Update intro colab with models logging (#549)

Merging

colabs/intro/Intro_to_Weights_&_Biases.ipynb

@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/wandb/examples/blob/add-core-to-examples/colabs/intro/Intro_to_Weights_%26_Biases.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -104,7 +104,7 @@
         "# Log in to your W&B account\n",
         "import wandb\n",
         "\n",
-        "# Use wandb-core\n",
+        "# Use wandb-core, temporary for wandb's new backend  \n",
         "wandb.require(\"core\")"
       ]
     },
@@ -199,7 +199,9 @@
         "[hyperparameters](https://docs.wandb.ai/ref/app/pages/run-page#overview-tab),\n",
         "[terminal output](https://docs.wandb.ai/ref/app/pages/run-page#logs-tab) and\n",
         "you'll see an [interactive table](https://docs.wandb.ai/guides/data-vis)\n",
-        "with model inputs and outputs."
+        "with model inputs and outputs. \n",
+        "\n",
+        "This code will also save and upload Model checkpoints to W&B where you can then use them in the [W&B Registry](https://docs.wandb.ai/guides/registry)"
       ]
     },
     {
@@ -286,7 +288,7 @@
         "id": "KR8D_a7l1KEB"
       },
       "source": [
-        "## Train Your Model"
+        "## Train Your Model & Upload Checkpoints"
       ]
     },
     {
@@ -297,13 +299,13 @@
       },
       "outputs": [],
       "source": [
-        "# Launch 5 experiments, trying different dropout rates\n",
-        "for _ in range(5):\n",
+        "# Launch 3 experiments, trying different dropout rates\n",
+        "for _ in range(3):\n",
         "    # 🐝 initialise a wandb run\n",
         "    wandb.init(\n",
         "        project=\"pytorch-intro\",\n",
         "        config={\n",
-        "            \"epochs\": 10,\n",
+        "            \"epochs\": 5,\n",
         "            \"batch_size\": 128,\n",
         "            \"lr\": 1e-3,\n",
         "            \"dropout\": random.uniform(0.01, 0.80),\n",
@@ -356,9 +358,13 @@
         "                       \"val/val_accuracy\": accuracy}\n",
         "        wandb.log({**metrics, **val_metrics})\n",
         "\n",
-        "        print(f\"Train Loss: {train_loss:.3f}, Valid Loss: {val_loss:3f}, Accuracy: {accuracy:.2f}\")\n",
+        "        # 🐝 Save the model checkpoint to wandb\n",
+        "        torch.save(model, \"my_model.pt\")\n",
+        "        wandb.log_model(\"./mnist_model.pt\", \"my_mnist_model\", aliases=[f\"epoch-{epoch+1}_dropout-{round(wandb.config.dropout, 4)}\"])\n",
+        "\n",
+        "        print(f\"Epoch: {epoch+1}, Train Loss: {train_loss:.3f}, Valid Loss: {val_loss:3f}, Accuracy: {accuracy:.2f}\")\n",
         "\n",
-        "    # If you had a test set, this is how you could log it as a Summary metric\n",
+        "    # 🐝 If you had a test set, this is how you could log it as a Summary metric\n",
         "    wandb.summary['test_accuracy'] = 0.8\n",
         "\n",
         "    # 🐝 Close your wandb run\n",
@@ -371,7 +377,7 @@
         "id": "4SZOL5on1KEB"
       },
       "source": [
-        "You have now trained your first model using wandb! 👆 Click on the wandb link above to see your metrics"
+        "You have now trained your first model using wandb! 👆 Click on the wandb link above to see your metrics and see your saved Model checkpoints in the Artifacts tab in the UI"
       ]
     },
     {
@@ -450,9 +456,9 @@
   "metadata": {
     "accelerator": "GPU",
     "colab": {
+      "include_colab_link": true,
       "provenance": [],
-      "toc_visible": true,
-      "include_colab_link": true
+      "toc_visible": true
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -461,4 +467,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}