在Keras中实现自定义层(RStudio接口)

from tensorflow import keras
from tensorflow.keras import layers

class CustomLayer(layers.Layer):
    def __init__(self, units=32):
        super(CustomLayer, self).__init__()
        self.units = units

    def build(self, input_shape):
        self.w = self.add_weight(
            shape=(input_shape[-1], self.units),
            initializer="random_normal",
            trainable=True,
        )
        self.b = self.add_weight(
            shape=(self.units,),
            initializer="zeros",
            trainable=True,
        )

    def call(self, inputs):
        return tf.matmul(inputs, self.w) + self.b

inputs = keras.Input(shape=(784,))
x = CustomLayer(units=64)(inputs)
outputs = layers.Dense(10, activation="softmax")(x)

model = keras.Model(inputs, outputs)