dl_fp_activation.py

import numpy as np

print("Enter the two values for input layers")

print('a = ')
a = int(input())
# 2
print('b = ')
b = int(input())

weights = {
    'node_0': np.array([2, 4]),
    'node_1': np.array([[4, -5]]),
    'output_node': np.array([2, 7])
}

input_data = np.array([a, b])


def relu(input):
    # Rectified Linear Activation
    output = max(input, 0)
    return(output)


node_0_input = (input_data * weights['node_0']).sum()
node_0_output = relu(node_0_input)

node_1_input = (input_data * weights['node_1']).sum()
node_1_output = relu(node_1_input)

hidden_layer_outputs = np.array([node_0_output, node_1_output])

model_output = (hidden_layer_outputs * weights['output_node']).sum()

print(model_output)