Merge branch 'with_comet' into 2024

adding the comet code to the existing 2024 branch

Author: Shorna Alam

lab1/Part1_TensorFlow.ipynb

@@ -75,6 +75,12 @@
       },
       "outputs": [],
       "source": [
+        "# Import Comet\n",
+        "!pip install comet_ml\n",
+        "import comet_ml\n",
+        "comet_ml.init(project_name=\"6.s191lab2.2.1\")\n",
+        "comet_model_1 = comet_ml.Experiment()\n",
+        "\n",
         "# Import Tensorflow 2.0\n",
         "%tensorflow_version 2.x\n",
         "import tensorflow as tf\n",
@@ -300,9 +306,11 @@
         "    x, y = loader.get_batch(batch_size)\n",
         "    loss = standard_train_step(x, y)\n",
         "\n",
+        "    comet_model_1.log_metric(\"loss\", loss.numpy().mean(), idx)\n",
         "    # Record the loss and plot the evolution of the loss as a function of training\n",
         "    loss_history.append(loss.numpy().mean())\n",
-        "    plotter.plot(loss_history.get())"
+        "    plotter.plot(loss_history.get())\n",
+        "comet_model_1.end()"
       ]
     },
     {
@@ -756,6 +764,9 @@
       "source": [
         "### Training the SS-VAE ###\n",
         "\n",
+        "comet_ml.init(project_name=\"6.s191lab2.2.2\")\n",
+        "comet_model_2 = comet_ml.Experiment()\n",
+        "\n",
         "# Hyperparameters\n",
         "batch_size = 32\n",
         "learning_rate = 5e-4\n",
@@ -806,10 +817,13 @@
         "    (x, y) = loader.get_batch(batch_size)\n",
         "    # loss optimization\n",
         "    loss = ss_vae_train_step(x, y)\n",
+        "    comet_model_2.log_metric(\"loss\", loss, step=j)\n",
         "    \n",
         "    # plot the progress every 200 steps\n",
         "    if j % 500 == 0: \n",
-        "      mdl.util.plot_sample(x, y, ss_vae)"
+        "      mdl.util.plot_sample(x, y, ss_vae)\n",
+        "  \n",
+        "comet_model_2.end()"
       ]
     },
     {