fc148e1a29e3d7893c438f701b8422225c95fc66,examples/classification.py,MNISTGenerator,create,#MNISTGenerator#,66

Before Change

        ops.describe("custom_generator")

        net = gan.inputs.x
        net = ops.reshape(net, [gan.batch_size(), -1])
        net = ops.linear(net, end_features)
        net = ops.lookup("tanh")(net)
        self.fy = net
        self.sample = net
        return net
    def layer(self, name):
        return getattr(self, name)

After Change

class MNISTGenerator(BaseGenerator):
    def create(self):
        self.linear = torch.nn.Linear(28*28*1, 1024)
        self.relu = torch.nn.ReLU()
        self.linear2 = torch.nn.Linear(1024, 10)
        self.sigmoid = torch.nn.Sigmoid()
    def forward(self, input, context={}):
        net = input

Instances