From 38d6e052f3489bc85350ff3f713494d9de3cde4c Mon Sep 17 00:00:00 2001
From: Manas Vardhan <manasvardhan@Manas-MacBook-Air.local>
Date: Mon, 16 Feb 2026 09:04:56 -0800
Subject: [PATCH] Fix outdated torch_logs tutorial by removing CUDA device
 check

The tutorial was wrapped in a CUDA device capability check that caused
the entire example to be skipped when built on CI without a compatible
GPU. This resulted in the docs showing 'Skipping because torch.compile
is not supported on this device' instead of actual log output.

torch.compile works on CPU, so this fix removes the device check and
uses a dynamic device selection (CUDA if available, otherwise CPU).
This ensures the tutorial produces meaningful log output regardless of
the build environment.

Fixes pytorch/pytorch#137285
---
 recipes_source/torch_logs.py | 48 +++++++++++++++++-------------------
 1 file changed, 23 insertions(+), 25 deletions(-)

diff --git a/recipes_source/torch_logs.py b/recipes_source/torch_logs.py
index b5c3f0bd8ac..527bcd71f3f 100644
--- a/recipes_source/torch_logs.py
+++ b/recipes_source/torch_logs.py
@@ -32,51 +32,49 @@
 
 import torch
 
-# exit cleanly if we are on a device that doesn't support torch.compile
-if torch.cuda.get_device_capability() < (7, 0):
-    print("Skipping because torch.compile is not supported on this device.")
-else:
-    @torch.compile()
-    def fn(x, y):
-        z = x + y
-        return z + 2
 
+@torch.compile()
+def fn(x, y):
+    z = x + y
+    return z + 2
 
-    inputs = (torch.ones(2, 2, device="cuda"), torch.zeros(2, 2, device="cuda"))
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+inputs = (torch.ones(2, 2, device=device), torch.zeros(2, 2, device=device))
 
 
 # print separator and reset dynamo
 # between each example
-    def separator(name):
-        print(f"==================={name}=========================")
-        torch._dynamo.reset()
+def separator(name):
+    print(f"==================={name}=========================")
+    torch._dynamo.reset()
 
 
-    separator("Dynamo Tracing")
+separator("Dynamo Tracing")
 # View dynamo tracing
 # TORCH_LOGS="+dynamo"
-    torch._logging.set_logs(dynamo=logging.DEBUG)
-    fn(*inputs)
+torch._logging.set_logs(dynamo=logging.DEBUG)
+fn(*inputs)
 
-    separator("Traced Graph")
+separator("Traced Graph")
 # View traced graph
 # TORCH_LOGS="graph"
-    torch._logging.set_logs(graph=True)
-    fn(*inputs)
+torch._logging.set_logs(graph=True)
+fn(*inputs)
 
-    separator("Fusion Decisions")
+separator("Fusion Decisions")
 # View fusion decisions
 # TORCH_LOGS="fusion"
-    torch._logging.set_logs(fusion=True)
-    fn(*inputs)
+torch._logging.set_logs(fusion=True)
+fn(*inputs)
 
-    separator("Output Code")
+separator("Output Code")
 # View output code generated by inductor
 # TORCH_LOGS="output_code"
-    torch._logging.set_logs(output_code=True)
-    fn(*inputs)
+torch._logging.set_logs(output_code=True)
+fn(*inputs)
 
-    separator("")
+separator("")
 
 ######################################################################
 # Conclusion