add tested files with jax backend

Author: maitry63

examples/vision/ipynb/supervised-contrastive-learning.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "**Author:** [Khalid Salama](https://www.linkedin.com/in/khalid-salama-24403144/)<br>\n",
     "**Date created:** 2020/11/30<br>\n",
-    "**Last modified:** 2026/07/17<br>\n",
+    "**Last modified:** 2026/08/04<br>\n",
     "**Description:** Using supervised contrastive learning for image classification."
    ]
   },
@@ -71,16 +71,15 @@
    },
    "outputs": [],
    "source": [
-    "num_classes = 10\n",
+    "num_classes = 50\n",
     "input_shape = (32, 32, 3)\n",
     "\n",
     "# Load the train and test data splits\n",
     "(x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.load_data()\n",
     "\n",
     "# Display shapes of train and test datasets\n",
     "print(f\"x_train shape: {x_train.shape} - y_train shape: {y_train.shape}\")\n",
-    "print(f\"x_test shape: {x_test.shape} - y_test shape: {y_test.shape}\")\n",
-    ""
+    "print(f\"x_test shape: {x_test.shape} - y_test shape: {y_test.shape}\")\n"
    ]
   },
   {
@@ -195,8 +194,7 @@
     "        loss=keras.losses.SparseCategoricalCrossentropy(),\n",
     "        metrics=[keras.metrics.SparseCategoricalAccuracy()],\n",
     "    )\n",
-    "    return model\n",
-    ""
+    "    return model\n"
    ]
   },
   {
@@ -227,8 +225,7 @@
     "history = classifier.fit(x=x_train, y=y_train, batch_size=batch_size, epochs=num_epochs)\n",
     "\n",
     "accuracy = classifier.evaluate(x_test, y_test)[1]\n",
-    "print(f\"Test accuracy: {round(accuracy * 100, 2)}%\")\n",
-    ""
+    "print(f\"Test accuracy: {round(accuracy * 100, 2)}%\")\n"
    ]
   },
   {
@@ -302,8 +299,7 @@
     "    model = keras.Model(\n",
     "        inputs=inputs, outputs=outputs, name=\"cifar-encoder_with_projection-head\"\n",
     "    )\n",
-    "    return model\n",
-    ""
+    "    return model\n"
    ]
   },
   {
@@ -426,4 +422,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}

examples/vision/md/supervised-contrastive-learning.md

@@ -44,7 +44,7 @@ from keras import ops
 
 
 ```python
-num_classes = 10
+num_classes = 50
 input_shape = (32, 32, 3)
 
 # Load the train and test data splits

examples/vision/supervised-contrastive-learning.py

@@ -38,7 +38,7 @@
 ## Prepare the data
 """
 
-num_classes = 10
+num_classes = 50
 input_shape = (32, 32, 3)
 
 # Load the train and test data splits