f47e301e50018af3365e3717e3ab1d8e07d297b5,gpytorch/kernels/index_kernel.py,IndexKernel,__init__,#IndexKernel#Any#Any#Any#Any#,7

Before Change

class IndexKernel(Kernel):
    def __init__(self, n_tasks, rank=1, covar_factor_bounds=(-100, 100), log_var_bounds=(-100, 100)):
        super(IndexKernel, self).__init__()
        self.register_parameter("covar_factor", nn.Parameter(torch.randn(n_tasks, rank)),
                                bounds=covar_factor_bounds)
        self.register_parameter("log_var", nn.Parameter(torch.randn(n_tasks)), bounds=log_var_bounds)

    def forward(self, i1, i2):
        covar_matrix = self.covar_factor.matmul(self.covar_factor.transpose(-1, -2))

After Change

    ):
        if active_dims is not None and len(active_dims) > 1:
            raise ValueError(
                "Index must be with respect to a single column. Received {}"
                .format(active_dims)
            )
        super(IndexKernel, self).__init__(active_dims=active_dims)
        self.register_parameter(
            "covar_factor",
            nn.Parameter(torch.randn(n_tasks, rank)),

Instances