def train(model, x, y, epoch=30): # TODO
optimizer = optim.SGD(model.parameters(), lr=0.1)
mse_loss = nn.MSELoss()
for i in range(1, epoch + 1):
model.zero_grad()
output = model(x)
loss = mse_loss(output, y)
print(f"train: epoch {i}, loss {loss}")
loss.backward()
optimizer.step()
def test_linear(self):
input = Tensor([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
target = Tensor([[6, 7, 8, 9, 10], [1, 2, 3, 4, 5]])
loss = nn.MSELoss()
output = loss(input, target)
self.assertEqual(output.data.tolist(), 25.)
def test(model, x, y):
output = model(x)
mse_loss = nn.MSELoss()
loss = mse_loss(output, y)
print(f"test: loss {loss}")