




import numpy as np

from transformers import Pipeline







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[Any]      )     ->       Any:





				"""simple docstring"""


				__lowerCamelCase		       =    np.max(UpperCamelCase__ ,     axis=-1 ,     keepdims=UpperCamelCase__      )
				__lowerCamelCase		       =    np.exp(outputs - maxes      )
				return shifted_exp / shifted_exp.sum(axis=-1 ,     keepdims=UpperCamelCase__      )







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			def       lowercase_    (      self			,						**lowerCamelCase__							)    ->      Optional[int]:



							'''simple docstring'''
							__lowerCamelCase		       =    {}
							if "second_text" in kwargs:
											__lowerCamelCase		       =    kwargs['second_text']
							return preprocess_kwargs, {}, {}


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__=None							)    ->      Tuple:



							'''simple docstring'''
							return self.tokenizer(lowerCamelCase__			,						text_pair=lowerCamelCase__			,						return_tensors=self.framework							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Union[str, Any]:



							'''simple docstring'''
							return self.model(**lowerCamelCase__							)






			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    model_outputs.logits[0].numpy()
							__lowerCamelCase		       =    softmax(lowerCamelCase__							)

							__lowerCamelCase		       =    np.argmax(lowerCamelCase__							)
							__lowerCamelCase		       =    self.model.config.idalabel[best_class]
							__lowerCamelCase		       =    probabilities[best_class].item()
							__lowerCamelCase		       =    logits.tolist()
							return {"label": label, "score": score, "logits": logits}




"""simple docstring"""





from collections import defaultdict






class     _UpperCAmelCase:



		def __init__(					self				,		__a				,		__a)       ->       Union[str, Any]:






							'''simple docstring'''
							_UpperCamelCase							 =  total  # total no of tasks (N)

							# DP table will have a dimension of (2^M)*N
							# initially all values are set to -1
							_UpperCamelCase							 =  [
							    [-1 for i in range(total + 1)] for j in range(2 ** len(__a))
							]

							_UpperCamelCase							 =  defaultdict(__a)  # stores the list of persons for each task

							# final_mask is used to check if all persons are included by setting all bits
							# to 1
							_UpperCamelCase							 =  (1 << len(__a)) - 1



		def 						UpperCAmelCase							(					self				,		__a				,		__a)       ->       Dict:






							'''simple docstring'''
							# if mask == self.finalmask all persons are distributed tasks, return 1
							if mask == self.final_mask:
												return 1

							# if not everyone gets the task and no more tasks are available, return 0
							if task_no > self.total_tasks:
												return 0

							# if case already considered
							if self.dp[mask][task_no] != -1:
												return self.dp[mask][task_no]

							# Number of ways when we don't this task in the arrangement
							_UpperCamelCase							 =  self.count_ways_until(__a				,		task_no + 1)

							# now assign the tasks one by one to all possible persons and recursively
							# assign for the remaining tasks.
							if task_no in self.task:
												for p in self.task[task_no]:
																	# if p is already given a task
																	if mask & (1 << p):
																						continue

																	# assign this task to p and change the mask value. And recursively
																	# assign tasks with the new mask value.
																	total_ways_util += self.count_ways_until(mask | (1 << p)				,		task_no + 1)

        # save the value.
							_UpperCamelCase							 =  total_ways_util

							return self.dp[mask][task_no]




		def 						UpperCAmelCase							(					self				,		__a)       ->       int:






							'''simple docstring'''
							# Store the list of persons for each task
							for i in range(len(__a)):
												for j in task_performed[i]:
																	self.task[j].append(__a)

        # call the function to fill the DP table, final answer is stored in dp[0][1]
							return self.count_ways_until(0				,		1)


if __name__ == "__main__":
				_a														=		5  # total no of tasks (the value of N)

				# the list of tasks that can be done by M persons.
				_a														=		[[1, 3, 4], [1, 2, 5], [3, 4]]
				print(
				    AssignmentUsingBitmask(task_performed, total_tasks).count_no_of_ways(
				        task_performed
				    )
				)






