Putting things together

train.py

def train(X, Y, nn_architecture, epochs, learning_rate):
    params_values = init_layers(nn_architecture, 2)
    cost_history = []
    accuracy_history = []
    
    for i in range(epochs):
        Y_hat, cashe = full_forward_propagation(X, params_values, nn_architecture)
        cost = get_cost_value(Y_hat, Y)
        cost_history.append(cost)
        accuracy = get_accuracy_value(Y_hat, Y)
        accuracy_history.append(accuracy)
        
        grads_values = full_backward_propagation(Y_hat, Y, cashe, params_values, nn_architecture)
        params_values = update(params_values, grads_values, nn_architecture, learning_rate)
        
    return params_values, cost_history, accuracy_history