def __getattr__()

in pyro/nn/module.py [0:0]

• 49 lines of code
• 23 McCabe index (conditional complexity)

    def __getattr__(self, name):
        # PyroParams trigger pyro.param statements.
        if '_pyro_params' in self.__dict__:
            _pyro_params = self.__dict__['_pyro_params']
            if name in _pyro_params:
                constraint, event_dim = _pyro_params[name]
                unconstrained_value = getattr(self, name + "_unconstrained")
                if self._pyro_context.active:
                    fullname = self._pyro_get_fullname(name)
                    if fullname in _PYRO_PARAM_STORE:
                        if _PYRO_PARAM_STORE._params[fullname] is not unconstrained_value:
                            # Update PyroModule <--- ParamStore.
                            unconstrained_value = _PYRO_PARAM_STORE._params[fullname]
                            if not isinstance(unconstrained_value, torch.nn.Parameter):
                                # Update PyroModule ---> ParamStore (type only; data is preserved).
                                unconstrained_value = torch.nn.Parameter(unconstrained_value)
                                _PYRO_PARAM_STORE._params[fullname] = unconstrained_value
                                _PYRO_PARAM_STORE._param_to_name[unconstrained_value] = fullname
                            super().__setattr__(name + "_unconstrained", unconstrained_value)
                    else:
                        # Update PyroModule ---> ParamStore.
                        _PYRO_PARAM_STORE._constraints[fullname] = constraint
                        _PYRO_PARAM_STORE._params[fullname] = unconstrained_value
                        _PYRO_PARAM_STORE._param_to_name[unconstrained_value] = fullname
                    return pyro.param(fullname, event_dim=event_dim)
                else:  # Cannot determine supermodule and hence cannot compute fullname.
                    return transform_to(constraint)(unconstrained_value)

        # PyroSample trigger pyro.sample statements.
        if '_pyro_samples' in self.__dict__:
            _pyro_samples = self.__dict__['_pyro_samples']
            if name in _pyro_samples:
                prior = _pyro_samples[name]
                context = self._pyro_context
                if context.active:
                    fullname = self._pyro_get_fullname(name)
                    value = context.get(fullname)
                    if value is None:
                        if not hasattr(prior, "sample"):  # if not a distribution
                            prior = prior(self)
                        value = pyro.sample(fullname, prior)
                        context.set(fullname, value)
                    return value
                else:  # Cannot determine supermodule and hence cannot compute fullname.
                    if not hasattr(prior, "sample"):  # if not a distribution
                        prior = prior(self)
                    return prior()

        result = super().__getattr__(name)

        # Regular nn.Parameters trigger pyro.param statements.
        if isinstance(result, torch.nn.Parameter) and not name.endswith("_unconstrained"):
            if self._pyro_context.active:
                pyro.param(self._pyro_get_fullname(name), result)

        # Regular nn.Modules trigger pyro.module statements.
        if isinstance(result, torch.nn.Module) and not isinstance(result, PyroModule):
            if self._pyro_context.active:
                pyro.module(self._pyro_get_fullname(name), result)

        return result