Reduce time of CIQ example smoke test
" urllib.request.urlretrieve('https://www.dropbox.com/s/f6ow1i59oqx05pl/3droad.mat?dl=1', '../3droad.mat')\n",
"\n",
"if smoke_test: # this is for running the notebook in our testing framework\n",
- " X, y = torch.randn(1000, 2), torch.randn(1000)\n",
+ " X, y = torch.randn(10, 2), torch.randn(10)\n",
"else:\n",
" data = torch.Tensor(loadmat('../3droad.mat')['data'])\n",
" X = data[:, :-2]\n",
"likelihood.train()\n",
"mll = gpytorch.mlls.VariationalELBO(likelihood, model, num_data=train_y.size(0))\n",
"\n",
- "num_epochs = 4\n",
+ "num_epochs = 1 if smoke_test else 4\n",
"epochs_iter = tqdm.notebook.tqdm(range(num_epochs), desc=\"Epoch\")\n",
"for i in epochs_iter:\n",
" minibatch_iter = tqdm.notebook.tqdm(train_loader, desc=\"Minibatch\", leave=False)\n",
