



def        UpperCAmelCase_      (							__snake_case  ,		__snake_case		)  ->    Optional[int]:







 """simple docstring"""


 _lowercase							   =(boundary[1] - boundary[0]) / steps
 _lowercase							   =boundary[0]
 _lowercase							   =boundary[1]
 _lowercase							   =make_points(__snake_case  ,		__snake_case  ,		__snake_case		)
 _lowercase							   =0.0
 y += (h / 3.0) * f(__snake_case		)
 _lowercase							   =2
 for i in x_i:
  y += (h / 3) * (4 - 2 * (cnt % 2)) * f(__snake_case		)
  cnt += 1
 y += (h / 3.0) * f(__snake_case		)
 return y
def        UpperCAmelCase_      (							__snake_case  ,		__snake_case  ,		__snake_case		)  ->    Dict:







 """simple docstring"""


 _lowercase							   =a + h
 while x < (b - h):
  yield x
  _lowercase							   =x + h
def        UpperCAmelCase_      (							__snake_case		)  ->    List[Any]:  # enter your function here







 """simple docstring"""


 _lowercase							   =(x - 0) * (x - 0)
 return y
def        UpperCAmelCase_      (							)  ->    Any:







 """simple docstring"""


 _lowercase							   =0.0  # Lower bound of integration
 _lowercase							   =1.0  # Upper bound of integration
 _lowercase							   =10.0  # define number of steps or resolution
 _lowercase							   =[a, b]  # define boundary of integration
 _lowercase							   =method_a(__snake_case  ,		__snake_case		)
 print(F"y = {y}"		)


if __name__ == "__main__":
  main()





import unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
  import tensorflow as tf

  from transformers.activations_tf import get_tf_activation







@require_tf
class    lowerCamelCase__     ( unittest.TestCase):





     def   __A      (self )  ->     Optional[Any]:
      _lowercase							   =tf.constant([-1_0_0, -1.0, -0.1, 0, 0.1, 1.0, 100.0] )
      _lowercase							   =get_tf_activation('''gelu''' )
      _lowercase							   =get_tf_activation('''gelu_10''' )

      _lowercase							   =gelu(UpperCAmelCase )
      _lowercase							   =geluaa(UpperCAmelCase )

      _lowercase							   =tf.where(y_gelu_aa < 10.0	,  1.0	,  0.0 )

      self.assertEqual(tf.math.reduce_max(UpperCAmelCase ).numpy().item()	,  10.0 )
      self.assertTrue(np.allclose(y_gelu * clipped_mask	,  y_gelu_aa * clipped_mask ) )





     def   __A      (self )  ->     Optional[Any]:
      get_tf_activation('''gelu''' )
      get_tf_activation('''gelu_10''' )
      get_tf_activation('''gelu_fast''' )
      get_tf_activation('''gelu_new''' )
      get_tf_activation('''glu''' )
      get_tf_activation('''mish''' )
      get_tf_activation('''quick_gelu''' )
      get_tf_activation('''relu''' )
      get_tf_activation('''sigmoid''' )
      get_tf_activation('''silu''' )
      get_tf_activation('''swish''' )
      get_tf_activation('''tanh''' )
      with self.assertRaises(UpperCAmelCase ):
       get_tf_activation('''bogus''' )
      with self.assertRaises(UpperCAmelCase ):
       get_tf_activation(UpperCAmelCase )

