






import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    int			,		UpperCamelCase__    :    int):






											'''simple docstring'''







											if isinstance(UpperCamelCase__			,		UpperCamelCase__):
																		# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
																		# modified it, it will not be accepted here again, since `auto` values would have been overridden
																		snake_case__	  =       deepcopy(UpperCamelCase__)
											elif os.path.exists(UpperCamelCase__):
																		with io.open(UpperCamelCase__			,		"""r"""			,		encoding="""utf-8""") as f:
																									snake_case__	  =       json.load(UpperCamelCase__)
											else:
																		try:
																									snake_case__	  =       baseaa.urlsafe_baadecode(UpperCamelCase__).decode("""utf-8""")
																									snake_case__	  =       json.loads(UpperCamelCase__)
																		except (UnicodeDecodeError, AttributeError, ValueError):
																									raise ValueError(
																									    F'''Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}''')

											snake_case__	  =       config

											self.set_stage_and_offload()



				def 					__magic_name__							(      self    :    List[str]):






											'''simple docstring'''







											snake_case__	  =       self.get_value("""zero_optimization.stage"""			,		-1)

											# offload
											snake_case__	  =       False
											if self.is_zeroa() or self.is_zeroa():
																		snake_case__	  =       set(["""cpu""", """nvme"""])
																		snake_case__	  =       set(
																		    [
																		        self.get_value("""zero_optimization.offload_optimizer.device"""),
																		        self.get_value("""zero_optimization.offload_param.device"""),
																		    ])
																		if len(offload_devices & offload_devices_valid) > 0:
																									snake_case__	  =       True



				def 					__magic_name__							(      self    :    str			,		UpperCamelCase__    :    Any):






											'''simple docstring'''







											snake_case__	  =       self.config

											# find the config node of interest if it exists
											snake_case__	  =       ds_key_long.split(""".""")
											snake_case__	  =       nodes.pop()
											for node in nodes:
																		snake_case__	  =       config.get(UpperCamelCase__)
																		if config is None:
																									return None, ds_key

											return config, ds_key



				def 					__magic_name__							(      self    :    Dict			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int=None):






											'''simple docstring'''







											snake_case__  , snake_case__	  =       self.find_config_node(UpperCamelCase__)
											if config is None:
																		return default
											return config.get(UpperCamelCase__			,		UpperCamelCase__)



				def 					__magic_name__							(      self    :    Optional[int]			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    List[Any]=False):






											'''simple docstring'''







											snake_case__	  =       self.config

											# find the config node of interest if it exists
											snake_case__	  =       ds_key_long.split(""".""")
											for node in nodes:
																		snake_case__	  =       config
																		snake_case__	  =       config.get(UpperCamelCase__)
																		if config is None:
																									if must_exist:
																																raise ValueError(F'''Can\'t find {ds_key_long} entry in the config: {self.config}''')
																									else:
																																return

        # if found remove it
											if parent_config is not None:
																		parent_config.pop(UpperCamelCase__)



				def 					__magic_name__							(      self    :    Optional[Any]			,		UpperCamelCase__    :    List[str]):






											'''simple docstring'''







											snake_case__	  =       self.get_value(UpperCamelCase__)
											return False if value is None else bool(UpperCamelCase__)



				def 					__magic_name__							(      self    :    Any			,		UpperCamelCase__    :    Optional[Any]):






											'''simple docstring'''







											snake_case__	  =       self.get_value(UpperCamelCase__)
											return False if value is None else not bool(UpperCamelCase__)



				def 					__magic_name__							(      self    :    List[Any]):






											'''simple docstring'''







											return self._stage == 2



				def 					__magic_name__							(      self    :    Tuple):






											'''simple docstring'''







											return self._stage == 3



				def 					__magic_name__							(      self    :    str):






											'''simple docstring'''







											return self._offload


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    List[str]			,		UpperCamelCase__    :    Any):






											'''simple docstring'''







											snake_case__	  =       engine



				def 					__magic_name__							(      self    :    List[str]			,		UpperCamelCase__    :    Any			,		**UpperCamelCase__    :    List[Any]):






											'''simple docstring'''







											self.engine.backward(UpperCamelCase__			,		**UpperCamelCase__)

											# Deepspeed's `engine.step` performs the following operations:
											# - gradient accumulation check
											# - gradient clipping
											# - optimizer step
											# - zero grad
											# - checking overflow
											# - lr_scheduler step (only if engine.lr_scheduler is not None)
											self.engine.step()
											# and this plugin overrides the above calls with no-ops when Accelerate runs under
											# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
											# training loop that works transparently under many training regimes.


class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				def __init__(      self    :    int			,		UpperCamelCase__    :    str):






											'''simple docstring'''







											super().__init__(UpperCamelCase__			,		device_placement=UpperCamelCase__			,		scaler=UpperCamelCase__)
											snake_case__	  =       hasattr(self.optimizer			,		"""overflow""")



				def 					__magic_name__							(      self    :    Optional[Any]			,		UpperCamelCase__    :    Union[str, Any]=None):






											'''simple docstring'''







											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



				def 					__magic_name__							(      self    :    Union[str, Any]):






											'''simple docstring'''







											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



				@property
				def 					__magic_name__							(      self    :    List[Any]):






											'''simple docstring'''







											if self.__has_overflow__:
																		return self.optimizer.overflow
											return False


class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				def __init__(      self    :    Any			,		UpperCamelCase__    :    Optional[Any]			,		UpperCamelCase__    :    str):






											'''simple docstring'''







											super().__init__(UpperCamelCase__			,		UpperCamelCase__)



				def 					__magic_name__							(      self    :    Dict):






											'''simple docstring'''







											pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Tuple			,		UpperCamelCase__    :    Optional[Any]			,		UpperCamelCase__    :    Dict=0.0_01			,		UpperCamelCase__    :    Any=0			,		**UpperCamelCase__    :    List[Any]):






											'''simple docstring'''







											snake_case__	  =       params
											snake_case__	  =       lr
											snake_case__	  =       weight_decay
											snake_case__	  =       kwargs


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    List[Any]			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    List[str]=None			,		UpperCamelCase__    :    Dict=0			,		**UpperCamelCase__    :    int):






											'''simple docstring'''







											snake_case__	  =       optimizer
											snake_case__	  =       total_num_steps
											snake_case__	  =       warmup_num_steps
											snake_case__	  =       kwargs








from __future__ import annotations

import time

a__       =     list[tuple[int, int]]

a__       =     [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

a__       =     [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Dict			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    int			,		UpperCamelCase__    :    Node | None):






											'''simple docstring'''







											snake_case__	  =       pos_x
											snake_case__	  =       pos_y
											snake_case__	  =       (pos_y, pos_x)
											snake_case__	  =       goal_x
											snake_case__	  =       goal_y
											snake_case__	  =       parent


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    Optional[int]			,		UpperCamelCase__    :    tuple[int, int]			,		UpperCamelCase__    :    tuple[int, int]):






											'''simple docstring'''







											snake_case__	  =       Node(start[1]			,		start[0]			,		goal[1]			,		goal[0]			,		UpperCamelCase__)
											snake_case__	  =       Node(goal[1]			,		goal[0]			,		goal[1]			,		goal[0]			,		UpperCamelCase__)

											snake_case__	  =       [self.start]
											snake_case__	  =       False



				def 					__magic_name__							(      self    :    List[Any]):






											'''simple docstring'''







											while self.node_queue:
																		snake_case__	  =       self.node_queue.pop(0)

																		if current_node.pos == self.target.pos:
																									snake_case__	  =       True
																									return self.retrace_path(UpperCamelCase__)

																		snake_case__	  =       self.get_successors(UpperCamelCase__)

																		for node in successors:
																									self.node_queue.append(UpperCamelCase__)

											if not self.reached:
																		return [self.start.pos]
											return None



				def 					__magic_name__							(      self    :    Any			,		UpperCamelCase__    :    Node):






											'''simple docstring'''







											snake_case__	  =       []
											for action in delta:
																		snake_case__	  =       parent.pos_x + action[1]
																		snake_case__	  =       parent.pos_y + action[0]
																		if not (0 <= pos_x <= len(grid[0]) - 1 and 0 <= pos_y <= len(UpperCamelCase__) - 1):
																									continue

																		if grid[pos_y][pos_x] != 0:
																									continue

																		successors.append(
																		    Node(UpperCamelCase__			,		UpperCamelCase__			,		self.target.pos_y			,		self.target.pos_x			,		UpperCamelCase__))
											return successors



				def 					__magic_name__							(      self    :    str			,		UpperCamelCase__    :    Node | None):






											'''simple docstring'''







											snake_case__	  =       node
											snake_case__	  =       []
											while current_node is not None:
																		path.append((current_node.pos_y, current_node.pos_x))
																		snake_case__	  =       current_node.parent
											path.reverse()
											return path


class    _lowerCAmelCase			:



				"""simple docstring"""



				def __init__(      self    :    str			,		UpperCamelCase__    :    Optional[Any]			,		UpperCamelCase__    :    Any):






											'''simple docstring'''







											snake_case__	  =       BreadthFirstSearch(UpperCamelCase__			,		UpperCamelCase__)
											snake_case__	  =       BreadthFirstSearch(UpperCamelCase__			,		UpperCamelCase__)
											snake_case__	  =       False



				def 					__magic_name__							(      self    :    Any):






											'''simple docstring'''







											while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
																		snake_case__	  =       self.fwd_bfs.node_queue.pop(0)
																		snake_case__	  =       self.bwd_bfs.node_queue.pop(0)

																		if current_bwd_node.pos == current_fwd_node.pos:
																									snake_case__	  =       True
																									return self.retrace_bidirectional_path(
																									    UpperCamelCase__			,		UpperCamelCase__)

																		snake_case__	  =       current_bwd_node
																		snake_case__	  =       current_fwd_node

																		snake_case__	  =       {
																		    self.fwd_bfs: self.fwd_bfs.get_successors(UpperCamelCase__),
																		    self.bwd_bfs: self.bwd_bfs.get_successors(UpperCamelCase__),
																		}

																		for bfs in [self.fwd_bfs, self.bwd_bfs]:
																									for node in successors[bfs]:
																																bfs.node_queue.append(UpperCamelCase__)

											if not self.reached:
																		return [self.fwd_bfs.start.pos]
											return None



				def 					__magic_name__							(      self    :    Union[str, Any]			,		UpperCamelCase__    :    Node			,		UpperCamelCase__    :    Node):






											'''simple docstring'''







											snake_case__	  =       self.fwd_bfs.retrace_path(UpperCamelCase__)
											snake_case__	  =       self.bwd_bfs.retrace_path(UpperCamelCase__)
											bwd_path.pop()
											bwd_path.reverse()
											snake_case__	  =       fwd_path + bwd_path
											return path


if __name__ == "__main__":
	# all coordinates are given in format [y,x]
	import doctest

	doctest.testmod()
	a__       =     (0, 0)
	a__       =     (len(grid) - 1, len(grid[0]) - 1)
	for elem in grid:
		print(elem)

	a__       =     time.time()
	a__       =     BreadthFirstSearch(init, goal)
	a__       =     bfs.search()
	a__       =     time.time() - start_bfs_time

	print("""Unidirectional BFS computation time : """, bfs_time)

	a__       =     time.time()
	a__       =     BidirectionalBreadthFirstSearch(init, goal)
	a__       =     bd_bfs.search()
	a__       =     time.time() - start_bd_bfs_time

	print("""Bidirectional BFS computation time : """, bd_bfs_time)
