test.py

# making an instance of a neuron
neuron = Perceptron(input_size = 3, learning_rate = 0.05)
#training samples
X_train = np.array([[1,0,0,1,1,0,1,0],
                    [0,1,0,1,0,1,1,0],
                    [0,0,1,0,1,1,1,0]] ) 
#training label
y_train =  np.array([  1,      0,      0,      1,    1,    0,      1,    0])
#test sample
X_test = np.array([[1],
                   [1],
                   [0]])
#test label
y_test =np.array( [   1   ])
#number of epochs i.e. number of times we train on the whole dataset
n_epochs = 30
#training loop
for epoch in range(n_epochs):
    for i in range(X_train.shape[1]):
        x = X_train[:,i]          #slice only one column
        y = y_train[i]          #slice only one column
        neuron.train(x,y)
#test loop
for i in range(X_test.shape[1]):
    y_hat = neuron.forward(X_test[:,i])
    y_true = y_test[i]
    print(f"Test: \npredicted y: {y_hat.squeeze()}, true y: {y_true}")