From 32777f426bc01aee9d31b1e672aaa983ea29b793 Mon Sep 17 00:00:00 2001
From: Yan Wang <wayan@nvidia.com>
Date: Wed, 19 Nov 2025 16:09:29 +0100
Subject: [PATCH 1/3] Add Tensor.is_cpu

---
 thunder/tests/opinfos.py  | 14 ++++++++++++++
 thunder/torch/__init__.py |  5 +++++
 2 files changed, 19 insertions(+)

diff --git a/thunder/tests/opinfos.py b/thunder/tests/opinfos.py
index 8f603a1883..7f06d7eab8 100644
--- a/thunder/tests/opinfos.py
+++ b/thunder/tests/opinfos.py
@@ -555,6 +555,20 @@ def _is_cuda_torch(x: torch.Tensor) -> bool:
 tensor_properties.append(is_cuda_opinfo)
 
 
+def _is_cpu_torch(x: torch.Tensor) -> bool:
+    return x.is_cpu
+
+
+is_cpu_opinfo = OpInfo(
+    ltorch.is_cpu,
+    sample_input_generator=elementwise_unary_generator,
+    torch_reference=_is_cpu_torch,
+    dtypes=(datatypes.all_dtypes),
+)
+
+tensor_properties.append(is_cpu_opinfo)
+
+
 def _is_nested_torch(x: torch.Tensor) -> bool:
     return x.is_nested
 
diff --git a/thunder/torch/__init__.py b/thunder/torch/__init__.py
index 7c828e664c..f295a2990b 100644
--- a/thunder/torch/__init__.py
+++ b/thunder/torch/__init__.py
@@ -333,6 +333,11 @@ def is_cuda(a: TensorLike, /) -> bool:
     return a.device.devicetype is devices.DeviceType.CUDA
 
 
+@torchsymbol(torch.Tensor.is_cpu, is_property=True, id="torch.is_cpu")
+def is_cpu(a: TensorLike, /) -> bool:
+    return a.device.devicetype is devices.DeviceType.CPU
+
+
 @torchsymbol(torch.polar, id="torch.polar")
 def polar(abs_: TensorLike, angle: TensorLike):
     # Decompose polar into real/imag using Thunder ops and construct complex via mapped torch.complex

From 743d803409a913a8596d7db81215adcc57024e31 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 19 Nov 2025 15:13:44 +0000
Subject: [PATCH 2/3] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 thunder/tests/distributed/test_fsdp.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/thunder/tests/distributed/test_fsdp.py b/thunder/tests/distributed/test_fsdp.py
index 920f912210..92832d17cf 100644
--- a/thunder/tests/distributed/test_fsdp.py
+++ b/thunder/tests/distributed/test_fsdp.py
@@ -46,6 +46,7 @@
     from transformer_engine.common.recipe import MXFP8BlockScaling
     import transformer_engine
     from thunder.tests.test_transformer_engine_executor import te_assert_close
+
     is_fp8_supported, fp8_support_reason = check_fp8_support()
 
 from thunder.tests.distributed.helper import (
@@ -1159,8 +1160,12 @@ def forward(self, x):
         shard_size = int(dim / world_size)
         fsdp_te_params = tuple(te_model.parameters())
         try:
-            te_assert_close(jit_model.get_parameter("fc1.weight"), fsdp_te_params[0].view(shard_size, dim), te_recipe=fp8_recipe)
-            te_assert_close(jit_model.get_parameter("fc2.weight"), fsdp_te_params[1].view(shard_size, dim), te_recipe=fp8_recipe)
+            te_assert_close(
+                jit_model.get_parameter("fc1.weight"), fsdp_te_params[0].view(shard_size, dim), te_recipe=fp8_recipe
+            )
+            te_assert_close(
+                jit_model.get_parameter("fc2.weight"), fsdp_te_params[1].view(shard_size, dim), te_recipe=fp8_recipe
+            )
         except Exception as e:
             # Return exceptions only for rank==0
             if rank == 0:

From dc081c6a12f6d460cf62e3e77d9124dab9025860 Mon Sep 17 00:00:00 2001
From: Yan Wang <wayan@nvidia.com>
Date: Thu, 20 Nov 2025 16:22:17 +0100
Subject: [PATCH 3/3] fix review comment

---
 thunder/torch/__init__.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/thunder/torch/__init__.py b/thunder/torch/__init__.py
index f295a2990b..090f46643e 100644
--- a/thunder/torch/__init__.py
+++ b/thunder/torch/__init__.py
@@ -333,11 +333,14 @@ def is_cuda(a: TensorLike, /) -> bool:
     return a.device.devicetype is devices.DeviceType.CUDA
 
 
-@torchsymbol(torch.Tensor.is_cpu, is_property=True, id="torch.is_cpu")
+@torchsymbol(torch.Tensor.is_cpu, is_property=True, id="torch.Tensor.is_cpu")
 def is_cpu(a: TensorLike, /) -> bool:
     return a.device.devicetype is devices.DeviceType.CPU
 
 
+register_method("is_cpu", is_cpu)
+
+
 @torchsymbol(torch.polar, id="torch.polar")
 def polar(abs_: TensorLike, angle: TensorLike):
     # Decompose polar into real/imag using Thunder ops and construct complex via mapped torch.complex