Fixing smoke test
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"# this is for running the notebook in our testing framework\n",
"smoke_test = ('CI' in os.environ)\n",
"\n",
- "\n",
"if not smoke_test and not os.path.isfile('../elevators.mat'):\n",
" print('Downloading \\'elevators\\' UCI dataset...')\n",
" urllib.request.urlretrieve('https://drive.google.com/uc?export=download&id=1jhWL3YUHvXIaftia4qeAyDwVxo6j1alk', '../elevators.mat')\n",
"\n",
"\n",
"if smoke_test: # this is for running the notebook in our testing framework\n",
- " X, y = torch.randn(1000, 3), torch.randn(1000)\n",
+ " X, y = torch.randn(1000, 18), torch.randn(1000)\n",
"else:\n",
" data = torch.Tensor(loadmat('../elevators.mat')['data'])\n",
" X = data[:, :-1]\n",
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 19,
"metadata": {},
"outputs": [
{
"<All keys matched successfully>"
]
},
- "execution_count": 3,
+ "execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"traced_model.save('traced_model.pt')"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
