AbstractDeepGP -> DeepGP
"from gpytorch.kernels import ScaleKernel, MaternKernel\n",
"from gpytorch.variational import VariationalStrategy, BatchDecoupledVariationalStrategy\n",
"from gpytorch.variational import MeanFieldVariationalDistribution\n",
- "from gpytorch.models.deep_gps import AbstractDeepGP\n",
+ "from gpytorch.models.deep_gps import DeepGP\n",
"from gpytorch.models.deep_gps.dspp import AbstractDSPPLayer, DeepPredictiveGaussianLikelihood, MultitaskDeepPredictiveGaussianLikelihood\n",
"import gpytorch.settings as settings"
]
"metadata": {},
"outputs": [],
"source": [
- "class DSPP(AbstractDeepGP):\n",
+ "class DSPP(DeepGP):\n",
" def __init__(self, train_x_shape, inducing_points, num_inducing, hidden_dim=3, Q=3):\n",
" hidden_layer = DSPPHiddenLayer(\n",
" input_dims=train_x_shape[-1],\n",
