0d97bc0bb3db40017f1278d6c1f292ea0f789ab0,gpflow/optimizers/mcmc.py,SamplingHelper,__init__,#SamplingHelper#Any#Any#,54

Before Change

    ):
        assert all([isinstance(p, (Parameter, tf.Variable)) for p in model_parameters])

        self._model_parameters = model_parameters
        self._target_log_prob_fn = target_log_prob_fn

        self._parameters = []
        self._unconstrained_variables = []
        for p in self._model_parameters:
            self._unconstrained_variables.append(
                p.unconstrained_variable if isinstance(p, Parameter) else p
            )
            self._parameters.append(p)

    @property
    def current_state(self):
        Return the current state of the unconstrained variables, used in HMC.

After Change

    

    def __init__(self, target_log_prob_fn: LogProbabilityFunction, parameters: Parameters):
        if not all([isinstance(p, Parameter) and p.prior is not None for p in parameters]):
            raise ValueError(f"Expected only parameters with priors")

        self._parameters = parameters
        self._target_log_prob_fn = target_log_prob_fn
        self._variables = [p.unconstrained_variable for p in parameters]

Instances