From 29adae84eb0ef7b5dc7b3835f7219a67fbb26b40 Mon Sep 17 00:00:00 2001
From: DavidFarago <farago@gmx.de>
Date: Thu, 24 Aug 2023 23:09:12 +0200
Subject: [PATCH] Quickstart: Use tensors to compute train accuracy (#1662)

Co-authored-by: Dave Farago <dfarago@innoopract.com>
---
 docs/quickstart.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/quickstart.md b/docs/quickstart.md
index 8211b69d69..573f5c0d08 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -205,11 +205,11 @@ for step in range(1000):
   opt.step()
 
   # calculate accuracy
-  pred = out.argmax(axis=-1).numpy()
+  pred = out.argmax(axis=-1)
   acc = (pred == labels).mean()
 
   if step % 100 == 0:
-    print(f"Step {step+1} | Loss: {loss.numpy()} | Accuracy: {acc}")
+    print(f"Step {step+1} | Loss: {loss.numpy()} | Accuracy: {acc.numpy()}")
 ```
 
 ## Evaluation