


import unittest

import numpy as np

from transformers import is_flax_available
from transformers.testing_utils import require_flax

from ..test_modeling_flax_common import ids_tensor


if is_flax_available():
					import jax
					import jax.numpy as jnp

					from transformers.generation import (
					    FlaxForcedBOSTokenLogitsProcessor,
					    FlaxForcedEOSTokenLogitsProcessor,
					    FlaxLogitsProcessorList,
					    FlaxMinLengthLogitsProcessor,
					    FlaxTemperatureLogitsWarper,
					    FlaxTopKLogitsWarper,
					    FlaxTopPLogitsWarper,
					)







@require_flax
class 				lowercase       ( unittest.TestCase    ):




				def 					a							(      self   ,     snake_case   ,     snake_case ):
											snake_case_           =					jnp.ones((batch_size, length) ) / length
											return scores




				def 					a							(      self ):
											snake_case_           =					None
											snake_case_           =					20

											snake_case_           =					self._get_uniform_logits(batch_size=2   ,     length=UpperCamelCase__ )

											# tweak scores to not be uniform anymore
											snake_case_           =					scores.at[1, 5].set((1 / length) + 0.1 )  # peak, 1st batch
											snake_case_           =					scores.at[1, 10].set((1 / length) - 0.4 )  # valley, 1st batch

											# compute softmax
											snake_case_           =					jax.nn.softmax(UpperCamelCase__   ,     axis=-1 )

											snake_case_           =					FlaxTemperatureLogitsWarper(temperature=0.5 )
											snake_case_           =					FlaxTemperatureLogitsWarper(temperature=1.3 )

											snake_case_           =					jax.nn.softmax(temp_dist_warper_sharper(UpperCamelCase__   ,     scores.copy()   ,     cur_len=UpperCamelCase__ )   ,     axis=-1 )
											snake_case_           =					jax.nn.softmax(temp_dist_warper_smoother(UpperCamelCase__   ,     scores.copy()   ,     cur_len=UpperCamelCase__ )   ,     axis=-1 )

											# uniform distribution stays uniform
											self.assertTrue(jnp.allclose(probs[0, :]   ,     warped_prob_sharp[0, :]   ,     atol=1e-3 ) )
											self.assertTrue(jnp.allclose(probs[0, :]   ,     warped_prob_smooth[0, :]   ,     atol=1e-3 ) )

											# sharp peaks get higher, valleys get lower
											self.assertLess(probs[1, :].max()   ,     warped_prob_sharp[1, :].max() )
											self.assertGreater(probs[1, :].min()   ,     warped_prob_sharp[1, :].min() )

											# smooth peaks get lower, valleys get higher
											self.assertGreater(probs[1, :].max()   ,     warped_prob_smooth[1, :].max() )
											self.assertLess(probs[1, :].min()   ,     warped_prob_smooth[1, :].min() )




				def 					a							(      self ):
											snake_case_           =					None
											snake_case_           =					10
											snake_case_           =					2

											# create ramp distribution
											snake_case_           =					np.broadcast_to(np.arange(UpperCamelCase__ )[None, :]   ,     (batch_size, vocab_size) ).copy()
											snake_case_           =					ramp_logits[1:, : vocab_size // 2] + vocab_size

											snake_case_           =					FlaxTopKLogitsWarper(3 )

											snake_case_           =					top_k_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )

											# check that correct tokens are filtered
											self.assertListEqual(jnp.isinf(scores[0] ).tolist()   ,     7 * [True] + 3 * [False] )
											self.assertListEqual(jnp.isinf(scores[1] ).tolist()   ,     2 * [True] + 3 * [False] + 5 * [True] )

											# check special case
											snake_case_           =					5
											snake_case_           =					FlaxTopKLogitsWarper(top_k=1   ,     filter_value=0.0   ,     min_tokens_to_keep=3 )

											snake_case_           =					np.broadcast_to(np.arange(UpperCamelCase__ )[None, :]   ,     (batch_size, length) ).copy()
											snake_case_           =					top_k_warp_safety_check(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )

											# min_tokens overwrites k: 3 tokens are kept => 2 tokens are nullified
											self.assertListEqual((scores == 0.0).sum(axis=-1 ).tolist()   ,     [2, 2] )




				def 					a							(      self ):
											snake_case_           =					None
											snake_case_           =					10
											snake_case_           =					2

											# create distribution and take log (inverse to Softmax as taken in TopPLogitsWarper)
											snake_case_           =					np.log(np.array([[0.3, 0.1, 0.1, 0.5], [0.15, 0.3, 0.3, 0.25]] ) )

											snake_case_           =					FlaxTopPLogitsWarper(0.8 )
											snake_case_           =					np.exp(top_p_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ ) )

											# dist should be filtered to keep min num values so that sum is >= top_p
											# exp (-inf) => 0
											snake_case_           =					np.array([[0.3, 0.0, 0.0, 0.5], [0.0, 0.3, 0.3, 0.25]] )
											self.assertTrue(np.allclose(UpperCamelCase__   ,     UpperCamelCase__   ,     atol=1e-3 ) )

											# check edge cases with negative and extreme logits
											snake_case_           =					np.broadcast_to(np.arange(UpperCamelCase__ )[None, :]   ,     (batch_size, vocab_size) ).copy() - (
											    vocab_size // 2
											)

											# make ramp_logits more extreme
											snake_case_           =					ramp_logits[1] * 100.0

											# make sure at least 2 tokens are kept
											snake_case_           =					FlaxTopPLogitsWarper(0.9   ,     min_tokens_to_keep=2   ,     filter_value=0.0 )
											snake_case_           =					top_p_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )

											# first batch should keep three tokens, second batch would keep only 1, but due to `min_tokens_to_keep=2` keeps 2.
											self.assertListEqual((filtered_dist != 0.0).sum(axis=-1 ).tolist()   ,     [3, 2] )




				def 					a							(      self ):
											snake_case_           =					20
											snake_case_           =					4
											snake_case_           =					0

											snake_case_           =					FlaxMinLengthLogitsProcessor(min_length=10   ,     eos_token_id=UpperCamelCase__ )

											# check that min length is applied at length 5
											snake_case_           =					ids_tensor((batch_size, 20)   ,     vocab_size=20 )
											snake_case_           =					5
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					min_dist_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertListEqual(scores_before_min_length[:, eos_token_id].tolist()   ,     4 * [-float('inf' )] )

											# check that min length is not applied anymore at length 15
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					15
											snake_case_           =					min_dist_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertFalse(jnp.isinf(UpperCamelCase__ ).any() )




				def 					a							(      self ):
											snake_case_           =					20
											snake_case_           =					4
											snake_case_           =					0

											snake_case_           =					FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase__ )

											# check that all scores are -inf except the bos_token_id score
											snake_case_           =					ids_tensor((batch_size, 1)   ,     vocab_size=20 )
											snake_case_           =					1
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					logits_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertTrue(jnp.isneginf(scores[:, bos_token_id + 1 :] ).all() )
											self.assertListEqual(scores[:, bos_token_id].tolist()   ,     4 * [0] )  # score for bos_token_id shold be zero

											# check that bos_token_id is not forced if current length is greater than 1
											snake_case_           =					3
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					logits_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertFalse(jnp.isinf(UpperCamelCase__ ).any() )




				def 					a							(      self ):
											snake_case_           =					20
											snake_case_           =					4
											snake_case_           =					0
											snake_case_           =					5

											snake_case_           =					FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase__   ,     eos_token_id=UpperCamelCase__ )

											# check that all scores are -inf except the eos_token_id when max_length is reached
											snake_case_           =					ids_tensor((batch_size, 4)   ,     vocab_size=20 )
											snake_case_           =					4
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					logits_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertTrue(jnp.isneginf(scores[:, eos_token_id + 1 :] ).all() )
											self.assertListEqual(scores[:, eos_token_id].tolist()   ,     4 * [0] )  # score for eos_token_id should be zero

											# check that eos_token_id is not forced if max_length is not reached
											snake_case_           =					3
											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					logits_processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											self.assertFalse(jnp.isinf(UpperCamelCase__ ).any() )




				def 					a							(      self ):
											snake_case_           =					4
											snake_case_           =					10
											snake_case_           =					15
											snake_case_           =					2
											snake_case_           =					1
											snake_case_           =					15

											# dummy input_ids and scores
											snake_case_           =					ids_tensor((batch_size, sequence_length)   ,     UpperCamelCase__ )
											snake_case_           =					input_ids.copy()

											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					scores.copy()

											# instantiate all dist processors
											snake_case_           =					FlaxTemperatureLogitsWarper(temperature=0.5 )
											snake_case_           =					FlaxTopKLogitsWarper(3 )
											snake_case_           =					FlaxTopPLogitsWarper(0.8 )

											# instantiate all logits processors
											snake_case_           =					FlaxMinLengthLogitsProcessor(min_length=10   ,     eos_token_id=UpperCamelCase__ )
											snake_case_           =					FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase__ )
											snake_case_           =					FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase__   ,     eos_token_id=UpperCamelCase__ )

											snake_case_           =					10

											# no processor list
											snake_case_           =					temp_dist_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											snake_case_           =					top_k_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											snake_case_           =					top_p_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											snake_case_           =					min_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											snake_case_           =					bos_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
											snake_case_           =					eos_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )

											# with processor list
											snake_case_           =					FlaxLogitsProcessorList(
											    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
											snake_case_           =					processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )

											# scores should be equal
											self.assertTrue(jnp.allclose(UpperCamelCase__   ,     UpperCamelCase__   ,     atol=1e-3 ) )

											# input_ids should never be changed
											self.assertListEqual(input_ids.tolist()   ,     input_ids_comp.tolist() )




				def 					a							(      self ):
											snake_case_           =					4
											snake_case_           =					10
											snake_case_           =					15
											snake_case_           =					2
											snake_case_           =					1
											snake_case_           =					15

											# dummy input_ids and scores
											snake_case_           =					ids_tensor((batch_size, sequence_length)   ,     UpperCamelCase__ )
											snake_case_           =					input_ids.copy()

											snake_case_           =					self._get_uniform_logits(UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					scores.copy()

											# instantiate all dist processors
											snake_case_           =					FlaxTemperatureLogitsWarper(temperature=0.5 )
											snake_case_           =					FlaxTopKLogitsWarper(3 )
											snake_case_           =					FlaxTopPLogitsWarper(0.8 )

											# instantiate all logits processors
											snake_case_           =					FlaxMinLengthLogitsProcessor(min_length=10   ,     eos_token_id=UpperCamelCase__ )
											snake_case_           =					FlaxForcedBOSTokenLogitsProcessor(bos_token_id=UpperCamelCase__ )
											snake_case_           =					FlaxForcedEOSTokenLogitsProcessor(max_length=UpperCamelCase__   ,     eos_token_id=UpperCamelCase__ )

											snake_case_           =					10

											# no processor list
											def run_no_processor_list(snake_case   ,     snake_case   ,     snake_case ):
																		snake_case_           =					temp_dist_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		snake_case_           =					top_k_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		snake_case_           =					top_p_warp(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		snake_case_           =					min_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		snake_case_           =					bos_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		snake_case_           =					eos_dist_proc(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		return scores

											# with processor list
											def run_processor_list(snake_case   ,     snake_case   ,     snake_case ):
																		snake_case_           =					FlaxLogitsProcessorList(
																		    [temp_dist_warp, top_k_warp, top_p_warp, min_dist_proc, bos_dist_proc, eos_dist_proc] )
																		snake_case_           =					processor(UpperCamelCase__   ,     UpperCamelCase__   ,     cur_len=UpperCamelCase__ )
																		return scores

											snake_case_           =					jax.jit(UpperCamelCase__ )
											snake_case_           =					jax.jit(UpperCamelCase__ )

											snake_case_           =					jitted_run_no_processor_list(UpperCamelCase__   ,     UpperCamelCase__   ,     UpperCamelCase__ )
											snake_case_           =					jitted_run_processor_list(UpperCamelCase__   ,     UpperCamelCase__   ,     UpperCamelCase__ )

											# scores should be equal
											self.assertTrue(jnp.allclose(UpperCamelCase__   ,     UpperCamelCase__   ,     atol=1e-3 ) )

											# input_ids should never be changed
											self.assertListEqual(input_ids.tolist()   ,     input_ids_comp.tolist() )







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)




