5b629fe89f1fdf7dd4126135825149ff848128be,gpytorch/inference/posterior_models.py,_ExactGPPosterior,__init__,#_ExactGPPosterior#Any#Any#Any#,15

Before Change

        train_y = train_y or torch.Tensor()
        if isinstance(train_x, Variable):
            train_x = train_x.data
        if isinstance(train_y, Variable):
            train_y = train_y.data
        self.register_buffer("train_x", train_x)
        self.register_buffer("train_y", train_y)


    def forward(self, input, **params):
        n = len(self.train_x)

After Change

        self.gp_observation_model = gp_observation_model

        // Buffers for conditioning on data
        if train_xs is not None and train_y is not None:
            self.update_data(train_xs, train_y)

    def update_data(self, train_xs, train_y):
        if isinstance(train_xs, Variable) or isinstance(train_xs, torch._TensorBase):
            train_xs = (train_xs,)
        train_xs = [input.data if isinstance(input, Variable) else input for input in train_xs]

Instances