
"""simple docstring"""







import heapq
import sys

import numpy as np

lowerCamelCase__           =	tuple[int, int]




class 				A__ :

		def __init__(   self				):
			__lowerCAmelCase    :		int		    =   []
			__lowerCAmelCase    :		List[str]		    =   set()

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

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

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE				):
			if item not in self.set:
				heapq.heappush(self.elements ,	(priority, item)				)
				self.set.add(_SCREAMING_SNAKE_CASE				)
			else:
				# update
				# print("update", item)
				__lowerCAmelCase    :		Optional[Any]		    =   []
				((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		int		    =   heapq.heappop(self.elements				)
				while x != item:
					temp.append((pri, x)				)
					((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		List[Any]		    =   heapq.heappop(self.elements				)
				temp.append((priority, item)				)
				for pro, xxx in temp:
					heapq.heappush(self.elements ,	(pro, xxx)				)

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
			if item in self.set:
				self.set.remove(_SCREAMING_SNAKE_CASE				)
				__lowerCAmelCase    :		Any		    =   []
				((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		int		    =   heapq.heappop(self.elements				)
				while x != item:
					temp.append((pro, x)				)
					((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		Tuple		    =   heapq.heappop(self.elements				)
				for prito, yyy in temp:
					heapq.heappush(self.elements ,	(prito, yyy)				)

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







		def 							__lowerCamelCase							(   self				):
			((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		Any		    =   heapq.heappop(self.elements				)
			self.set.remove(_SCREAMING_SNAKE_CASE				)
			return (priority, item)



def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase	):
	# euclidean distance
	__lowerCAmelCase    :		Optional[Any]		    =   np.array(_UpperCamelCase	)
	__lowerCAmelCase    :		Union[str, Any]		    =   np.array(_UpperCamelCase	)
	return np.linalg.norm(a - b	)
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase	):
	# integer division by time variable
	return consistent_heuristic(_UpperCamelCase ,						_UpperCamelCase	) // t
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase	):
	# manhattan distance
	return abs(p[0] - goal[0]	) + abs(p[1] - goal[1]	)
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		Union[str, Any]		    =   g_function[start] + Wa * heuristics[i](_UpperCamelCase ,						_UpperCamelCase	)
	return ans
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		Dict		    =   np.chararray((n, n)	)
	for i in range(_UpperCamelCase	):
		for j in range(_UpperCamelCase	):
			__lowerCAmelCase    :		List[Any]		    =   '*'

	for i in range(_UpperCamelCase	):
		for j in range(_UpperCamelCase	):
			if (j, (n - 1) - i) in blocks:
				__lowerCAmelCase    :		Tuple		    =   '#'

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

	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:-'	)
	__lowerCAmelCase    :		Optional[Any]		    =   back_pointer[goal]
	while x != start:
		print(_UpperCamelCase ,						end=' '	)
		__lowerCAmelCase    :		Optional[Any]		    =   back_pointer[x]
	print(_UpperCamelCase	)
	sys.exit()
def 					__lowerCAmelCase       (_UpperCamelCase	):
	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 ,						):
	for itera in range(_UpperCamelCase	):
		open_list[itera].remove_element(_UpperCamelCase	)
	# print("s", s)
	# print("j", j)
	((__lowerCAmelCase)    ,     (__lowerCAmelCase))    :		Dict		    =   s
	__lowerCAmelCase    :		Optional[int]		    =   (x - 1, y)
	__lowerCAmelCase    :		Dict		    =   (x + 1, y)
	__lowerCAmelCase    :		int		    =   (x, y + 1)
	__lowerCAmelCase    :		Optional[int]		    =   (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	)
				__lowerCAmelCase    :		Optional[int]		    =   -1
				__lowerCAmelCase    :		str		    =   float('inf'	)

			if valid(_UpperCamelCase	) and g_function[neighbours] > g_function[s] + 1:
				__lowerCAmelCase    :		str		    =   g_function[s] + 1
				__lowerCAmelCase    :		Tuple		    =   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       ():
	__lowerCAmelCase    :		int		    =   []
	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


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

lowerCamelCase__           =	[
    (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),
]
lowerCamelCase__           =	make_common_ground()


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

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

lowerCamelCase__           =	1
def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		Tuple		    =   {start: 0, goal: float('inf'	)}
	__lowerCAmelCase    :		Any		    =   {start: -1, goal: -1}
	__lowerCAmelCase    :		Optional[Any]		    =   []
	__lowerCAmelCase    :		Optional[int]		    =   set()

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

	__lowerCAmelCase    :		list[int]		    =   []
	__lowerCAmelCase    :		list[int]		    =   []
	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:
					__lowerCAmelCase    ,     __lowerCAmelCase    :		Tuple		    =   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:
					__lowerCAmelCase    :		Optional[int]		    =   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)

"""simple docstring"""







from ....configuration_utils import PretrainedConfig
from ....utils import logging


lowerCamelCase__           =	logging.get_logger(__name__)

lowerCamelCase__           =	{
    """speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json""",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}




class 				A__ (			_lowerCamelCase):
		A_		: Any            =			'mctct'

		def __init__(   self ,	_SCREAMING_SNAKE_CASE=80_65 ,	_SCREAMING_SNAKE_CASE=15_36 ,	_SCREAMING_SNAKE_CASE=36 ,	_SCREAMING_SNAKE_CASE=61_44 ,	_SCREAMING_SNAKE_CASE=4 ,	_SCREAMING_SNAKE_CASE=3_84 ,	_SCREAMING_SNAKE_CASE=9_20 ,	_SCREAMING_SNAKE_CASE=1E-5 ,	_SCREAMING_SNAKE_CASE=0.3 ,	_SCREAMING_SNAKE_CASE="relu" ,	_SCREAMING_SNAKE_CASE=0.02 ,	_SCREAMING_SNAKE_CASE=0.3 ,	_SCREAMING_SNAKE_CASE=0.3 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=0 ,	_SCREAMING_SNAKE_CASE=2 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=0.3 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=(7,) ,	_SCREAMING_SNAKE_CASE=(3,) ,	_SCREAMING_SNAKE_CASE=80 ,	_SCREAMING_SNAKE_CASE=1 ,	_SCREAMING_SNAKE_CASE=None ,	_SCREAMING_SNAKE_CASE="sum" ,	_SCREAMING_SNAKE_CASE=False ,	**_SCREAMING_SNAKE_CASE ,	):
			super().__init__(**_SCREAMING_SNAKE_CASE ,	pad_token_id=_SCREAMING_SNAKE_CASE ,	bos_token_id=_SCREAMING_SNAKE_CASE ,	eos_token_id=_SCREAMING_SNAKE_CASE				)
			__lowerCAmelCase    :		str		    =   vocab_size
			__lowerCAmelCase    :		Any		    =   hidden_size
			__lowerCAmelCase    :		int		    =   num_hidden_layers
			__lowerCAmelCase    :		Any		    =   intermediate_size
			__lowerCAmelCase    :		Optional[int]		    =   num_attention_heads
			__lowerCAmelCase    :		str		    =   attention_head_dim
			__lowerCAmelCase    :		int		    =   max_position_embeddings
			__lowerCAmelCase    :		List[Any]		    =   layer_norm_eps
			__lowerCAmelCase    :		Tuple		    =   layerdrop
			__lowerCAmelCase    :		Dict		    =   hidden_act
			__lowerCAmelCase    :		Dict		    =   initializer_range
			__lowerCAmelCase    :		Any		    =   hidden_dropout_prob
			__lowerCAmelCase    :		Dict		    =   attention_probs_dropout_prob
			__lowerCAmelCase    :		List[str]		    =   pad_token_id
			__lowerCAmelCase    :		Union[str, Any]		    =   bos_token_id
			__lowerCAmelCase    :		int		    =   eos_token_id
			__lowerCAmelCase    :		Optional[int]		    =   conv_glu_dim
			__lowerCAmelCase    :		List[Any]		    =   conv_dropout
			__lowerCAmelCase    :		Tuple		    =   num_conv_layers
			__lowerCAmelCase    :		Tuple		    =   input_feat_per_channel
			__lowerCAmelCase    :		Optional[int]		    =   input_channels
			__lowerCAmelCase    :		str		    =   conv_channels
			__lowerCAmelCase    :		str		    =   ctc_loss_reduction
			__lowerCAmelCase    :		Tuple		    =   ctc_zero_infinity

			# prevents config testing fail with exporting to json
			__lowerCAmelCase    :		List[str]		    =   list(_SCREAMING_SNAKE_CASE				)
			__lowerCAmelCase    :		Dict		    =   list(_SCREAMING_SNAKE_CASE				)

			if len(self.conv_kernel				) != self.num_conv_layers:
				raise ValueError(
				    'Configuration for convolutional module is incorrect. '
				    'It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '
				    f"but is `len(config.conv_kernel) = {len(self.conv_kernel				)}`, "
				    f"`config.num_conv_layers = {self.num_conv_layers}`."				)