在keras/tf中制作自定义多热嵌入层

import tensorflow as tf

class MultiHotEmbedding(tf.keras.layers.Layer):
    def __init__(self, input_dim, output_dim, **kwargs):
        super(MultiHotEmbedding, self).__init__(**kwargs)
        self.input_dim = input_dim
        self.output_dim = output_dim

    def build(self, input_shape):
        self.embedding = self.add_weight(shape=(self.input_dim, self.output_dim),
                                         initializer='uniform',
                                         trainable=True)

    def call(self, inputs):
        return tf.reduce_sum(tf.nn.embedding_lookup(self.embedding, inputs), axis=1)

import tensorflow as tf

# 假设有一个输入特征为[1, 3, 5, 7, 9]的样本
input_features = tf.constant([[1, 3, 5, 7, 9]])

# 创建自定义多热嵌入层
embedding_layer = MultiHotEmbedding(input_dim=10, output_dim=8)

# 前向传播计算
output = embedding_layer(input_features)

print(output)