StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],
        keepdims=True) # Author code uses std + 1e-5 return
        super().convolution_op(inputs, (kernel - mean) / tf.sqrt(var + 1e-10))`
    *   Added `merge_state()` method to `tf.keras.metrics.Metric` for use in
        distributed computations.
    *   Added `sparse` and `ragged` options to

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