您可能需要查看How to make a custom activation function with only Python in Tensorflow?
patapouf_ai解释了如何使用python代码添加操作（而不需要实现C++代码。

使用TensorFlow API和模型子类化的一种方法

#Custom class inherited from Layer class

class CustomConv2D(Layer):

def __init__(self, n_filters, kernel_size, n_strides, padding="valid"):
    super(CustomConv2D, self).__init__(name="custom_conv2D")
   
    # From tensorflow API
    self.conv = Conv2D(
        filters=n_filters,
        kernel_size=kernel_size,
        activation="relu",
        strides= n_strides,
        padding=padding
    )

    # For batch normalization and can be removed if not required for use case

    self.batch_norm = BatchNormalization()

def call(self, x, training):

    x = self.conv(x)
    x = self.batch_norm(x, training)

    return x

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