6bf26a0ab5c0ea9e332216d1d48d4ce3c03a2f8d,gpytorch/kernels/kernel.py,Kernel,size,#Kernel#Any#Any#,196

Before Change

    def size(self, x1, x2):
        non_batch_size = (x1.size(-2), x2.size(-2))
        if x1.ndimension() == 3:
            return torch.Size((x1.size(0),) + non_batch_size)
        else:
            return torch.Size(non_batch_size)

    @abstractmethod
    def forward(self, x1, x2, diag=False, batch_dims=None, **params):
        
        Computes the covariance between x1 and x2.

After Change

    def size(self, x1, x2):
        non_batch_shape = torch.Size([x1.size(-2), x2.size(-2)])
        return x1.shape[:-2] + non_batch_shape

    @abstractmethod
    def forward(self, x1, x2, diag=False, batch_dims=None, **params):

Instances