCase:					int	)				->    Matrix:
				random.seed(lowerCAmelCase	)
				_UpperCAmelCase    :						list[list[float]]							=      [
				    [random.randint(lowerCAmelCase					, lowerCAmelCase	) for _ in range(lowerCAmelCase	)] for _ in range(lowerCAmelCase	)
				]
				return Matrix(lowerCAmelCase					, lowerCAmelCase					, lowerCAmelCase	)


