From 878be7b8d65eaa492b7fabc33ca508b3de4f25f2 Mon Sep 17 00:00:00 2001
From: Priyansh Jain <Priyanshj1304@gmail.com>
Date: Sun, 2 Nov 2025 12:49:11 +0530
Subject: [PATCH] Add clarifying documentation for CUDA 7.0+ requirement in
 torch_logs tutorial

Added a new 'Device Compatibility Check' section with detailed comments explaining that:
- torch.compile requires CUDA compute capability 7.0 or higher
- Users on unsupported devices will only see a skip message
- The logging output examples (Dynamo Tracing, Traced Graph, Fusion Decisions, Output Code) will not be displayed on unsupported devices
- Specific GPU examples (V100, T4, or newer) are provided for clarity

This improves the tutorial's clarity for all readers, especially those who might run it on devices without the required CUDA support.
---
 recipes_source/torch_logs.py | 31 ++++++++++++++-----------------
 1 file changed, 14 insertions(+), 17 deletions(-)

diff --git a/recipes_source/torch_logs.py b/recipes_source/torch_logs.py
index b5c3f0bd8ac..45ca17584f8 100644
--- a/recipes_source/torch_logs.py
+++ b/recipes_source/torch_logs.py
@@ -3,9 +3,7 @@
 ==========================================================================================
 **Author:** `Michael Lazos <https://github.com/mlazos>`_
 """
-
 import logging
-
 ######################################################################
 #
 # This tutorial introduces the ``TORCH_LOGS`` environment variable, as well as the Python API, and
@@ -16,8 +14,6 @@
 #   This tutorial requires PyTorch 2.2.0 or later.
 #
 #
-
-
 ######################################################################
 # Setup
 # ~~~~~~~~~~~~~~~~~~~~~
@@ -29,10 +25,22 @@
 #   There is also an environment variable ``TORCH_LOGS``, which can be used to
 #   change logging settings at the command line. The equivalent environment
 #   variable setting is shown for each example.
-
 import torch
 
-# exit cleanly if we are on a device that doesn't support torch.compile
+######################################################################
+# Device Compatibility Check
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# The following code checks if the device supports torch.compile, which requires
+# CUDA compute capability 7.0 or higher.
+#
+# .. important::
+#
+#   If your device does not meet this requirement, this tutorial will only print
+#   a skip message and exit. You will NOT see any of the logging output examples
+#   (Dynamo Tracing, Traced Graph, Fusion Decisions, Output Code) demonstrated
+#   below. To see the actual logging output, you need a CUDA-capable GPU with
+#   compute capability 7.0 or higher (e.g., V100, T4, or newer).
+#
 if torch.cuda.get_device_capability() < (7, 0):
     print("Skipping because torch.compile is not supported on this device.")
 else:
@@ -40,44 +48,33 @@
     def fn(x, y):
         z = x + y
         return z + 2
-
-
     inputs = (torch.ones(2, 2, device="cuda"), torch.zeros(2, 2, device="cuda"))
-
-
 # print separator and reset dynamo
 # between each example
     def separator(name):
         print(f"==================={name}=========================")
         torch._dynamo.reset()
-
-
     separator("Dynamo Tracing")
 # View dynamo tracing
 # TORCH_LOGS="+dynamo"
     torch._logging.set_logs(dynamo=logging.DEBUG)
     fn(*inputs)
-
     separator("Traced Graph")
 # View traced graph
 # TORCH_LOGS="graph"
     torch._logging.set_logs(graph=True)
     fn(*inputs)
-
     separator("Fusion Decisions")
 # View fusion decisions
 # TORCH_LOGS="fusion"
     torch._logging.set_logs(fusion=True)
     fn(*inputs)
-
     separator("Output Code")
 # View output code generated by inductor
 # TORCH_LOGS="output_code"
     torch._logging.set_logs(output_code=True)
     fn(*inputs)
-
     separator("")
-
 ######################################################################
 # Conclusion
 # ~~~~~~~~~~