

import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score

import datasets


_UpperCAmelCase	:     Union[str, Any]		       = """\
    @inproceedings{kakwani2020indicnlpsuite,
    title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages}},
    author={Divyanshu Kakwani and Anoop Kunchukuttan and Satish Golla and Gokul N.C. and Avik Bhattacharyya and Mitesh M. Khapra and Pratyush Kumar},
    year={2020},
    booktitle={Findings of EMNLP},
}
"""

_UpperCAmelCase	:     Union[str, Any]		       = """\
    IndicGLUE is a natural language understanding benchmark for Indian languages. It contains a wide
    variety of tasks and covers 11 major Indian languages - as, bn, gu, hi, kn, ml, mr, or, pa, ta, te.
"""

_UpperCAmelCase	:     Tuple		       = """
Compute IndicGLUE evaluation metric associated to each IndicGLUE dataset.
Args:
    predictions: list of predictions to score (as int64),
        except for 'cvit-mkb-clsr' where each prediction is a vector (of float32).
    references: list of ground truth labels corresponding to the predictions (as int64),
        except for 'cvit-mkb-clsr' where each reference is a vector (of float32).
Returns: depending on the IndicGLUE subset, one or several of:
    \"accuracy\": Accuracy
    \"f1\": F1 score
    \"precision\": Precision@10
Examples:

    >>> indic_glue_metric = datasets.load_metric('indic_glue', 'wnli')  # 'wnli' or any of [\"copa\", \"sna\", \"csqa\", \"wstp\", \"inltkh\", \"bbca\", \"iitp-mr\", \"iitp-pr\", \"actsa-sc\", \"md\"]
    >>> references = [0, 1]
    >>> predictions = [0, 1]
    >>> results = indic_glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'accuracy': 1.0}

    >>> indic_glue_metric = datasets.load_metric('indic_glue', 'wiki-ner')
    >>> references = [0, 1]
    >>> predictions = [0, 1]
    >>> results = indic_glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'accuracy': 1.0, 'f1': 1.0}

    >>> indic_glue_metric = datasets.load_metric('indic_glue', 'cvit-mkb-clsr')
    >>> references = [[0.5, 0.5, 0.5], [0.1, 0.2, 0.3]]
    >>> predictions = [[0.5, 0.5, 0.5], [0.1, 0.2, 0.3]]
    >>> results = indic_glue_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'precision@10': 1.0}

"""





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							return float((preds == labels).mean()   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					simple_accuracy(UpperCamelCase__     ,							UpperCamelCase__   )
							snake_case_           =					float(fa_score(y_true=UpperCamelCase__     ,							y_pred=UpperCamelCase__   )   )
							return {
							    "accuracy": acc,
							    "f1": fa,
							}





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					np.array(UpperCamelCase__   )
							snake_case_           =					np.array(UpperCamelCase__   )
							snake_case_           =					en_sentvecs.shape[0]

							# mean centering
							snake_case_           =					en_sentvecs - np.mean(UpperCamelCase__     ,							axis=0   )
							snake_case_           =					in_sentvecs - np.mean(UpperCamelCase__     ,							axis=0   )

							snake_case_           =					cdist(UpperCamelCase__     ,							UpperCamelCase__     ,							'cosine'   )
							snake_case_           =					np.array(range(UpperCamelCase__   )   )
							snake_case_           =					sim.argsort(axis=1   )[:, :10]
							snake_case_           =					np.any(preds == actual[:, None]     ,							axis=1   )
							return float(matches.mean()   )







@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION			,						_KWARGS_DESCRIPTION    )
class 				lowercase       ( datasets.Metric    ):




				def 					a							(      self ):
											if self.config_name not in [
											    "wnli",
											    "copa",
											    "sna",
											    "csqa",
											    "wstp",
											    "inltkh",
											    "bbca",
											    "cvit-mkb-clsr",
											    "iitp-mr",
											    "iitp-pr",
											    "actsa-sc",
											    "md",
											    "wiki-ner",
											]:
																		raise KeyError(
																		    'You should supply a configuration name selected in '
																		    '["wnli", "copa", "sna", "csqa", "wstp", "inltkh", "bbca", '
																		    '"cvit-mkb-clsr", "iitp-mr", "iitp-pr", "actsa-sc", "md", '
																		    '"wiki-ner"]' )
											return datasets.MetricInfo(
											    description=_DESCRIPTION   ,     citation=_CITATION   ,     inputs_description=_KWARGS_DESCRIPTION   ,     features=datasets.Features(
											        {
											            'predictions': datasets.Value('int64' )
											            if self.config_name != 'cvit-mkb-clsr'
											            else datasets.Sequence(datasets.Value('float32' ) ),
											            'references': datasets.Value('int64' )
											            if self.config_name != 'cvit-mkb-clsr'
											            else datasets.Sequence(datasets.Value('float32' ) ),
											        } )   ,     codebase_urls=[]   ,     reference_urls=[]   ,     format='numpy' if self.config_name != 'cvit-mkb-clsr' else None   ,     )




				def 					a							(      self   ,     snake_case   ,     snake_case ):
											if self.config_name == "cvit-mkb-clsr":
																		return {"precision@10": precision_at_aa(snake_case   ,     snake_case )}
											elif self.config_name in ["wiki-ner"]:
																		return acc_and_fa(snake_case   ,     snake_case )
											elif self.config_name in [
											    "wnli",
											    "copa",
											    "sna",
											    "csqa",
											    "wstp",
											    "inltkh",
											    "bbca",
											    "iitp-mr",
											    "iitp-pr",
											    "actsa-sc",
											    "md",
											]:
																		return {"accuracy": simple_accuracy(snake_case   ,     snake_case )}
											else:
																		raise KeyError(
																		    'You should supply a configuration name selected in '
																		    '["wnli", "copa", "sna", "csqa", "wstp", "inltkh", "bbca", '
																		    '"cvit-mkb-clsr", "iitp-mr", "iitp-pr", "actsa-sc", "md", '
																		    '"wiki-ner"]' )







import heapq
import sys

import numpy as np

_UpperCAmelCase	:     str		       = tuple[int, int]







class 				lowercase       :




				def __init__(      self ):
											snake_case_           =					[]
											snake_case_           =					set()




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




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




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




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




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




				def 					a							(      self ):
											((snake_case_)       ,					(snake_case_))           =					heapq.heappop(self.elements )
											self.set.remove(snake_case )
											return (priority, item)





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					np.array(UpperCamelCase__   )
							snake_case_           =					np.array(UpperCamelCase__   )
							return np.linalg.norm(a - b   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							return consistent_heuristic(UpperCamelCase__     ,							UpperCamelCase__   ) // 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'''






							snake_case_           =					g_function[start] + Wa * heuristics[i](UpperCamelCase__     ,							UpperCamelCase__   )
							return ans





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					np.chararray((n, n)   )
							for i in range(UpperCamelCase__   ):
														for j in range(UpperCamelCase__   ):
																					snake_case_           =					'*'

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

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

							for i in range(UpperCamelCase__   ):
														for j in range(UpperCamelCase__   ):
																					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:-'   )
							snake_case_           =					back_pointer[goal]
							while x != start:
														print(UpperCamelCase__     ,							end=' '   )
														snake_case_           =					back_pointer[x]
							print(UpperCamelCase__   )
							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(UpperCamelCase__   ):
														open_list[itera].remove_element(UpperCamelCase__   )
							# print("s", s)
							# print("j", j)
							((snake_case_)       ,					(snake_case_))           =					s
							snake_case_           =					(x - 1, y)
							snake_case_           =					(x + 1, y)
							snake_case_           =					(x, y + 1)
							snake_case_           =					(x, y - 1)

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

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





def       __lowerCamelCase			(				):







							'''simple docstring'''






							snake_case_           =					[]
							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	:     Tuple		       = {0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

_UpperCAmelCase	:     List[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),
]
_UpperCAmelCase	:     Tuple		       = make_common_ground()


_UpperCAmelCase	:     Dict		       = blocks_blk
# hyper parameters
_UpperCAmelCase	:     int		       = 1
_UpperCAmelCase	:     int		       = 1
_UpperCAmelCase	:     Tuple		       = 20
_UpperCAmelCase	:     Tuple		       = 3  # one consistent and two other inconsistent

# start and end destination
_UpperCAmelCase	:     Tuple		       = (0, 0)
_UpperCAmelCase	:     List[Any]		       = (n - 1, n - 1)

_UpperCAmelCase	:     Optional[int]		       = 1





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






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

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

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




