code: import numpy as np
  
  def relu(input):
      '''Define your relu activation function here'''
      # Calculate the value for the output of the relu function: output
      output = max(input, 0)
      
      # Return the value just calculated
      return(output)
  
  input_data = np.array([3,5])
  
  # Calculate node 0 value: node_0_output
  node_0_input = (input_data * weights['node_0']).sum()
  node_0_output = relu(node_0_input)
  
  # Calculate node 1 value: node_1_output
  node_1_input = (input_data * weights['node_1']).sum()
  node_1_output = relu(node_1_input)
  
  # Put node values into array: hidden_layer_outputs
  hidden_layer_outputs = np.array([node_0_output, node_1_output])
  
  # Calculate model output (do not apply relu)
  model_output = (hidden_layer_outputs * weights['output']).sum()
  
  # Print model output
  print(model_output)
  
apis: numpy.array