
import numpy

# List of input, output pairs
UpperCAmelCase__		:     List[str]     			=      (
    ((5, 2, 3), 15),
    ((6, 5, 9), 25),
    ((11, 12, 13), 41),
    ((1, 1, 1), 8),
    ((11, 12, 13), 41),
)
UpperCAmelCase__		:     int     			=      (((515, 22, 13), 555), ((61, 35, 49), 150))
UpperCAmelCase__		:     str     			=      [2, 4, 1, 5]
UpperCAmelCase__		:     Optional[int]     			=      len(train_data)
UpperCAmelCase__		:     Any     			=      0.009






def   lowerCamelCase__							(					a		,		a="train"      )      ->   Optional[Any]:
   return calculate_hypothesis_value(a		,		a      ) - output(
       a		,		a      )






def   lowerCamelCase__							(					a      )      ->   Optional[Any]:
   _A:  Optional[Any]					=       0
   for i in range(len(a      ) - 1      ):
      hyp_val += data_input_tuple[i] * parameter_vector[i + 1]
   hyp_val += parameter_vector[0]
   return hyp_val






def   lowerCamelCase__							(					a		,		a      )      ->   Union[str, Any]:
   if data_set == "train":
      return train_data[example_no][1]
   elif data_set == "test":
      return test_data[example_no][1]
   return None






def   lowerCamelCase__							(					a		,		a      )      ->   Any:
   if data_set == "train":
      return _hypothesis_value(train_data[example_no][0]      )
   elif data_set == "test":
      return _hypothesis_value(test_data[example_no][0]      )
   return None






def   lowerCamelCase__							(					a		,		a=m      )      ->   Dict:
   _A:  Dict					=       0
   for i in range(a      ):
      if index == -1:
         summation_value += _error(a      )
      else:
         summation_value += _error(a      ) * train_data[i][0][index]
   return summation_value






def   lowerCamelCase__							(					a      )      ->   Union[str, Any]:
   _A:  List[str]					=       summation_of_cost_derivative(a		,		a      ) / m
   return cost_derivative_value






def   lowerCamelCase__							(					)      ->   int:
   global parameter_vector
   # Tune these values to set a tolerance value for predicted output
   _A:  List[str]					=       0.00_0002
   _A:  Optional[int]					=       0
   _A:  Union[str, Any]					=       0
   while True:
      j += 1
      _A:  int					=       [0, 0, 0, 0]
      for i in range(0		,		len(a      )      ):
         _A:  Optional[Any]					=       get_cost_derivative(i - 1      )
         _A:  str					=       (
             parameter_vector[i] - LEARNING_RATE * cost_derivative
         )
      if numpy.allclose(
          a		,		a		,		atol=a		,		rtol=a		,		):
         break
      _A:  Union[str, Any]					=       temp_parameter_vector
   print(('''Number of iterations:''', j)      )






def   lowerCamelCase__							(					)      ->   int:
   for i in range(len(a      )      ):
      print(('''Actual output value:''', output(a		,		'''test'''      ))      )
      print(('''Hypothesis output:''', calculate_hypothesis_value(a		,		'''test'''      ))      )


if __name__ == "__main__":
   run_gradient_descent()
   print('\nTesting gradient descent for a linear hypothesis function.\n')
   test_gradient_descent()





from __future__ import annotations






class UpperCAmelCase   :





   '''simple docstring'''


   def __init__(					self     :							Optional[Any]			,			lowerCAmelCase_     :							int     ):

      """simple docstring"""
      _A:  List[str]					=       data
      _A:  Node | None					=       None
      _A:  Node | None					=       None






def   lowerCamelCase__							(					a      )      ->   None:  # In Order traversal of the tree
   if tree:
      display(tree.left      )
      print(tree.data      )
      display(tree.right      )






def   lowerCamelCase__							(					a      )      ->   int:
   return 1 + max(depth_of_tree(tree.left      )		,		depth_of_tree(tree.right      )      ) if tree else 0






def   lowerCamelCase__							(					a      )      ->   bool:
   if not tree:
      return True
   if tree.left and tree.right:
      return is_full_binary_tree(tree.left      ) and is_full_binary_tree(tree.right      )
   else:
      return not tree.left and not tree.right






def   lowerCamelCase__							(					)      ->   None:  # Main function for testing.
   _A:  Optional[int]					=       Node(1      )
   _A:  int					=       Node(2      )
   _A:  str					=       Node(3      )
   _A:  Union[str, Any]					=       Node(4      )
   _A:  Dict					=       Node(5      )
   _A:  int					=       Node(6      )
   _A:  Optional[Any]					=       Node(7      )
   _A:  List[str]					=       Node(8      )
   _A:  int					=       Node(9      )

   print(is_full_binary_tree(a      )      )
   print(depth_of_tree(a      )      )
   print('''Tree is: '''      )
   display(a      )


if __name__ == "__main__":
   main()



