




"""simple docstring"""




import numpy as np






class 					__magic_name__							:






				'''simple docstring'''





				def __init__( self				):





							"""simple docstring"""
							lowerCamelCase       =      (0, 0)
							lowerCamelCase       =      None
							lowerCamelCase       =      0
							lowerCamelCase       =      0
							lowerCamelCase       =      0





				def __eq__( self	,				_a				):





							"""simple docstring"""
							return self.position == cell.position





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							print(self.position				)






class 					__magic_name__							:






				'''simple docstring'''





				def __init__( self	,				_a=(5, 5)				):





							"""simple docstring"""
							lowerCamelCase       =      np.zeros(_a				)
							lowerCamelCase       =      world_size[0]
							lowerCamelCase       =      world_size[1]





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							print(self.w				)





				def      _lowerCAmelCase       ( self	,				_a				):





							"""simple docstring"""
							lowerCamelCase       =      [
							    (-1, -1),
							    (-1, 0),
							    (-1, 1),
							    (0, -1),
							    (0, 1),
							    (1, -1),
							    (1, 0),
							    (1, 1),
							]
							lowerCamelCase       =      cell.position[0]
							lowerCamelCase       =      cell.position[1]
							lowerCamelCase       =      []
							for n in neughbour_cord:
										lowerCamelCase       =      current_x + n[0]
										lowerCamelCase       =      current_y + n[1]
										if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
													lowerCamelCase       =      Cell()
													lowerCamelCase       =      (x, y)
													lowerCamelCase       =      cell
													neighbours.append(_a				)
							return neighbours




def 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      int:
			lowerCamelCase       =      []
			lowerCamelCase       =      []
			_open.append(snake_case__       )

			while _open:
						lowerCamelCase       =      np.argmin([n.f for n in _open]       )
						lowerCamelCase       =      _open[min_f]
						_closed.append(_open.pop(snake_case__       )       )
						if current == goal:
									break
						for n in world.get_neigbours(snake_case__       ):
									for c in _closed:
												if c == n:
															continue
									lowerCamelCase       =      current.g + 1
									lowerCamelCase   ,     lowerCamelCase       =      n.position
									lowerCamelCase   ,     lowerCamelCase       =      goal.position
									lowerCamelCase       =      (ya - ya) ** 2 + (xa - xa) ** 2
									lowerCamelCase       =      n.h + n.g

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


if __name__ == "__main__":
					lowerCAmelCase							:    List[str]  							=							Gridworld()
					# Start position and goal
					lowerCAmelCase							:    str  							=							Cell()
					lowerCAmelCase							:    Any  							=							(0, 0)
					lowerCAmelCase							:    Any  							=							Cell()
					lowerCAmelCase							:    Union[str, Any]  							=							(4, 4)
					print(F"""path from {start.position} to {goal.position}""")
					lowerCAmelCase							:    List[str]  							=							astar(world, start, goal)
					#   Just for visual reasons.
					for i in s:
										lowerCAmelCase							:    Optional[Any]  							=							1
					print(world.w)









"""simple docstring"""




import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


lowerCAmelCase							:    Optional[Any]  							=							"""sshleifer/bart-tiny-random"""
lowerCAmelCase							:    List[Any]  							=							"""patrickvonplaten/t5-tiny-random"""






@require_torch
class 					__magic_name__							( unittest.TestCase       ):






				'''simple docstring'''





				@cached_property
				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							return AutoConfig.from_pretrained(_a				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=1				)
							self.assertEqual(student.config.num_hidden_layers	,				1				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=_a				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=_a				)
							self.assertEqual(student.config.encoder_layers	,				1				)
							self.assertEqual(student.config.decoder_layers	,				self.teacher_config.encoder_layers				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase   ,     *lowerCamelCase       =      create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=1	,				d=1				)
							self.assertEqual(student.config.encoder_layers	,				1				)
							self.assertEqual(student.config.decoder_layers	,				1				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							with self.assertRaises(_a				):
										create_student_by_copying_alternating_layers(_a	,				tempfile.mkdtemp()	,				e=_a	,				d=_a				)



