[Inductor UT] Set input tensors to corresponding device for test case in

test_aot_indutor.py

Fix #145247

ghstack-source-id: 3d452ab351
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145248

test/inductor/test_aot_inductor_utils.py

@@ -16,6 +16,7 @@ from torch._inductor import config
 from torch._inductor.test_case import TestCase
 from torch.testing import FileCheck
 from torch.testing._internal.common_utils import IS_FBCODE
+from torch.testing._internal.inductor_utils import clone_preserve_strides_offset
 from torch.utils import _pytree as pytree
 
 
@@ -177,6 +178,18 @@ def check_model(
         torch.manual_seed(0)
         if not isinstance(model, types.FunctionType):
             model = model.to(self.device)
+
+        # For non mixed device inputs with default "cpu",set the device manully.
+        if all(
+            t.device.type == "cpu"
+            for t in example_inputs
+            if isinstance(t, torch.Tensor)
+        ):
+            example_inputs = tuple(
+                clone_preserve_strides_offset(x, device=self.device)
+                for x in example_inputs
+            )
+
         ref_model = copy.deepcopy(model)
         ref_inputs = copy.deepcopy(example_inputs)
         expected = ref_model(*ref_inputs)

test/inductor/test_torchinductor.py

@@ -121,6 +121,7 @@ from torch._inductor.compile_fx import (
 from torch._inductor.utils import has_torchvision_roi_align
 from torch.testing._internal.common_utils import slowTest
 from torch.testing._internal.inductor_utils import (
+    clone_preserve_strides_offset,
     GPU_TYPE,
     HAS_CPU,
     HAS_GPU,
@@ -372,20 +373,6 @@ def compute_grads(args, kwrags, results, grads):
     )
 
 
-def clone_preserve_strides(x, device=None):
-    if not isinstance(x, torch.Tensor):
-        return x
-    buffer = torch.as_strided(
-        x, (x.untyped_storage().size() // x.element_size(),), (1,), 0
-    )
-    if not device:
-        buffer = buffer.clone()
-    else:
-        buffer = buffer.to(device, copy=True)
-    out = torch.as_strided(buffer, x.size(), x.stride(), x.storage_offset())
-    return out
-
-
 def check_model(
     self: TestCase,
     model,
@@ -409,7 +396,7 @@ def check_model(
     kwargs = kwargs or {}
     torch._dynamo.reset()
 
-    ref_inputs = [clone_preserve_strides(x) for x in example_inputs]
+    ref_inputs = [clone_preserve_strides_offset(x) for x in example_inputs]
     ref_kwargs = kwargs
     has_lowp_args = False
 
@@ -422,7 +409,7 @@ def check_model(
             # Eager model may fail if the dtype is not supported
             eager_result = None
 
-        ref_inputs = [clone_preserve_strides(x) for x in example_inputs]
+        ref_inputs = [clone_preserve_strides_offset(x) for x in example_inputs]
         expect_dtypes = [
             x.dtype if isinstance(x, torch.Tensor) else None
             for x in pytree.tree_leaves(eager_result)
@@ -625,7 +612,7 @@ def check_model_gpu(
 
     if copy_to_gpu:
         example_inputs = tuple(
-            clone_preserve_strides(x, device=GPU_TYPE) for x in example_inputs
+            clone_preserve_strides_offset(x, device=GPU_TYPE) for x in example_inputs
         )
 
     check_model(

torch/testing/_internal/inductor_utils.py

@@ -195,3 +195,16 @@ def maybe_skip_size_asserts(op):
         return torch._inductor.config.patch(size_asserts=False)
     else:
         return contextlib.nullcontext()
+
+def clone_preserve_strides_offset(x, device=None):
+    if not isinstance(x, torch.Tensor):
+        return x
+    buffer = torch.as_strided(
+        x, (x.untyped_storage().size() // x.element_size(),), (1,), 0
+    )
+    if not device:
+        buffer = buffer.clone()
+    else:
+        buffer = buffer.to(device, copy=True)
+    out = torch.as_strided(buffer, x.size(), x.stride(), x.storage_offset())
+    return out