





import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad


class        __SCREAMING_SNAKE_CASE      (			unittest.TestCase ):







       def 						__lowerCamelCase   (				self					:     Optional[Any]      )       ->Optional[Any]:
          lowerCamelCase__       :						Dict        =							1_0







       def 						__lowerCamelCase   (				self					:     Any      )       ->Union[str, Any]:
          lowerCamelCase__       :						str        =							[1, 2, 3, 4]
          lowerCamelCase__       :						Optional[int]        =							[1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
          self.assertEqual(truncate_or_pad(A		, self.block_size		, 0      )		, A      )







       def 						__lowerCamelCase   (				self					:     List[Any]      )       ->Union[str, Any]:
          lowerCamelCase__       :						Optional[int]        =							[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
          lowerCamelCase__       :						Optional[int]        =							[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
          self.assertEqual(truncate_or_pad(A		, self.block_size		, 0      )		, A      )







       def 						__lowerCamelCase   (				self					:     Dict      )       ->Dict:
          lowerCamelCase__       :						Optional[Any]        =							[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0, 1_1, 1_2, 1_3]
          lowerCamelCase__       :						int        =							[1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
          self.assertEqual(truncate_or_pad(A		, self.block_size		, 0      )		, A      )







       def 						__lowerCamelCase   (				self					:     List[Any]      )       ->Tuple:
          lowerCamelCase__       :						Union[str, Any]        =							'''It was the year of Our Lord one thousand seven hundred and
        seventy-five.\n\nSpiritual revelations were conceded to England at that
        favoured period, as at this.'''
          lowerCamelCase__       ,							lowerCamelCase__       :						Union[str, Any]        =							process_story(A      )
          self.assertEqual(A		, []      )







       def 						__lowerCamelCase   (				self					:     Union[str, Any]      )       ->Any:
          lowerCamelCase__       :						str        =							''''''
          lowerCamelCase__       ,							lowerCamelCase__       :						Dict        =							process_story(A      )
          self.assertEqual(A		, []      )
          self.assertEqual(A		, []      )







       def 						__lowerCamelCase   (				self					:     str      )       ->str:
          lowerCamelCase__       :						Dict        =							(
              '''It was the year of Our Lord one thousand seven hundred and '''
              '''seventy-five\n\nSpiritual revelations were conceded to England '''
              '''at that favoured period, as at this.\n@highlight\n\nIt was the best of times'''
          )
          lowerCamelCase__       ,							lowerCamelCase__       :						Optional[int]        =							process_story(A      )

          lowerCamelCase__       :						Optional[int]        =							[
              '''It was the year of Our Lord one thousand seven hundred and seventy-five.''',
              '''Spiritual revelations were conceded to England at that favoured period, as at this.''',
          ]
          self.assertEqual(A		, A      )

          lowerCamelCase__       :						Optional[int]        =							['''It was the best of times.''']
          self.assertEqual(A		, A      )







       def 						__lowerCamelCase   (				self					:     int      )       ->Tuple:
          lowerCamelCase__       :						int        =							torch.tensor([1, 2, 3, 4]      )
          lowerCamelCase__       :						Tuple        =							torch.tensor([1, 1, 1, 1]      )
          np.testing.assert_array_equal(build_mask(A		, 0      ).numpy()		, expected.numpy()      )







       def 						__lowerCamelCase   (				self					:     int      )       ->Optional[Any]:
          lowerCamelCase__       :						Any        =							torch.tensor([1, 2, 3, 4, 2_3, 2_3, 2_3]      )
          lowerCamelCase__       :						Union[str, Any]        =							torch.tensor([1, 1, 1, 1, 0, 0, 0]      )
          np.testing.assert_array_equal(build_mask(A		, 2_3      ).numpy()		, expected.numpy()      )







       def 						__lowerCamelCase   (				self					:     List[Any]      )       ->Any:
          lowerCamelCase__       :						Any        =							torch.tensor([8, 2, 3, 4, 1, 1, 1]      )
          lowerCamelCase__       :						Optional[int]        =							torch.tensor([1, 1, 1, 1, 0, 0, 0]      )
          np.testing.assert_array_equal(build_mask(A		, 1      ).numpy()		, expected.numpy()      )







       def 						__lowerCamelCase   (				self					:     Optional[Any]      )       ->Optional[int]:
          lowerCamelCase__       :						Optional[int]        =							1_0_1
          lowerCamelCase__       :						int        =							torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 1_0_1, 5, 6], [1, 1_0_1, 3, 4, 1_0_1, 6]]      )
          lowerCamelCase__       :						int        =							torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]      )

          lowerCamelCase__       :						Optional[int]        =							compute_token_type_ids(A		, A      )
          np.testing.assert_array_equal(A		, A      )










import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
       # Create universe of discourse in Python using linspace ()
       _A :   Optional[int]  			=  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).
       _A :   Any  			=  [0, 25, 50]
       _A :   Dict  			=  [25, 50, 75]
       _A :   Any  			=  fuzz.membership.trimf(X, abca)
       _A :   List[Any]  			=  fuzz.membership.trimf(X, abca)

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



