def get_line(data, lr=0.0001):
X = np.array([p[0] for p in data]).reshape(-1, 1)
y = np.array([p[1] for p in data]).reshape(-1, 1)
losses = []
model = Model([Dense(1, 1)], MSE())
for _ in range(50):
h = model.forward(X)
losses.append(model.backward(h, y, lr))
layer = model.layers[0]
return layer.W[0, 0], layer.b[0, 0], losses
from lib import Model
from lib.nodes import Dense, Tanh
from lib.losses import MSE
X = np.array([
[0, 0],
[0, 1],
[1, 0],
[1, 1]
])
y = np.array([0, 1, 1, 0]).reshape(-1, 1)
lr = 0.1
errs = []
for _ in range(20):
model = Model([Dense(2, 4), Tanh(), Dense(4, 1)], MSE())
for _ in range(1000):
pred = model.forward(X)
model.backward(pred, y, lr)
err = np.abs(y - model.forward(X)).sum()
errs.append(err)
plt.hist(errs)
plt.show()