iris.py 文件源码

def learn(dataset: DataSet, n_iter: int = 10000) -> IrisChain:
    model = IrisChain()
    optimizer = optimizers.Adam()
    optimizer.setup(model)

    x_train = dataset.train.drop('class', axis=1).values
    y_train = to_hot_vector(dataset.train['class']).values

    for i in range(n_iter):
        model.cleargrads()
        x = Variable(x_train)
        y = Variable(y_train)
        loss = model(x, y)
        loss.backward()
        optimizer.update()

    return model