我正在尝试在浏览器中实现一个深度学习模型，这需要移植一些自定义层，其中一个是即时层归一化。下面是一段应该能工作的代码，但它有点旧。我遇到了这个错误：

Uncaught (in promise) ReferenceError: initializer is not definedat InstantLayerNormalization.build

<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs/dist/tf.min.js"> </script><script>class InstantLayerNormalization extends tf.layers.Layer{    static className = 'InstantLayerNormalization';    epsilon = 1e-7     gamma;    beta;    constructor(config)     {        super(config);    }    getConfig()     {        const config = super.getConfig();        return config;    }        build(input_shape)    {        let shape = tf.tensor(input_shape);        // initialize gamma        self.gamma = self.add_weight(shape=shape,                                      initializer='ones',                                      trainable=true,                                      name='gamma')        // initialize beta        self.beta = self.add_weight(shape=shape,                            initializer='zeros',                            trainable=true,                            name='beta')    }            call(inputs){        mean = tf.math.reduce_mean(inputs, axis=[-1], keepdims=True)        variance = tf.math.reduce_mean(tf.math.square(inputs - mean), axis=[-1], keepdims=True)        std = tf.math.sqrt(variance + self.epsilon)        outputs = (inputs - mean) / std        outputs = outputs * self.gamma        outputs = outputs + self.beta        return outputs    }    static get className() {        console.log(className);       return className;    }}tf.serialization.registerClass(InstantLayerNormalization);</script>

回答：

继承类tf.layers.Layer的方法没有被正确调用。

• Python中的self在JavaScript中是this
• add_weight在JavaScript中应为addWeight
• 这里是addWeight方法的签名。请注意，在JavaScript中，函数参数的解构赋值没有variable=value的格式

// 而不是这样self.gamma = self.add_weight(shape=shape, initializer='ones', trainable=true, name='gamma')// 应该是这样this.gamma = this.addWeight('gamma', shape, undefined, 'ones', undefined, true)