old_contents: from learntools.core import *
  import tensorflow as tf
  
  
  class Q1A(ThoughtExperiment):
      _solution = ""
  
  
  class Q1B(ThoughtExperiment):
      _solution = ""
  
  Q1 = MultipartProblem(Q1A, Q1B)
  
  class Q2A(ThoughtExperiment):
      _hint = r"Stacking the second layer expanded the receptive field by one neuron on each side, giving $3+1+1=5$ for each dimension. If you expanded by one neuron again, what would you get?"
      _solution = r"The third layer would have a $7 \times 7$ receptive field."
  
  class Q2B(ThoughtExperiment):
      _hint = r"This pooling layer collapses a $2 \times 2$ patch into a single pixel, effectively *doubling* the number of connections along each dimension. "
      _solution = r"Doubling a $7 \times 7$ field produces a $14 \times 14$ field for the final outputs."
  
  Q2 = MultipartProblem(Q2A, Q2B)
  
  
  class Q3(CodingProblem):
      _hint = "You just need a list of numbers, maybe three to five."
      _solution = CS("""
  kernel = tf.constant([0.1, 0.2, 0.3, 0.4])
  """)
      def check(self):
          pass
  
  
  qvars = bind_exercises(globals(), [
          Q1, Q2, Q3,
      ],
      var_format='q_{n}',
  )
  __all__ = list(qvars)
      
  
new_contents: from learntools.core import *
  import tensorflow as tf
  
  
  # Free
  class Q1(CodingProblem):
      _solution = ""
      def check(self):
          pass
  
  class Q2A(ThoughtExperiment):
      _hint = r"Stacking the second layer expanded the receptive field by one neuron on each side, giving $3+1+1=5$ for each dimension. If you expanded by one neuron again, what would you get?"
      _solution = r"The third layer would have a $7 \times 7$ receptive field."
  
  class Q2B(ThoughtExperiment):
      _hint = r"This pooling layer collapses a $2 \times 2$ patch into a single pixel, effectively *doubling* the number of connections along each dimension. "
      _solution = r"Doubling a $7 \times 7$ field produces a $14 \times 14$ field for the final outputs."
  
  Q2 = MultipartProblem(Q2A, Q2B)
  
  
  class Q3(CodingProblem):
      _hint = "You just need a list of numbers, maybe three to five."
      _solution = CS("""
  kernel = tf.constant([0.1, 0.2, 0.3, 0.4])
  """)
      def check(self):
          pass
  
  
  qvars = bind_exercises(globals(), [
          Q1, Q2, Q3,
      ],
      var_format='q_{n}',
  )
  __all__ = list(qvars)
      
  
subject: Change exercise 4 question 1