import numpy as np
from cnnlearn.layers.fullyconnected import FC
from cnnlearn.model import SequentialModel
from cnnlearn.cost import mse
from cnnlearn.activation import relu, sigmoid, tanh

n_iters = 100
n_samples = 10
n_features = 40
lr = 0.05

model = SequentialModel(mse)
model.append(FC(3, activation=relu), FC(2, activation=relu), FC(2, activation=relu))

x = np.random.rand(n_samples, n_features)
y = np.random.randint(0, 1, size=(n_samples, 1))

model.train(x, y, n_iters, lr)
a = np.array([1, 2, 3])
b = np.array([0.5, 0.5, 0.5])

print(a / b)