def test_equal_layers(self): """ Should return True, as the net is equal to itself. """ net = Net(NetNames.CONV, DatasetNames.MNIST, plan_conv=[2, 'M'], plan_fc=[2]) self.assertIs(net.equal_layers(other=net), True)
def test_equal_layers_unequal_types(self): """ Should return False, as two layers have unequal activation functions. """ net0 = Net(NetNames.LENET, DatasetNames.MNIST, plan_conv=[2, 'M'], plan_fc=[2]) net1 = Net(NetNames.CONV, DatasetNames.MNIST, plan_conv=[2, 'M'], plan_fc=[2]) self.assertIs(net0.equal_layers(other=net1), False)
def test_equal_layers_unequal_weights(self): """ Should return False, as two layers contain unequal 'weight'-attributes. """ torch.manual_seed(0) net0 = Net(NetNames.CONV, DatasetNames.MNIST, plan_conv=[2, 'M'], plan_fc=[2]) torch.manual_seed(1) net1 = Net(NetNames.CONV, DatasetNames.MNIST, plan_conv=[2, 'M'], plan_fc=[2]) self.assertIs(net0.equal_layers(other=net1), False)