
'''simple docstring'''





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 						a   (				unittest.TestCase    ):




				def 	__snake_case							(							self	:				Tuple,    SCREAMING_SNAKE_CASE_	:				Dict,    SCREAMING_SNAKE_CASE_	:				Optional[int]      ):
										return F"""gaussian_noise_s={seed}_shape={'_'.join([str(SCREAMING_SNAKE_CASE_      ) for s in shape]      )}.npy"""




				def 	__snake_case							(							self	:				int      ):
										# clean up the VRAM after each test
										super().tearDown()
										gc.collect()




				def 	__snake_case							(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				Tuple=0,    SCREAMING_SNAKE_CASE_	:				int=(4, 4, 64, 64),    SCREAMING_SNAKE_CASE_	:				Union[str, Any]=False      ):
										snake_case       :     str =    jnp.bfloataa if fpaa else jnp.floataa
										snake_case       :     int =    jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_      )      ),    dtype=SCREAMING_SNAKE_CASE_      )
										return image




				def 	__snake_case							(							self	:				Optional[int],    SCREAMING_SNAKE_CASE_	:				List[str]=False,    SCREAMING_SNAKE_CASE_	:				int="CompVis/stable-diffusion-v1-4"      ):
										snake_case       :     Optional[int] =    jnp.bfloataa if fpaa else jnp.floataa
										snake_case       :     List[Any] =    '''bf16''' if fpaa else None

										snake_case,					snake_case       :     Optional[Any] =    FlaxUNetaDConditionModel.from_pretrained(
										    SCREAMING_SNAKE_CASE_,    subfolder='''unet''',    dtype=SCREAMING_SNAKE_CASE_,    revision=SCREAMING_SNAKE_CASE_      )
										return model, params




				def 	__snake_case							(							self	:				List[Any],    SCREAMING_SNAKE_CASE_	:				int=0,    SCREAMING_SNAKE_CASE_	:				Optional[int]=(4, 77, 7_68),    SCREAMING_SNAKE_CASE_	:				List[str]=False      ):
										snake_case       :     str =    jnp.bfloataa if fpaa else jnp.floataa
										snake_case       :     List[str] =    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
				        [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
				        [17, 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, 10_00, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
				        # fmt: on
				    ]      )
				def 	__snake_case							(							self	:				List[Any],    SCREAMING_SNAKE_CASE_	:				Dict,    SCREAMING_SNAKE_CASE_	:				int,    SCREAMING_SNAKE_CASE_	:				Tuple      ):
										snake_case,					snake_case       :     List[str] =    self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4''',    fpaa=SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[Any] =    self.get_latents(SCREAMING_SNAKE_CASE_,    fpaa=SCREAMING_SNAKE_CASE_      )
										snake_case       :     Tuple =    self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_,    fpaa=SCREAMING_SNAKE_CASE_      )

										snake_case       :     Dict =    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

										snake_case       :     Any =    jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())      ),    dtype=jnp.floataa      )
										snake_case       :     int =    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
				        [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
				        [17, 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, 10_00, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
				        # fmt: on
				    ]      )
				def 	__snake_case							(							self	:				str,    SCREAMING_SNAKE_CASE_	:				Any,    SCREAMING_SNAKE_CASE_	:				int,    SCREAMING_SNAKE_CASE_	:				int      ):
										snake_case,					snake_case       :     Tuple =    self.get_unet_model(model_id='''stabilityai/stable-diffusion-2''',    fpaa=SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[int] =    self.get_latents(SCREAMING_SNAKE_CASE_,    shape=(4, 4, 96, 96),    fpaa=SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[Any] =    self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_,    shape=(4, 77, 10_24),    fpaa=SCREAMING_SNAKE_CASE_      )

										snake_case       :     int =    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

										snake_case       :     List[Any] =    jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())      ),    dtype=jnp.floataa      )
										snake_case       :     Union[str, Any] =    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      )



'''simple docstring'''





import numpy as np

class 						a   :




				def __init__(							self	:				Dict      ):
										snake_case       :     List[str] =    (0, 0)
										snake_case       :     Tuple =    None
										snake_case       :     Union[str, Any] =    0
										snake_case       :     Dict =    0
										snake_case       :     List[str] =    0




				def __eq__(							self	:				str,    SCREAMING_SNAKE_CASE_	:				List[Any]      ):
										return self.position == cell.position




				def 	__snake_case							(							self	:				Optional[int]      ):
										print(self.position      )




class 						a   :




				def __init__(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				Union[str, Any]=(5, 5)      ):
										snake_case       :     int =    np.zeros(SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[int] =    world_size[0]
										snake_case       :     Optional[Any] =    world_size[1]




				def 	__snake_case							(							self	:				Any      ):
										print(self.w      )




				def 	__snake_case							(							self	:				str,    SCREAMING_SNAKE_CASE_	:				Optional[int]      ):
										snake_case       :     Union[str, Any] =    [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										snake_case       :     str =    cell.position[0]
										snake_case       :     Optional[Any] =    cell.position[1]
										snake_case       :     Any =    []
										for n in neughbour_cord:
																snake_case       :     List[str] =    current_x + n[0]
																snake_case       :     Tuple =    current_y + n[1]
																if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																						snake_case       :     int =    Cell()
																						snake_case       :     int =    (x, y)
																						snake_case       :     Any =    cell
																						neighbours.append(SCREAMING_SNAKE_CASE_      )
										return neighbours




def      A (       A_							:					Tuple    ,							A_							:					Tuple    ,							A_							:					Union[str, Any]       ):
						snake_case       :     Union[str, Any] =    []
						snake_case       :     Union[str, Any] =    []
						_open.append(A_       )

						while _open:
												snake_case       :     List[Any] =    np.argmin([n.f for n in _open]       )
												snake_case       :     List[Any] =    _open[min_f]
												_closed.append(_open.pop(A_       )       )
												if current == goal:
																		break
												for n in world.get_neigbours(A_       ):
																		for c in _closed:
																								if c == n:
																														continue
																		snake_case       :     Dict =    current.g + 1
																		snake_case,					snake_case       :     Optional[Any] =    n.position
																		snake_case,					snake_case       :     Union[str, Any] =    goal.position
																		snake_case       :     Tuple =    (ya - ya) ** 2 + (xa - xa) ** 2
																		snake_case       :     Union[str, Any] =    n.h + n.g

																		for c in _open:
																								if c == n and c.f < n.f:
																														continue
																		_open.append(A_       )
						snake_case       :     Dict =    []
						while current.parent is not None:
												path.append(current.position       )
												snake_case       :     Tuple =    current.parent
						path.append(current.position       )
						return path[::-1]


if __name__ == "__main__":
						UpperCAmelCase    					=   Gridworld()
						# Start position and goal
						UpperCAmelCase    					=   Cell()
						UpperCAmelCase    					=   (0, 0)
						UpperCAmelCase    					=   Cell()
						UpperCAmelCase    					=   (4, 4)
						print(f'''path from {start.position} to {goal.position}''')
						UpperCAmelCase    					=   astar(world, start, goal)
						#   Just for visual reasons.
						for i in s:
												UpperCAmelCase    					=   1
						print(world.w)

