softmax

app.py

@@ -184,10 +184,10 @@ def predict(embeds, exemplars, lut):
     hd_embeds[hd_embeds < 0.5] = 0.
     # hd_embeds_integer is nexample x dims
     # print(exemplars[0].shape, exemplars[1].shape, np.abs(exemplars[0] - exemplars[1]).sum())
-    preds = np.zeros(hd_embeds.shape[0])
     dist_to_ex0 = np.abs(hd_embeds - exemplars[0][np.newaxis, ...]).sum(axis=-1)
     dist_to_ex1 = np.abs(hd_embeds - exemplars[1][np.newaxis, ...]).sum(axis=-1)
-    preds[dist_to_ex1 < dist_to_ex0] = 1
+    preds = [HYPERDIMS - dist_to_ex0, HYPERDIMS - dist_to_ex1]
+    preds = np.exp(preds)/sum(np.exp(preds))
     # print(preds.shape)
     return {"👍": preds[1], "👎": preds[0]}