


'''simple docstring'''






import heapq
import sys

import numpy as np

__UpperCAmelCase       							=				tuple[int, int]




class 						a__							:





							'''simple docstring'''






							def __init__(						self  )			->				Union[str, Any]:
														lowerCAmelCase__			  =      []
														lowerCAmelCase__			  =      set()







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Any:
														if not self.empty():
																					return self.elements[0][0]
														else:
																					return float('''inf'''  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Union[str, Any]:
														return len(self.elements  ) == 0







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_  )			->				Optional[Any]:
														if item not in self.set:
																					heapq.heappush(self.elements   ,       (priority, item)  )
																					self.set.add(lowerCamelCase_  )
														else:
																					# update
																					# print("update", item)
																					lowerCAmelCase__			  =      []
																					((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      heapq.heappop(self.elements  )
																					while x != item:
																												temp.append((pri, x)  )
																												((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      heapq.heappop(self.elements  )
																					temp.append((priority, item)  )
																					for pro, xxx in temp:
																												heapq.heappush(self.elements   ,       (pro, xxx)  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				Tuple:
														if item in self.set:
																					self.set.remove(lowerCamelCase_  )
																					lowerCAmelCase__			  =      []
																					((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      heapq.heappop(self.elements  )
																					while x != item:
																												temp.append((pro, x)  )
																												((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      heapq.heappop(self.elements  )
																					for prito, yyy in temp:
																												heapq.heappush(self.elements   ,       (prito, yyy)  )







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				int:
														return self.elements[0][1]







							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Any:
														((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      heapq.heappop(self.elements  )
														self.set.remove(lowerCamelCase_  )
														return (priority, item)


def    _snake_case  (	A					,       A			)		->       Tuple:
							# euclidean distance
							lowerCAmelCase__			  =      np.array(A			)
							lowerCAmelCase__			  =      np.array(A			)
							return np.linalg.norm(a - b			)


def    _snake_case  (	A					,       A			)		->       List[str]:
							# integer division by time variable
							return consistent_heuristic(A					,       A			) // t


def    _snake_case  (	A					,       A			)		->       List[Any]:
							# manhattan distance
							return abs(p[0] - goal[0]			) + abs(p[1] - goal[1]			)


def    _snake_case  (	A					,       A					,       A					,       A			)		->       str:
							lowerCAmelCase__			  =      g_function[start] + Wa * heuristics[i](A					,       A			)
							return ans


def    _snake_case  (	A					,       A					,       A			)		->       int:
							lowerCAmelCase__			  =      np.chararray((n, n)			)
							for i in range(A			):
														for j in range(A			):
																					lowerCAmelCase__			  =      '''*'''

							for i in range(A			):
														for j in range(A			):
																					if (j, (n - 1) - i) in blocks:
																												lowerCAmelCase__			  =      '''#'''

							lowerCAmelCase__			  =      '''-'''
							lowerCAmelCase__			  =      back_pointer[goal]
							while x != start:
														((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      x
														# print(x)
														lowerCAmelCase__			  =      '''-'''
														lowerCAmelCase__			  =      back_pointer[x]
							lowerCAmelCase__			  =      '''-'''

							for i in range(A			):
														for j in range(A			):
																					if (i, j) == (0, n - 1):
																												print(grid[i][j]					,       end=''' '''			)
																												print('''<-- End position'''					,       end=''' '''			)
																					else:
																												print(grid[i][j]					,       end=''' '''			)
														print()
							print('''^'''			)
							print('''Start position'''			)
							print()
							print('''# is an obstacle'''			)
							print('''- is the path taken by algorithm'''			)
							print('''PATH TAKEN BY THE ALGORITHM IS:-'''			)
							lowerCAmelCase__			  =      back_pointer[goal]
							while x != start:
														print(A					,       end=''' '''			)
														lowerCAmelCase__			  =      back_pointer[x]
							print(A			)
							sys.exit()


def    _snake_case  (	A			)		->       Any:
							if p[0] < 0 or p[0] > n - 1:
														return False
							if p[1] < 0 or p[1] > n - 1:
														return False
							return True


def    _snake_case  (	A					,       A					,       A					,       A					,       A					,       A					,       A					,       A					,       )		->       str:
							for itera in range(A			):
														open_list[itera].remove_element(A			)
							# print("s", s)
							# print("j", j)
							((lowerCAmelCase__)  ,   (lowerCAmelCase__))			  =      s
							lowerCAmelCase__			  =      (x - 1, y)
							lowerCAmelCase__			  =      (x + 1, y)
							lowerCAmelCase__			  =      (x, y + 1)
							lowerCAmelCase__			  =      (x, y - 1)

							for neighbours in [left, right, up, down]:
														if neighbours not in blocks:
																					if valid(A			) and neighbours not in visited:
																												# print("neighbour", neighbours)
																												visited.add(A			)
																												lowerCAmelCase__			  =      -1
																												lowerCAmelCase__			  =      float('''inf'''			)

																					if valid(A			) and g_function[neighbours] > g_function[s] + 1:
																												lowerCAmelCase__			  =      g_function[s] + 1
																												lowerCAmelCase__			  =      s
																												if neighbours not in close_list_anchor:
																																			open_list[0].put(A					,       key(A					,       0					,       A					,       A			)			)
																																			if neighbours not in close_list_inad:
																																										for var in range(1					,       A			):
																																																	if key(A					,       A					,       A					,       A			) <= Wa * key(
																																																	    A					,       0					,       A					,       A			):
																																																								open_list[j].put(
																																																								    A					,       key(A					,       A					,       A					,       A			)			)


def    _snake_case  (	)		->       str:
							lowerCAmelCase__			  =      []
							for x in range(1					,       5			):
														for y in range(1					,       6			):
																					some_list.append((x, y)			)

							for x in range(15					,       20			):
														some_list.append((x, 17)			)

							for x in range(10					,       19			):
														for y in range(1					,       15			):
																					some_list.append((x, y)			)

    # L block
							for x in range(1					,       4			):
														for y in range(12					,       19			):
																					some_list.append((x, y)			)
							for x in range(3					,       13			):
														for y in range(16					,       19			):
																					some_list.append((x, y)			)
							return some_list


__UpperCAmelCase       							=				{0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

__UpperCAmelCase       							=				[
    (0, 1),
    (1, 1),
    (2, 1),
    (3, 1),
    (4, 1),
    (5, 1),
    (6, 1),
    (7, 1),
    (8, 1),
    (9, 1),
    (10, 1),
    (11, 1),
    (12, 1),
    (13, 1),
    (14, 1),
    (15, 1),
    (16, 1),
    (17, 1),
    (18, 1),
    (19, 1),
]
__UpperCAmelCase       							=				make_common_ground()


__UpperCAmelCase       							=				blocks_blk
# hyper parameters
__UpperCAmelCase       							=				1
__UpperCAmelCase       							=				1
__UpperCAmelCase       							=				20
__UpperCAmelCase       							=				3  # one consistent and two other inconsistent

# start and end destination
__UpperCAmelCase       							=				(0, 0)
__UpperCAmelCase       							=				(n - 1, n - 1)

__UpperCAmelCase       							=				1


def    _snake_case  (	A					,       A					,       A			)		->       Dict:
							lowerCAmelCase__			  =      {start: 0, goal: float('''inf'''			)}
							lowerCAmelCase__			  =      {start: -1, goal: -1}
							lowerCAmelCase__			  =      []
							lowerCAmelCase__			  =      set()

							for i in range(A			):
														open_list.append(PriorityQueue()			)
														open_list[i].put(A					,       key(A					,       A					,       A					,       A			)			)

							lowerCAmelCase__			  =      []
							lowerCAmelCase__			  =      []
							while open_list[0].minkey() < float('''inf'''			):
														for i in range(1					,       A			):
																					# print(open_list[0].minkey(), open_list[i].minkey())
																					if open_list[i].minkey() <= Wa * open_list[0].minkey():
																												global t
																												t += 1
																												if g_function[goal] <= open_list[i].minkey():
																																			if g_function[goal] < float('''inf'''			):
																																										do_something(A					,       A					,       A			)
																												else:
																																			lowerCAmelCase__  ,   lowerCAmelCase__			  =      open_list[i].top_show()
																																			visited.add(A			)
																																			expand_state(
																																			    A					,       A					,       A					,       A					,       A					,       A					,       A					,       A					,       )
																																			close_list_inad.append(A			)
																					else:
																												if g_function[goal] <= open_list[0].minkey():
																																			if g_function[goal] < float('''inf'''			):
																																										do_something(A					,       A					,       A			)
																												else:
																																			lowerCAmelCase__			  =      open_list[0].top_show()
																																			visited.add(A			)
																																			expand_state(
																																			    A					,       0					,       A					,       A					,       A					,       A					,       A					,       A					,       )
																																			close_list_anchor.append(A			)
							print('''No path found to goal'''			)
							print()
							for i in range(n - 1					,       -1					,       -1			):
														for j in range(A			):
																					if (j, i) in blocks:
																												print('''#'''					,       end=''' '''			)
																					elif (j, i) in back_pointer:
																												if (j, i) == (n - 1, n - 1):
																																			print('''*'''					,       end=''' '''			)
																												else:
																																			print('''-'''					,       end=''' '''			)
																					else:
																												print('''*'''					,       end=''' '''			)
																					if (j, i) == (n - 1, n - 1):
																												print('''<-- End position'''					,       end=''' '''			)
														print()
							print('''^'''			)
							print('''Start position'''			)
							print()
							print('''# is an obstacle'''			)
							print('''- is the path taken by algorithm'''			)


if __name__ == "__main__":
		multi_a_star(start, goal, n_heuristic)

"""simple docstring"""


import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration






def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  [
			    '''encoder.version''',
			    '''decoder.version''',
			    '''model.encoder.version''',
			    '''model.decoder.version''',
			    '''_float_tensor''',
			    '''decoder.output_projection.weight''',
			]
			for k in ignore_keys:
						state_dict.pop(lowerCAmelCase__	,lowerCAmelCase__						)






def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_		, lowerCamelCase_					=  emb.weight.shape
			lowerCamelCase_					=  nn.Linear(lowerCAmelCase__	,lowerCAmelCase__	,bias=lowerCAmelCase__						)
			lowerCamelCase_					=  emb.weight.data
			return lin_layer






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__="facebook/mbart-large-en-ro"	,lowerCAmelCase__=False	,lowerCAmelCase__=False						):
			lowerCamelCase_					=  torch.load(lowerCAmelCase__	,map_location='''cpu'''						)['''model''']
			remove_ignore_keys_(lowerCAmelCase__						)
			lowerCamelCase_					=  state_dict['''encoder.embed_tokens.weight'''].shape[0]

			lowerCamelCase_					=  MBartConfig.from_pretrained(lowerCAmelCase__	,vocab_size=lowerCAmelCase__						)
			if mbart_aa and finetuned:
						lowerCamelCase_					=  '''relu'''

			lowerCamelCase_					=  state_dict['''decoder.embed_tokens.weight''']
			lowerCamelCase_					=  MBartForConditionalGeneration(lowerCAmelCase__						)
			model.model.load_state_dict(lowerCAmelCase__						)

			if finetuned:
						lowerCamelCase_					=  make_linear_from_emb(model.model.shared						)

			return model


if __name__ == "__main__":
						A_    							=					argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    """fairseq_path""", type=str, help="""bart.large, bart.large.cnn or a path to a model.pt on local filesystem."""
						)
						parser.add_argument("""pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model.""")
						parser.add_argument(
						    """--hf_config""",
						    default="""facebook/mbart-large-cc25""",
						    type=str,
						    help="""Which huggingface architecture to use: mbart-large""",
						)
						parser.add_argument("""--mbart_50""", action="""store_true""", help="""whether the model is mMART-50 checkpoint""")
						parser.add_argument("""--finetuned""", action="""store_true""", help="""whether the model is a fine-tuned checkpoint""")
						A_    							=					parser.parse_args()
						A_    							=					convert_fairseq_mbart_checkpoint_from_disk(
						    args.fairseq_path, hf_config_path=args.hf_config, finetuned=args.finetuned, mbart_aa=args.mbart_aa
						)
						model.save_pretrained(args.pytorch_dump_folder_path)



