import keras
import tensorflow as tf
class Linear(keras.layers.Layer):
    def __init__(self, input_dim=32, output_dim=32):
        super().__init__()
        w_init = tf.random_normal_initializer()
        self.w = tf.Variable(
            initial_value=w_init(shape=(input_dim, output_dim), dtype="float32"),
            
           
            trainable=True,
        )
        # print(self.w)
        b_init = tf.zeros_initializer()
        self.b = tf.Variable(
            initial_value=b_init(shape=(output_dim,), dtype="float32"), trainable=True
        )

    def call(self, inputs):
        #矩阵相乘 Amn*Bnp 的维度是m*p
        return tf.matmul(inputs, self.w) + self.b
    
x = tf.ones((3, 2))
linear_layer = Linear(2, 5)

#函数式变成直接用 linear_layer(x)
y= linear_layer(x)
print(y.shape)

#更本质通用的用法
y = linear_layer.call(x)
print(y.shape)