past embeds type issue, labels

app.py

@@ -90,16 +90,12 @@ def quantize_embeds(embeds):
     return quantized_embeds, closest_bin
 
 def update_exemplars(df, rng, exemplars, lut):
-    print(df[['image_embed']], df[['image_embed']].to_numpy().shape)
-    print(np.array(df['image_embed'].values.tolist()).shape)
     embeds = np.array(df['image_embed'].values.tolist()) # df[['image_embed']].to_numpy()
-    print(df['labels'].to_numpy())
-    labels = df[['label']].to_numpy().astype('int')
-    print(labels)
-    print(embeds)
+    labels = np.array(df['label'].values.tolist(), 'int')
+    print(labels, labels.shape)
     assert np.all(np.unique(labels) == [0, 1])
-    labels_zero_idx = (labels == 0).nonzero()
-    labels_one_idx = (labels == 1).nonzero()
+    labels_zero_idx = (labels == 0).nonzero()[0]
+    labels_one_idx = (labels == 1).nonzero()[0]
     print(labels_zero_idx.shape, " zeros and ", labels_one_idx.shape, " ones")
     # 70-30 split
     labels_zero_train_idx = rng.choice(labels_zero_idx, size=int(.7 * len(labels_zero_idx)), replace=False)