def main(max_iter):
# prepare
npdl.utils.random.set_seed(1234)
# data
digits = load_digits()
X_train = digits.data
X_train /= np.max(X_train)
Y_train = digits.target
n_classes = np.unique(Y_train).size
# model
model = npdl.model.Model()
model.add(npdl.layers.Dense(n_out=500, n_in=64, activation=npdl.activations.ReLU()))
model.add(npdl.layers.Dense(n_out=n_classes, activation=npdl.activations.Softmax()))
model.compile(loss=npdl.objectives.SCCE(), optimizer=npdl.optimizers.SGD(lr=0.005))
# train
model.fit(X_train, npdl.utils.data.one_hot(Y_train), max_iter=max_iter, validation_split=0.1)
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