keras/src/layers/normalization/spectral_normalization.py/SpectralNormalization/call
class SpectralNormalization:    def call(self, inputs, training=False):
        if training:
            new_vector_u, new_kernel = ops.cond(
                ops.all(ops.equal(self.kernel.value, 0)),
                lambda: (self.vector_u.value, self.kernel.value),
                self.normalized_weights,
            )
            self.vector_u.assign(new_vector_u)
            self.kernel.assign(new_kernel)

        output = self.layer(inputs)
        return ops.cast(output, inputs.dtype)