吴裕雄--天生自然TensorFlow2教程：全连接层

out = f(X@W + b)
out = relut(X@W + b)

 

 

import tensorflow as tf

x = tf.random.normal([4, 784])
net = tf.keras.layers.Dense(512)
out = net(x)
out.shape

net.kernel.shape, net.bias.shape
net = tf.keras.layers.Dense(10)
try:
    net.bias
except Exception as e:
    print(e)

net.build(input_shape=(None, 4))
net.kernel.shape, net.bias.shape
net.build(input_shape=(None, 20))
net.kernel.shape, net.bias.shape

net.build(input_shape=(2, 4))
net.kernel

from tensorflow import keras

x = tf.random.normal([2, 3])
model = keras.Sequential([
    keras.layers.Dense(2, activation='relu'),
    keras.layers.Dense(2, activation='relu'),
    keras.layers.Dense(2)
])
model.build(input_shape=[None, 3])
model.summary()
# [w1,b1,w2,b2,w3,b3]
for p in model.trainable_variables:
    print(p.name, p.shape)