Update app.py

app.py

@@ -55,4 +55,21 @@ def training():
     print("Test accuracy:", score[1])
 
     push_to_hub_keras(model, "active-learning/mnist_classifier")
+
+def find_samples_to_label():
+    loaded_model = from_pretrained_keras("active-learning/mnist_classifier")
+    loaded_model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
     
+    unlabeled_data = load_dataset("active-learning/unlabeled_samples")["train"]
+    processed_data = unlabeled_data.map(to_numpy, batched=True)
+    processed_data = processed_data["pixel_values"]
+    processed_data = tf.expand_dims(processed_data, -1)
+
+    # Get all predictions
+    # And then get the 5 samples with the lowest prediction score
+    preds = loaded_model.predict(unlabeled_data)
+    top_pred_confs = 1 - np.max(preds, axis=1)
+    idx_to_label = np.argpartition(top_pred_confs, -5)[-5:]
+
+    to_label_data = unlabeled_data.select(idx_to_label)
+    to_label_data.push_to_hub("active-learning/to_label_samples")