botorch/models/kernels/downsampling.py [46:70]:
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    ):
        super().__init__(**kwargs)

        if power_constraint is None:
            power_constraint = Positive()
        if offset_constraint is None:
            offset_constraint = Positive()

        self.register_parameter(
            name="raw_power",
            parameter=torch.nn.Parameter(torch.zeros(*self.batch_shape, 1)),
        )

        self.register_parameter(
            name="raw_offset",
            parameter=torch.nn.Parameter(torch.zeros(*self.batch_shape, 1)),
        )

        if power_prior is not None:
            self.register_prior(
                "power_prior",
                power_prior,
                lambda m: m.power,
                lambda m, v: m._set_power(v),
            )
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botorch/models/kernels/exponential_decay.py [51:75]:
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    ):
        super().__init__(**kwargs)

        if power_constraint is None:
            power_constraint = Positive()
        if offset_constraint is None:
            offset_constraint = Positive()

        self.register_parameter(
            name="raw_power",
            parameter=torch.nn.Parameter(torch.zeros(*self.batch_shape, 1)),
        )

        self.register_parameter(
            name="raw_offset",
            parameter=torch.nn.Parameter(torch.zeros(*self.batch_shape, 1)),
        )

        if power_prior is not None:
            self.register_prior(
                "power_prior",
                power_prior,
                lambda m: m.power,
                lambda m, v: m._set_power(v),
            )
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