要查看TensorFlow模型的参数,可以使用model.summary()
方法来打印出模型的结构和参数数量。示例代码如下:
import tensorflow as tf
# 创建模型
model = tf.keras.Sequential([
tf.keras.layers.Dense(64, activation='relu', input_shape=(784,)),
tf.keras.layers.Dense(64, activation='relu'),
tf.keras.layers.Dense(10)
])
# 打印模型的参数
model.summary()
运行以上代码,会输出类似如下的结果:
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 64) 50240
_________________________________________________________________
dense_1 (Dense) (None, 64) 4160
_________________________________________________________________
dense_2 (Dense) (None, 10) 650
=================================================================
Total params: 55,050
Trainable params: 55,050
Non-trainable params: 0
_________________________________________________________________
以上结果中,Param #
列显示了每个层的参数数量,Total params
列显示了总的参数数量。