Question

给定使用tf.sequential()创建的模型，是否可以使用tf.model()获取图层并使用它们创建另一个模型？

const model = tf.sequential();
model.add(tf.layers.dense({units: 32, inputShape: [50]}));
model.add(tf.layers.dense({units: 4}));

// get the layers
 layers
// use the layers to create another model
tf.model({layers})

Answer 1

要获取使用tf.sequential创建的模型的各层，需要使用模型的属性layers

const model = tf.sequential();

// first layer
model.add(tf.layers.dense({units: 32, inputShape: [50]}));
// second layer
model.add(tf.layers.dense({units: 4}));

// get all the layers of the model
const layers = model.layers

// second model
const model2 = tf.model({
  inputs: layers[0].input, 
  outputs: layers[1].output
})

model2.predict(tf.randomNormal([1, 50])).print()

<html>
  <head>
    <!-- Load TensorFlow.js -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.12.0"> </script>
  </head>

  <body>
  </body>
</html>

一个人也可以使用apply方法

const model = tf.sequential();

// first layer
model.add(tf.layers.dense({units: 32, inputShape: [50]}));
// second layer
model.add(tf.layers.dense({units: 4}));

var input = tf.randomNormal([1, 50])
var layers = model.layers
for (var i=0; i < layers.length; i++){
    var layer = layers[i]
    var output = layer.apply(input)
    input = output
    output.print()
}

<html>
  <head>
    <!-- Load TensorFlow.js -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.12.0"> </script>
  </head>

  <body>
  </body>
</html>

从一个模型中获取图层并将其分配给另一个模型

1 个答案: