






import heapq
import sys

import numpy as np

A        =			tuple[int, int]


class 							__a							:





		'''simple docstring'''



		def __init__(						self       ):
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   []
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   set()


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


		def   __snake_case			(						self       ):
						return len(self.elements       ) == 0


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


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						if item in self.set:
										self.set.remove(UpperCamelCase__       )
										SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   []
										((SCREAMING_SNAKE_CASE_)							,       (SCREAMING_SNAKE_CASE_))   :	List[str]													=   heapq.heappop(self.elements       )
										while x != item:
														temp.append((pro, x)       )
														((SCREAMING_SNAKE_CASE_)							,       (SCREAMING_SNAKE_CASE_))   :	Union[str, Any]													=   heapq.heappop(self.elements       )
										for prito, yyy in temp:
														heapq.heappush(self.elements ,    (prito, yyy)       )


		def   __snake_case			(						self       ):
						return self.elements[0][1]






		def   __snake_case			(						self       ):
						((SCREAMING_SNAKE_CASE_)							,       (SCREAMING_SNAKE_CASE_))   :	Any													=   heapq.heappop(self.elements       )
						self.set.remove(UpperCamelCase__       )
						return (priority, item)






def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		TPos      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Any													=   np.array(lowerCAmelCase__      )
				SCREAMING_SNAKE_CASE_   :	List[str]													=   np.array(lowerCAmelCase__      )
				return np.linalg.norm(a - b      )



def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		TPos      ):





				'''simple docstring'''







				return consistent_heuristic(lowerCAmelCase__    ,    lowerCAmelCase__      ) // t



def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		TPos      ):





				'''simple docstring'''







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



def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		int    ,    lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		dict[TPos, float]      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	List[str]													=   g_function[start] + Wa * heuristics[i](lowerCAmelCase__    ,    lowerCAmelCase__      )
				return ans



def 					_lowerCamelCase(			lowerCAmelCase__				:		Optional[int]    ,    lowerCAmelCase__				:		int    ,    lowerCAmelCase__				:		List[Any]      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   np.chararray((n, n)      )
				for i in range(lowerCAmelCase__      ):
								for j in range(lowerCAmelCase__      ):
												SCREAMING_SNAKE_CASE_   :	str													=   '*'

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

				SCREAMING_SNAKE_CASE_   :	str													=   '-'
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   back_pointer[goal]
				while x != start:
								((SCREAMING_SNAKE_CASE_)							,       (SCREAMING_SNAKE_CASE_))   :	Any													=   x
								# print(x)
								SCREAMING_SNAKE_CASE_   :	int													=   '-'
								SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   back_pointer[x]
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   '-'

				for i in range(lowerCAmelCase__      ):
								for j in range(lowerCAmelCase__      ):
												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:-'      )
				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   back_pointer[goal]
				while x != start:
								print(lowerCAmelCase__    ,    end=' '      )
								SCREAMING_SNAKE_CASE_   :	Tuple													=   back_pointer[x]
				print(lowerCAmelCase__      )
				sys.exit()



def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos      ):





				'''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(			lowerCAmelCase__				:		Optional[Any]    ,    lowerCAmelCase__				:		Optional[Any]    ,    lowerCAmelCase__				:		str    ,    lowerCAmelCase__				:		List[str]    ,    lowerCAmelCase__				:		Union[str, Any]    ,    lowerCAmelCase__				:		List[str]    ,    lowerCAmelCase__				:		Any    ,    lowerCAmelCase__				:		Dict    ,    ):





				'''simple docstring'''







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

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

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



def 					_lowerCamelCase(			):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   []
				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        =			{0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

A        =			[
    (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        =			make_common_ground()


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

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

A        =			1



def 					_lowerCamelCase(			lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		TPos    ,    lowerCAmelCase__				:		int      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Tuple													=   {start: 0, goal: float('inf'      )}
				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   {start: -1, goal: -1}
				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   []
				SCREAMING_SNAKE_CASE_   :	List[Any]													=   set()

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

				SCREAMING_SNAKE_CASE_   :	list[int]													=   []
				SCREAMING_SNAKE_CASE_   :	list[int]													=   []
				while open_list[0].minkey() < float('inf'      ):
								for i in range(1    ,    lowerCAmelCase__      ):
												# 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(lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__      )
																else:
																				SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	Dict													=   open_list[i].top_show()
																				visited.add(lowerCAmelCase__      )
																				expand_state(
																				    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    )
																				close_list_inad.append(lowerCAmelCase__      )
												else:
																if g_function[goal] <= open_list[0].minkey():
																				if g_function[goal] < float('inf'      ):
																								do_something(lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__      )
																else:
																				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   open_list[0].top_show()
																				visited.add(lowerCAmelCase__      )
																				expand_state(
																				    lowerCAmelCase__    ,    0    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__    ,    )
																				close_list_anchor.append(lowerCAmelCase__      )
				print('No path found to goal'      )
				print()
				for i in range(n - 1    ,    -1    ,    -1      ):
								for j in range(lowerCAmelCase__      ):
												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)







import argparse
import os

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
A        =			'src/transformers'
A        =			'docs/source/en/tasks'



def 					_lowerCamelCase(			lowerCAmelCase__				:		Tuple    ,    lowerCAmelCase__				:		Optional[Any]    ,    lowerCAmelCase__				:		Union[str, Any]      ):





				'''simple docstring'''







				with open(lowerCAmelCase__    ,    'r'    ,    encoding='utf-8'    ,    newline='\n'      ) as f:
								SCREAMING_SNAKE_CASE_   :	Optional[int]													=   f.readlines()
				# Find the start prompt.
				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   0
				while not lines[start_index].startswith(lowerCAmelCase__      ):
								start_index += 1
				start_index += 1

				SCREAMING_SNAKE_CASE_   :	int													=   start_index
				while not lines[end_index].startswith(lowerCAmelCase__      ):
								end_index += 1
				end_index -= 1

				while len(lines[start_index]      ) <= 1:
								start_index += 1
				while len(lines[end_index]      ) <= 1:
								end_index -= 1
				end_index += 1
				return "".join(lines[start_index:end_index]      ), start_index, end_index, lines


# This is to make sure the transformers module imported is the one in the repo.
A        =			direct_transformers_import(TRANSFORMERS_PATH)

A        =			{
    'asr.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_CTC_MAPPING_NAMES,
    'audio_classification.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,
    'language_modeling.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,
    'image_classification.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,
    'masked_language_modeling.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_MASKED_LM_MAPPING_NAMES,
    'multiple_choice.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES,
    'object_detection.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,
    'question_answering.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,
    'semantic_segmentation.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,
    'sequence_classification.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,
    'summarization.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    'token_classification.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,
    'translation.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    'video_classification.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES,
    'document_question_answering.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES,
    'monocular_depth_estimation.md': transformers_module.models.auto.modeling_auto.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,
}

# This list contains model types used in some task guides that are not in `CONFIG_MAPPING_NAMES` (therefore not in any
# `MODEL_MAPPING_NAMES` or any `MODEL_FOR_XXX_MAPPING_NAMES`).
A        =			{
    'summarization.md': ('nllb',),
    'translation.md': ('nllb',),
}



def 					_lowerCamelCase(			lowerCAmelCase__				:		Dict      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	List[str]													=   TASK_GUIDE_TO_MODELS[task_guide]
				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(lowerCAmelCase__    ,    set()      )
				SCREAMING_SNAKE_CASE_   :	Optional[int]													=   {
				    code: name
				    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
				    if (code in model_maping_names or code in special_model_types)
				}
				return ", ".join([F'''[{name}](../model_doc/{code})''' for code, name in model_names.items()]      ) + "\n"



def 					_lowerCamelCase(			lowerCAmelCase__				:		List[Any]    ,    lowerCAmelCase__				:		List[str]=False      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	Dict													=   _find_text_in_file(
				    filename=os.path.join(lowerCAmelCase__    ,    lowerCAmelCase__      )    ,    start_prompt='<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->'    ,    end_prompt='<!--End of the generated tip-->'    ,    )

				SCREAMING_SNAKE_CASE_   :	Dict													=   get_model_list_for_task(lowerCAmelCase__      )

				if current_list != new_list:
								if overwrite:
												with open(os.path.join(lowerCAmelCase__    ,    lowerCAmelCase__      )    ,    'w'    ,    encoding='utf-8'    ,    newline='\n'      ) as f:
																f.writelines(lines[:start_index] + [new_list] + lines[end_index:]      )
								else:
												raise ValueError(
												    F'''The list of models that can be used in the {task_guide} guide needs an update. Run `make fix-copies`'''
												    ' to fix this.'      )


if __name__ == "__main__":
				A        =			argparse.ArgumentParser()
				parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
				A        =			parser.parse_args()

				for task_guide in TASK_GUIDE_TO_MODELS.keys():
								check_model_list_for_task(task_guide, args.fix_and_overwrite)