Tutorial2: moved functs from utils.py to notebook

Author: GabrieleSantin

Tutorial2/Tutorial2.ipynb

@@ -168,7 +168,30 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from utils import VectorialDataset\n",
+    "#%% Dataset to manage vector to vector data\n",
+    "class VectorialDataset(torch.utils.data.Dataset):\n",
+    "    def __init__(self, input_data, output_data):\n",
+    "        super(VectorialDataset, self).__init__()\n",
+    "        self.input_data = torch.tensor(input_data.astype('f'))\n",
+    "        self.output_data = torch.tensor(output_data.astype('f'))\n",
+    "        \n",
+    "    def __len__(self):\n",
+    "        return self.input_data.shape[0]\n",
+    "    \n",
+    "    def __getitem__(self, idx):\n",
+    "        if torch.is_tensor(idx):\n",
+    "            idx = idx.tolist()\n",
+    "        sample = (self.input_data[idx, :], \n",
+    "                  self.output_data[idx, :])  \n",
+    "        return sample "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "training_set = VectorialDataset(input_data=X_train, output_data=y_train)"
    ]
   },
@@ -287,7 +310,30 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from utils import LinearModel\n",
+    "#%% Linear layer\n",
+    "class LinearModel(nn.Module):\n",
+    "    def __init__(self, input_dim, output_dim):\n",
+    "        super(LinearModel, self).__init__()\n",
+    "\n",
+    "        self.input_dim = input_dim\n",
+    "        self.output_dim = output_dim\n",
+    "\n",
+    "        self.linear = nn.Linear(self.input_dim, self.output_dim, bias=True)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        out = self.linear(x)\n",
+    "        return out\n",
+    "    \n",
+    "    def reset(self):\n",
+    "        self.linear.reset_parameters()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "model = LinearModel(input_dim, output_dim)"
    ]
   },