


import heapq
import sys

import numpy as np

A_     :       Optional[int]   							=tuple[int, int]





class 							lowercase_					:






							"""simple docstring"""







							def __init__( self		):







													"""simple docstring"""


													a_		      =		[]
													a_		      =		set()


							def     lowercase__  ( self		):







													"""simple docstring"""


													if not self.empty():
																			return self.elements[0][0]
													else:
																			return float("""inf"""		)


							def     lowercase__  ( self		):







													"""simple docstring"""


													return len(self.elements		) == 0


							def     lowercase__  ( self      ,     _UpperCAmelCase      ,     _UpperCAmelCase		):







													"""simple docstring"""


													if item not in self.set:
																			heapq.heappush(self.elements      ,     (priority, item)		)
																			self.set.add(_lowercase		)
													else:
																			# update
																			# print("update", item)
																			a_		      =		[]
																			((a_)      , (a_))		      =		heapq.heappop(self.elements		)
																			while x != item:
																									temp.append((pri, x)		)
																									((a_)      , (a_))		      =		heapq.heappop(self.elements		)
																			temp.append((priority, item)		)
																			for pro, xxx in temp:
																									heapq.heappush(self.elements      ,     (pro, xxx)		)


							def     lowercase__  ( self      ,     _UpperCAmelCase		):







													"""simple docstring"""


													if item in self.set:
																			self.set.remove(_lowercase		)
																			a_		      =		[]
																			((a_)      , (a_))		      =		heapq.heappop(self.elements		)
																			while x != item:
																									temp.append((pro, x)		)
																									((a_)      , (a_))		      =		heapq.heappop(self.elements		)
																			for prito, yyy in temp:
																									heapq.heappush(self.elements      ,     (prito, yyy)		)


							def     lowercase__  ( self		):







													"""simple docstring"""


													return self.elements[0][1]






							def     lowercase__  ( self		):







													"""simple docstring"""


													((a_)      , (a_))		      =		heapq.heappop(self.elements		)
													self.set.remove(_lowercase		)
													return (priority, item)




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						a_		      =		np.array(SCREAMING_SNAKE_CASE_   )
						a_		      =		np.array(SCREAMING_SNAKE_CASE_   )
						return np.linalg.norm(a - b   )




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						return consistent_heuristic(SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_   ) // t




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						return abs(p[0] - goal[0]   ) + abs(p[1] - goal[1]   )




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						a_		      =		g_function[start] + Wa * heuristics[i](SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_   )
						return ans




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						a_		      =		np.chararray((n, n)   )
						for i in range(SCREAMING_SNAKE_CASE_   ):
												for j in range(SCREAMING_SNAKE_CASE_   ):
																		a_		      =		"""*"""

						for i in range(SCREAMING_SNAKE_CASE_   ):
												for j in range(SCREAMING_SNAKE_CASE_   ):
																		if (j, (n - 1) - i) in blocks:
																								a_		      =		"""#"""

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

						for i in range(SCREAMING_SNAKE_CASE_   ):
												for j in range(SCREAMING_SNAKE_CASE_   ):
																		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:-"""   )
						a_		      =		back_pointer[goal]
						while x != start:
												print(SCREAMING_SNAKE_CASE_							,     end=""" """   )
												a_		      =		back_pointer[x]
						print(SCREAMING_SNAKE_CASE_   )
						sys.exit()




def 	lowerCamelCase_							(       UpperCAmelCase__   ):



						"""simple docstring"""




						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 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__							,     ):



						"""simple docstring"""




						for itera in range(SCREAMING_SNAKE_CASE_   ):
												open_list[itera].remove_element(SCREAMING_SNAKE_CASE_   )
						# print("s", s)
						# print("j", j)
						((a_)      , (a_))		      =		s
						a_		      =		(x - 1, y)
						a_		      =		(x + 1, y)
						a_		      =		(x, y + 1)
						a_		      =		(x, y - 1)

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

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




def 	lowerCamelCase_							(       ):



						"""simple docstring"""




						a_		      =		[]
						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


A_     :       Optional[int]   							={0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

A_     :       str   							=[
    (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),
]
A_     :       List[Any]   							=make_common_ground()


A_     :       Optional[int]   							=blocks_blk
# hyper parameters
A_     :       Dict   							=1
A_     :       Optional[int]   							=1
A_     :       Optional[int]   							=20
A_     :       str   							=3  # one consistent and two other inconsistent

# start and end destination
A_     :       Optional[Any]   							=(0, 0)
A_     :       Optional[int]   							=(n - 1, n - 1)

A_     :       Dict   							=1




def 	lowerCamelCase_							(       UpperCAmelCase__							,     UpperCAmelCase__							,     UpperCAmelCase__   ):



						"""simple docstring"""




						a_		      =		{start: 0, goal: float("""inf"""   )}
						a_		      =		{start: -1, goal: -1}
						a_		      =		[]
						a_		      =		set()

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

						a_		      =		[]
						a_		      =		[]
						while open_list[0].minkey() < float("""inf"""   ):
												for i in range(1							,     SCREAMING_SNAKE_CASE_   ):
																		# 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(SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_   )
																								else:
																														a_      , a_		      =		open_list[i].top_show()
																														visited.add(SCREAMING_SNAKE_CASE_   )
																														expand_state(
																														    SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     )
																														close_list_inad.append(SCREAMING_SNAKE_CASE_   )
																		else:
																								if g_function[goal] <= open_list[0].minkey():
																														if g_function[goal] < float("""inf"""   ):
																																				do_something(SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_   )
																								else:
																														a_		      =		open_list[0].top_show()
																														visited.add(SCREAMING_SNAKE_CASE_   )
																														expand_state(
																														    SCREAMING_SNAKE_CASE_							,     0							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     SCREAMING_SNAKE_CASE_							,     )
																														close_list_anchor.append(SCREAMING_SNAKE_CASE_   )
						print("""No path found to goal"""   )
						print()
						for i in range(n - 1							,     -1							,     -1   ):
												for j in range(SCREAMING_SNAKE_CASE_   ):
																		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 transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_     )		->		str:
			# Construct model
			if openai_config_file == "":
						A_									= OpenAIGPTConfig()
			else:
						A_									= OpenAIGPTConfig.from_json_file(SCREAMING_SNAKE_CASE_     )
			A_									= OpenAIGPTModel(SCREAMING_SNAKE_CASE_     )

			# Load weights from numpy
			load_tf_weights_in_openai_gpt(SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_     )

			# Save pytorch-model
			A_									= pytorch_dump_folder_path + '/' + WEIGHTS_NAME
			A_									= pytorch_dump_folder_path + '/' + CONFIG_NAME
			print(F'Save PyTorch model to {pytorch_weights_dump_path}'     )
			torch.save(model.state_dict()       ,SCREAMING_SNAKE_CASE_     )
			print(F'Save configuration file to {pytorch_config_dump_path}'     )
			with open(SCREAMING_SNAKE_CASE_       ,'w'       ,encoding='utf-8'     ) as f:
						f.write(config.to_json_string()     )


if __name__ == "__main__":
							_SCREAMING_SNAKE_CASE			=						argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    "--openai_checkpoint_folder_path",
							    default=None,
							    type=str,
							    required=True,
							    help="Path to the TensorFlow checkpoint path.",
							)
							parser.add_argument(
							    "--pytorch_dump_folder_path", default=None, type=str, required=True, help="Path to the output PyTorch model."
							)
							parser.add_argument(
							    "--openai_config_file",
							    default="",
							    type=str,
							    help=(
							        "An optional config json file corresponding to the pre-trained OpenAI model. \n"
							        "This specifies the model architecture."
							    ),
							)
							_SCREAMING_SNAKE_CASE			=						parser.parse_args()
							convert_openai_checkpoint_to_pytorch(
							    args.openai_checkpoint_folder_path, args.openai_config_file, args.pytorch_dump_folder_path
							)




