






import numpy

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

def     snake_case   (UpperCAmelCase__      ,       UpperCAmelCase__="train"    )			->							Optional[int]:
  return calculate_hypothesis_value(UpperCAmelCase__      ,       UpperCAmelCase__    ) - output(
      UpperCAmelCase__      ,       UpperCAmelCase__    )

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

def     snake_case   (UpperCAmelCase__      ,       UpperCAmelCase__    )			->							List[Any]:
  if data_set == "train":
    return train_data[example_no][1]
  elif data_set == "test":
    return test_data[example_no][1]
  return None

def     snake_case   (UpperCAmelCase__      ,       UpperCAmelCase__    )			->							Optional[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     snake_case   (UpperCAmelCase__      ,       UpperCAmelCase__=m    )			->							Optional[Any]:
  UpperCamelCase_:   Any        =							0
  for i in range(UpperCAmelCase__    ):
    if index == -1:
      summation_value += _error(UpperCAmelCase__    )
    else:
      summation_value += _error(UpperCAmelCase__    ) * train_data[i][0][index]
  return summation_value

def     snake_case   (UpperCAmelCase__    )			->							Optional[Any]:
  UpperCamelCase_:   Optional[int]        =							summation_of_cost_derivative(UpperCAmelCase__      ,       UpperCAmelCase__    ) / m
  return cost_derivative_value

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

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


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


'''simple docstring'''

import os

# Precomputes a list of the 100 first triangular numbers
SCREAMING_SNAKE_CASE							:				List[Any]     	=			[int(0.5 * n * (n + 1)) for n in range(1, 101)]




def 							_UpperCamelCase				(   )      -> List[Any]:
							SCREAMING_SNAKE_CASE_				=				os.path.dirname(os.path.realpath(lowerCAmelCase__   )   )
							SCREAMING_SNAKE_CASE_				=				os.path.join(lowerCAmelCase__		,'words.txt'   )

							SCREAMING_SNAKE_CASE_				=				''
							with open(lowerCAmelCase__   ) as f:
														SCREAMING_SNAKE_CASE_				=				f.readline()

							SCREAMING_SNAKE_CASE_				=				[word.strip('"'   ) for word in words.strip('\r\n'   ).split(','   )]
							SCREAMING_SNAKE_CASE_				=				[
							    word
							    for word in [sum(ord(lowerCAmelCase__   ) - 64 for x in word   ) for word in words]
							    if word in TRIANGULAR_NUMBERS
							]
							return len(lowerCAmelCase__   )


if __name__ == "__main__":
							print(solution())





