


import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
			# Create universe of discourse in Python using linspace ()
			__snake_case            =   np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)

			# Create two fuzzy sets by defining any membership function
			# (trapmf(), gbellmf(), gaussmf(), etc).
			__snake_case            =   [0, 25, 50]
			__snake_case            =   [25, 50, 75]
			__snake_case            =   fuzz.membership.trimf(X, abca)
			__snake_case            =   fuzz.membership.trimf(X, abca)

			# Compute the different operations using inbuilt functions.
			__snake_case            =   np.ones(75)
			__snake_case            =   np.zeros((75,))
			# 1. Union = max(µA(x), µB(x))
			__snake_case            =   fuzz.fuzzy_or(X, young, X, middle_aged)[1]
			# 2. Intersection = min(µA(x), µB(x))
			__snake_case            =   fuzz.fuzzy_and(X, young, X, middle_aged)[1]
			# 3. Complement (A) = (1- min(µA(x))
			__snake_case            =   fuzz.fuzzy_not(young)
			# 4. Difference (A/B) = min(µA(x),(1- µB(x)))
			__snake_case            =   fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
			# 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
			__snake_case            =   young + middle_aged - (young * middle_aged)
			# 6. Algebraic Product = (µA(x) * µB(x))
			__snake_case            =   young * middle_aged
			# 7. Bounded Sum = min[1,(µA(x), µB(x))]
			__snake_case            =   fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
			# 8. Bounded difference = min[0,(µA(x), µB(x))]
			__snake_case            =   fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]

			# max-min composition
			# max-product composition

			# Plot each set A, set B and each operation result using plot() and subplot().
			from matplotlib import pyplot as plt

			plt.figure()

			plt.subplot(4, 3, 1)
			plt.plot(X, young)
			plt.title("Young")
			plt.grid(True)

			plt.subplot(4, 3, 2)
			plt.plot(X, middle_aged)
			plt.title("Middle aged")
			plt.grid(True)

			plt.subplot(4, 3, 3)
			plt.plot(X, union)
			plt.title("union")
			plt.grid(True)

			plt.subplot(4, 3, 4)
			plt.plot(X, intersection)
			plt.title("intersection")
			plt.grid(True)

			plt.subplot(4, 3, 5)
			plt.plot(X, complement_a)
			plt.title("complement_a")
			plt.grid(True)

			plt.subplot(4, 3, 6)
			plt.plot(X, difference)
			plt.title("difference a/b")
			plt.grid(True)

			plt.subplot(4, 3, 7)
			plt.plot(X, alg_sum)
			plt.title("alg_sum")
			plt.grid(True)

			plt.subplot(4, 3, 8)
			plt.plot(X, alg_product)
			plt.title("alg_product")
			plt.grid(True)

			plt.subplot(4, 3, 9)
			plt.plot(X, bdd_sum)
			plt.title("bdd_sum")
			plt.grid(True)

			plt.subplot(4, 3, 10)
			plt.plot(X, bdd_difference)
			plt.title("bdd_difference")
			plt.grid(True)

			plt.subplots_adjust(hspace=0.5)
			plt.show()








import torch

from transformers import AutoModel




class    UpperCAmelCase					(       torch.nn.Module    ):




			def __init__(						self							:		int       ,       __magic_name__							:		List[Any]="sayef/fsner-bert-base-uncased"						):







						"""simple docstring"""







						super(__magic_name__       ,       self						).__init__()

						UpperCamelCase         =					AutoModel.from_pretrained(__magic_name__       ,       return_dict=__magic_name__						)
						UpperCamelCase         =					torch.nn.CosineSimilarity(3       ,       1e-08						)
						UpperCamelCase         =					torch.nn.Softmax(dim=1						)




			def   lowerCamelCase_					(						self							:		Optional[int]       ,       **__magic_name__							:		List[Any]						):







						"""simple docstring"""







						return self.bert(**__magic_name__						).last_hidden_state




			def   lowerCamelCase_					(						self							:		Tuple       ,       __magic_name__							:		int						):







						"""simple docstring"""







						return token_embeddings.sum(2       ,       keepdim=__magic_name__						)




			def   lowerCamelCase_					(						self							:		Optional[Any]       ,       __magic_name__							:		List[str]       ,       __magic_name__							:		Union[str, Any]       ,       __magic_name__							:		Optional[Any]=1						):







						"""simple docstring"""







						return self.softmax(T * self.cos(__magic_name__       ,       __magic_name__						)						)





			def   lowerCamelCase_					(						self							:		Union[str, Any]       ,       __magic_name__							:		List[Any]       ,       __magic_name__							:		List[str]						):







						"""simple docstring"""







						UpperCamelCase         =					W_supports["""sizes"""].tolist()
						UpperCamelCase         =					W_supports["""start_token_id"""].item()
						UpperCamelCase         =					W_supports["""end_token_id"""].item()

						del W_supports["sizes"]
						del W_supports["start_token_id"]
						del W_supports["end_token_id"]

						UpperCamelCase         =					self.BERT(**__magic_name__						)
						UpperCamelCase         =					self.BERT(**__magic_name__						)

						UpperCamelCase         =					None
						UpperCamelCase         =					None

						UpperCamelCase         =					W_supports["""input_ids"""] == start_token_id
						UpperCamelCase         =					W_supports["""input_ids"""] == end_token_id

						for i, size in enumerate(__magic_name__						):
									if i == 0:
												UpperCamelCase         =					0
									else:
												UpperCamelCase         =					support_sizes[i - 1]

									UpperCamelCase         =					S[s : s + size][start_token_masks[s : s + size]]
									UpperCamelCase         =					S[s : s + size][end_token_masks[s : s + size]]

									UpperCamelCase         =					torch.matmul(q[i]       ,       s_start.T						).sum(1						).softmax(0						)
									UpperCamelCase         =					torch.matmul(q[i]       ,       s_end.T						).sum(1						).softmax(0						)

									if p_starts is not None:
												UpperCamelCase         =					torch.vstack((p_starts, p_start)						)
												UpperCamelCase         =					torch.vstack((p_ends, p_end)						)
									else:
												UpperCamelCase         =					p_start
												UpperCamelCase         =					p_end

						return p_starts, p_ends




