SDP Backend function fix (#161169)

The issue cannot be reproduced using the original repro code provided in the issue description.

However, the underlying issue mentioned by the maintainer (missing functions in `builder.py` and `trace_rules.py`) was never addressed and can still be reproduced with this test case:

```python
import torch
from torch.nn.attention import _cur_sdpa_kernel_backends

@torch.compile(fullgraph=True)
def test_function_that_triggers_error():
    return _cur_sdpa_kernel_backends()

print("Calling torch.compile function...")
try:
    result = test_function_that_triggers_error()
    print(f"Success: {result}")
except Exception as e:
    print(f"ERROR: {e}")
    print(f"Error type: {type(e)}")
```

The original repro likely no longer triggers the issue due to code path changes in the SDPA implementation, while the direct call to `_cur_sdpa_kernel_backends()` exposes the underlying problem where certain torch._C functions returning non-Tensor values aren't properly handled by dynamo tracing.

I have implemented the changes by adding the missing functions to both `builder.py` and `trace_rules.py` to properly handle these cases during compilation.

@guilhermeleobas

Pull Request resolved: https://github.com/pytorch/pytorch/pull/161169
Approved by: https://github.com/guilhermeleobas, https://github.com/StrongerXi
This commit is contained in:
ankushwahaRH
2025-09-19 20:19:56 +00:00
committed by PyTorch MergeBot
parent 7130b174e0
commit ba3c2c80ab
3 changed files with 45 additions and 0 deletions

View File

@ -5,6 +5,7 @@ import torch._dynamo.test_case
import torch._dynamo.testing
from torch._dynamo.testing import CompileCounter
from torch.backends.cuda import SDPAParams
from torch.nn.attention import _cur_sdpa_kernel_backends, sdpa_kernel, SDPBackend
@contextlib.contextmanager
@ -99,6 +100,43 @@ class TestSDPA(torch._dynamo.test_case.TestCase):
self.assert_ref_equals_params(o, expected)
self.assertEqual(counter.frame_count, 1)
def test_sdpa_c_functions_no_graph_break(self):
counter = CompileCounter()
@torch.compile(fullgraph=True, backend=counter)
def test_cur_sdpa_kernel_backends():
return _cur_sdpa_kernel_backends()
result = test_cur_sdpa_kernel_backends()
self.assertIsInstance(result, list)
self.assertEqual(counter.frame_count, 1)
def test_sdpa_kernel_decorator_with_compile(self):
SDPA_BACKEND_PRIORITY = [
SDPBackend.MATH,
SDPBackend.EFFICIENT_ATTENTION,
SDPBackend.FLASH_ATTENTION,
]
@sdpa_kernel(backends=SDPA_BACKEND_PRIORITY, set_priority=True)
def scaled_dot_product_attention(q, k, v, *args, **kwargs):
return torch.nn.functional.scaled_dot_product_attention(
q, k, v, *args, **kwargs
)
counter = CompileCounter()
@torch.compile(fullgraph=True, backend=counter)
def f(x):
return scaled_dot_product_attention(x, x, x)
x = torch.rand(128, 64, 64, 256, dtype=torch.float16)
result = f(x)
self.assertEqual(result.shape, x.shape)
self.assertEqual(counter.frame_count, 1)
if __name__ == "__main__":
from torch._dynamo.test_case import run_tests

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@ -684,6 +684,7 @@ torch_c_binding_in_graph_functions = dict.fromkeys(
"torch._C._get_mem_efficient_sdp_enabled",
"torch._C._get_mkldnn_enabled",
"torch._C._get_cudnn_sdp_enabled",
"torch._C._get_overrideable_sdp_enabled",
"torch._C._set_sdp_use_cudnn",
"torch._C._get_mobile_model_contained_types_from_buffer",
"torch._C._get_mobile_model_contained_types",
@ -1220,6 +1221,7 @@ torch_c_binding_in_graph_functions = dict.fromkeys(
"torch._C._set_sdp_use_math",
"torch._C._set_math_sdp_allow_fp16_bf16_reduction",
"torch._C._set_sdp_use_mem_efficient",
"torch._C._set_sdp_use_overrideable",
"torch._C._set_should_use_format_with_string_table",
"torch._C._set_sm_carveout_experimental",
"torch._C._set_storage_access_error_msg",

View File

@ -3033,6 +3033,11 @@ def handle_traced_output(example_value, tx, proxy, options, subclass_type, targe
torch.backends.cuda.is_flash_attention_available,
torch.backends.cuda.can_use_flash_attention,
torch.backends.cuda.can_use_efficient_attention,
torch._C._get_cudnn_sdp_enabled,
torch._C._get_flash_sdp_enabled,
torch._C._get_mem_efficient_sdp_enabled,
torch._C._get_math_sdp_enabled,
torch._C._get_overrideable_sdp_enabled,
"is_integer",
]
+ list(supported_const_comparison_op_values.keys())