https://d2l.ai/chapter_builders-guide/model-construction.html
Exercises 2:
class MySequential(tf.keras.Model):
def __init__(self, *args):
super().__init__()
self.net1 = []
self.net2 = []
for block in args[0]:
self.net1.append(block)
for block in args[1]:
self.net1.append(block)
def net1add(self, block):
self.net1.append(block)
def net1add(self, block):
self.net1.append(block)
def call(self, inputs):
net1_prob:tf.Tensor = inputs
net2_prob:tf.Tensor = inputs
for block in self.net1:
net1_prob = block(net1_prob)
for block in self.net2:
net2_prob = block(net1_prob)
return net1_prob, net2_prob
net = MySequential(
[tf.keras.layers.Dense(64, activation=tf.nn.relu),
tf.keras.layers.Dense(32, activation=tf.nn.relu),
tf.keras.layers.Dense(10)],
[tf.keras.layers.Dense(64, activation=tf.nn.relu),
tf.keras.layers.Dense(10)]
)
net1, net2 = net(X)
print(net1)
print(net2)