text: """
  # !/usr/bin/env python
  # -*- coding: utf-8 -*-
  @Time        : 2022/3/26 10:48
  @File        : and_perceptron.py
  """
  
  
  import pandas as pd
  
  # TODO: Set weight1, weight2, and bias
  weight1 = 1.0 # 1.0
  weight2 = 1.0 # 1.0
  bias = -0.5 # -0.5
  
  
  # DON'T CHANGE ANYTHING BELOW
  # Inputs and outputs
  test_inputs = [(0, 0), (0, 1), (1, 0), (1, 1)]
  correct_outputs = [False, True, True, True]
  outputs = []
  
  # Generate and check output
  for test_input, correct_output in zip(test_inputs, correct_outputs):
      linear_combination = weight1 * test_input[0] + weight2 * test_input[1] + bias
      output = int(linear_combination >= 0)
      is_correct_string = 'Yes' if output == correct_output else 'No'
      outputs.append([test_input[0], test_input[1], linear_combination, output, is_correct_string])
  
  # Print output
  num_wrong = len([output[4] for output in outputs if output[4] == 'No'])
  output_frame = pd.DataFrame(outputs, columns=['Input 1', '  Input 2', '  Linear Combination', '  Activation Output', '  Is Correct'])
  if not num_wrong:
      print('Nice!  You got it all correct.\n')
  else:
      print('You got {} wrong.  Keep trying!\n'.format(num_wrong))
  print(output_frame.to_string(index=False))
  