def install_bower(self, package, save=True, save_dev=False):
        """Installs a bower package.

        :param save: if `True`, pins the package to the Hydrogen requirements
            YAML file.
        :param save_dev: if `True`, pins the package as a development
            dependency to the Hydrogen requirements YAML file.
        :param return: a list of tuples, containing all installed package names
            and versions, including any dependencies.
        """
        requirement = Requirement.coerce(package)
        url = Bower.get_package_url(requirement.package)

        installed = []
        for name, _ in self.get_bower_package(url):
            installed.append(Requirement(name, requirement.version))

        for requirement in installed:
            if save:
                self.requirements["bower"].add(requirement, replace=True)
            if save_dev:
                self.requirements["bower-dev"].add(requirement, replace=True)
            success("installed {}".format(str(requirement)))
        if save or save_dev:
            self.requirements.save()
        return installed
def __init__(self, train_x, train_y, likelihood):
        super(GPRegressionModel, self).__init__(train_x, train_y, likelihood)
        self.mean_module = ConstantMean(prior=SmoothedBoxPrior(-1e-5, 1e-5))
        self.base_covar_module = ScaleKernel(RBFKernel(lengthscale_prior=SmoothedBoxPrior(exp(-5), exp(6), sigma=0.1)))
        self.covar_module = InducingPointKernel(
            self.base_covar_module, inducing_points=torch.linspace(0, 1, 32), likelihood=likelihood
        )