






"""simple docstring"""
from typing import List, Union

import numpy as np

from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline


_lowerCAmelCase         =							logging.get_logger(__name__)



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		if isinstance(lowerCAmelCase_     ,     lowerCAmelCase_							):
			A_		:						List[Any]	    =   [label.strip() for label in labels.split(""","""							) if label.strip()]
		return labels





	def __call__(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_     ,     lowerCAmelCase_							):
		if len(lowerCAmelCase_							) == 0 or len(lowerCAmelCase_							) == 0:
			raise ValueError("""You must include at least one label and at least one sequence."""							)
		if hypothesis_template.format(labels[0]							) == hypothesis_template:
			raise ValueError(
			    (
			        """The provided hypothesis_template \"{}\" was not able to be formatted with the target labels. """
			        """Make sure the passed template includes formatting syntax such as {{}} where the label should go."""
			    ).format(lowerCAmelCase_							)							)

		if isinstance(lowerCAmelCase_     ,     lowerCAmelCase_							):
			A_		:						Optional[Any]	    =   [sequences]

		A_		:						Union[str, Any]	    =   []
		for sequence in sequences:
			sequence_pairs.extend([[sequence, hypothesis_template.format(lowerCAmelCase_							)] for label in labels]							)

		return sequence_pairs, sequences






@add_end_docstrings(_SCREAMING_SNAKE_CASE						)
class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	def __init__(self     ,     lowerCAmelCase_=ZeroShotClassificationArgumentHandler()     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_							):
		A_		:						Optional[Any]	    =   args_parser
		super().__init__(*lowerCAmelCase_     ,     **lowerCAmelCase_							)
		if self.entailment_id == -1:
			logger.warning(
			    """Failed to determine 'entailment' label id from the label2id mapping in the model config. Setting to """
			    """-1. Define a descriptive label2id mapping in the model config to ensure correct outputs."""							)





	@property
	def    lowerCamelCase(self							):
		for label, ind in self.model.config.labelaid.items():
			if label.lower().startswith("""entail"""							):
				return ind
		return -1





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_=True     ,     lowerCAmelCase_=True     ,     lowerCAmelCase_=TruncationStrategy.ONLY_FIRST     ,     **lowerCAmelCase_							):
		A_		:						List[str]	    =   self.framework
		if self.tokenizer.pad_token is None:
			# Override for tokenizers not supporting padding
			logger.error(
			    """Tokenizer was not supporting padding necessary for zero-shot, attempting to use """
			    """ `pad_token=eos_token`"""							)
			A_		:						List[Any]	    =   self.tokenizer.eos_token
		try:
			A_		:						List[Any]	    =   self.tokenizer(
			    lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_     ,     return_tensors=lowerCAmelCase_     ,     padding=lowerCAmelCase_     ,     truncation=lowerCAmelCase_     ,     )
		except Exception as e:
			if "too short" in str(lowerCAmelCase_							):
				# tokenizers might yell that we want to truncate
				# to a value that is not even reached by the input.
				# In that case we don't want to truncate.
				# It seems there's not a really better way to catch that
				# exception.

				A_		:						Union[str, Any]	    =   self.tokenizer(
				    lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_     ,     return_tensors=lowerCAmelCase_     ,     padding=lowerCAmelCase_     ,     truncation=TruncationStrategy.DO_NOT_TRUNCATE     ,     )
			else:
				raise e

		return inputs





	def    lowerCamelCase(self     ,     **lowerCAmelCase_							):
		if kwargs.get("""multi_class"""     ,     lowerCAmelCase_							) is not None:
			A_		:						List[Any]	    =   kwargs["""multi_class"""]
			logger.warning(
			    """The `multi_class` argument has been deprecated and renamed to `multi_label`. """
			    """`multi_class` will be removed in a future version of Transformers."""							)
		A_		:						str	    =   {}
		if "candidate_labels" in kwargs:
			A_		:						List[str]	    =   self._args_parser._parse_labels(kwargs["""candidate_labels"""]							)
		if "hypothesis_template" in kwargs:
			A_		:						List[str]	    =   kwargs["""hypothesis_template"""]

		A_		:						Optional[int]	    =   {}
		if "multi_label" in kwargs:
			A_		:						Optional[int]	    =   kwargs["""multi_label"""]
		return preprocess_params, {}, postprocess_params





	def __call__(self     ,     lowerCAmelCase_     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_     ,     ):
		if len(lowerCAmelCase_							) == 0:
			pass
		elif len(lowerCAmelCase_							) == 1 and "candidate_labels" not in kwargs:
			A_		:						Optional[int]	    =   args[0]
		else:
			raise ValueError(f"""Unable to understand extra arguments {args}"""							)

		return super().__call__(lowerCAmelCase_     ,     **lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_="This example is {}."							):
		A_    ,     A_		:						List[str]	    =   self._args_parser(lowerCAmelCase_     ,     lowerCAmelCase_     ,     lowerCAmelCase_							)

		for i, (candidate_label, sequence_pair) in enumerate(zip(lowerCAmelCase_     ,     lowerCAmelCase_							)							):
			A_		:						int	    =   self._parse_and_tokenize([sequence_pair]							)

			yield {
			    "candidate_label": candidate_label,
			    "sequence": sequences[0],
			    "is_last": i == len(lowerCAmelCase_							) - 1,
			    **model_input,
			}





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		A_		:						List[Any]	    =   inputs["""candidate_label"""]
		A_		:						int	    =   inputs["""sequence"""]
		A_		:						Optional[Any]	    =   {k: inputs[k] for k in self.tokenizer.model_input_names}
		A_		:						List[str]	    =   self.model(**lowerCAmelCase_							)

		A_		:						Optional[int]	    =   {
		    """candidate_label""": candidate_label,
		    """sequence""": sequence,
		    """is_last""": inputs["""is_last"""],
		    **outputs,
		}
		return model_outputs





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_=False							):
		A_		:						Optional[Any]	    =   [outputs["""candidate_label"""] for outputs in model_outputs]
		A_		:						List[Any]	    =   [outputs["""sequence"""] for outputs in model_outputs]
		A_		:						Any	    =   np.concatenate([output["""logits"""].numpy() for output in model_outputs]							)
		A_		:						Tuple	    =   logits.shape[0]
		A_		:						List[str]	    =   len(lowerCAmelCase_							)
		A_		:						Optional[Any]	    =   N // n
		A_		:						List[str]	    =   logits.reshape((num_sequences, n, -1)							)

		if multi_label or len(lowerCAmelCase_							) == 1:
			# softmax over the entailment vs. contradiction dim for each label independently
			A_		:						Any	    =   self.entailment_id
			A_		:						Any	    =   -1 if entailment_id == 0 else 0
			A_		:						str	    =   reshaped_outputs[..., [contradiction_id, entailment_id]]
			A_		:						List[str]	    =   np.exp(lowerCAmelCase_							) / np.exp(lowerCAmelCase_							).sum(-1     ,     keepdims=lowerCAmelCase_							)
			A_		:						Tuple	    =   scores[..., 1]
		else:
			# softmax the "entailment" logits over all candidate labels
			A_		:						Dict	    =   reshaped_outputs[..., self.entailment_id]
			A_		:						Optional[int]	    =   np.exp(lowerCAmelCase_							) / np.exp(lowerCAmelCase_							).sum(-1     ,     keepdims=lowerCAmelCase_							)

		A_		:						List[Any]	    =   list(reversed(scores[0].argsort()							)							)
		return {
		    "sequence": sequences[0],
		    "labels": [candidate_labels[i] for i in top_inds],
		    "scores": scores[0, top_inds].tolist(),
		}









"""simple docstring"""
import heapq
import sys

import numpy as np

_lowerCAmelCase         =							tuple[int, int]



class      SCREAMING_SNAKE_CASE  :





	"""simple docstring"""




	def __init__(self							):
		A_		:						Any	    =   []
		A_		:						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     ,     lowerCAmelCase_     ,     lowerCAmelCase_							):
		if item not in self.set:
			heapq.heappush(self.elements     ,     (priority, item)							)
			self.set.add(lowerCAmelCase_							)
		else:
			# update
			# print("update", item)
			A_		:						Union[str, Any]	    =   []
			((A_)    ,     (A_))		:						Union[str, Any]	    =   heapq.heappop(self.elements							)
			while x != item:
				temp.append((pri, x)							)
				((A_)    ,     (A_))		:						Any	    =   heapq.heappop(self.elements							)
			temp.append((priority, item)							)
			for pro, xxx in temp:
				heapq.heappush(self.elements     ,     (pro, xxx)							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		if item in self.set:
			self.set.remove(lowerCAmelCase_							)
			A_		:						int	    =   []
			((A_)    ,     (A_))		:						Union[str, Any]	    =   heapq.heappop(self.elements							)
			while x != item:
				temp.append((pro, x)							)
				((A_)    ,     (A_))		:						List[Any]	    =   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							):
		((A_)    ,     (A_))		:						Optional[Any]	    =   heapq.heappop(self.elements							)
		self.set.remove(lowerCAmelCase_							)
		return (priority, item)






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__					):
	# euclidean distance
	A_		:						Optional[Any]	    =   np.array(snake_case__					)
	A_		:						List[str]	    =   np.array(snake_case__					)
	return np.linalg.norm(a - b					)






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__					):
	# integer division by time variable
	return consistent_heuristic(snake_case__   ,   snake_case__					) // t






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__					):
	# manhattan distance
	return abs(p[0] - goal[0]					) + abs(p[1] - goal[1]					)






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__					):
	A_		:						Optional[int]	    =   g_function[start] + Wa * heuristics[i](snake_case__   ,   snake_case__					)
	return ans






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__   ,   snake_case__					):
	A_		:						Tuple	    =   np.chararray((n, n)					)
	for i in range(snake_case__					):
		for j in range(snake_case__					):
			A_		:						List[Any]	    =   """*"""

	for i in range(snake_case__					):
		for j in range(snake_case__					):
			if (j, (n - 1) - i) in blocks:
				A_		:						Optional[Any]	    =   """#"""

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

	for i in range(snake_case__					):
		for j in range(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_		:						List[str]	    =   back_pointer[goal]
	while x != start:
		print(snake_case__   ,   end=""" """					)
		A_		:						Optional[int]	    =   back_pointer[x]
	print(snake_case__					)
	sys.exit()






def 			__UpperCamelCase	(		snake_case__					):
	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 			__UpperCamelCase	(		snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   ):
	for itera in range(snake_case__					):
		open_list[itera].remove_element(snake_case__					)
	# print("s", s)
	# print("j", j)
	((A_)    ,     (A_))		:						Any	    =   s
	A_		:						int	    =   (x - 1, y)
	A_		:						List[str]	    =   (x + 1, y)
	A_		:						Union[str, Any]	    =   (x, y + 1)
	A_		:						Any	    =   (x, y - 1)

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

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






def 			__UpperCamelCase	(		):
	A_		:						str	    =   []
	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 			__UpperCamelCase	(		snake_case__   ,   snake_case__   ,   snake_case__					):
	A_		:						Tuple	    =   {start: 0, goal: float("""inf"""					)}
	A_		:						List[str]	    =   {start: -1, goal: -1}
	A_		:						str	    =   []
	A_		:						int	    =   set()

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

	A_		:						list[int]	    =   []
	A_		:						list[int]	    =   []
	while open_list[0].minkey() < float("""inf"""					):
		for i in range(1   ,   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(snake_case__   ,   snake_case__   ,   snake_case__					)
				else:
					A_    ,     A_		:						Optional[Any]	    =   open_list[i].top_show()
					visited.add(snake_case__					)
					expand_state(
					    snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   )
					close_list_inad.append(snake_case__					)
			else:
				if g_function[goal] <= open_list[0].minkey():
					if g_function[goal] < float("""inf"""					):
						do_something(snake_case__   ,   snake_case__   ,   snake_case__					)
				else:
					A_		:						int	    =   open_list[0].top_show()
					visited.add(snake_case__					)
					expand_state(
					    snake_case__   ,   0   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   snake_case__   ,   )
					close_list_anchor.append(snake_case__					)
	print("""No path found to goal"""					)
	print()
	for i in range(n - 1   ,   -1   ,   -1					):
		for j in range(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)

