Skip to content

jarvis-nightly-operators-test-aten-clamp-out #15501

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Nov 4, 2025
+30 −1
Merged

jarvis-nightly-operators-test-aten-clamp-out #15501

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
9c67fe2
jarvis-nightly-operators-test-aten-clamp-out
Oct 31, 2025
f4b6ff4
Update on "jarvis-nightly-operators-test-aten-clamp-out"
Nov 1, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
31 changes: 30 additions & 1 deletion backends/cadence/utils/facto_util.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -266,6 +266,9 @@ def random_size_constraint(deps: object, r: int, d: int) -> int:
tensor_constraints.extend(
[
cp.Dtype.In(lambda deps: [torch.float32, torch.int32]),
# Avoid NaN/Inf values that expose clamp NaN handling bugs
cp.Value.Ge(lambda deps, dtype, struct: -(2**4)),
cp.Value.Le(lambda deps, dtype, struct: 2**4),
]
)
case "rsqrt.default":
Expand Down Expand Up @@ -456,6 +459,7 @@ def apply_scalar_contraints(op_name: str) -> list[ScalarDtype]:
| "mul.Scalar"
| "div.Scalar"
| "constant_pad_nd.default"
| "clamp.default"
):
return [ScalarDtype.int]
case "full.default":
Expand Down Expand Up @@ -483,7 +487,32 @@ def facto_testcase_gen( # noqa: C901
cp.Size.Le(lambda deps, r, d: 2**2),
]
)
if in_spec.name == "max_val": # hardtanh
# Special handling for clamp.default to ensure min < max with sufficient gap (at least 2) and never None
if op_name == "clamp.default":
if in_spec.name == "min":
# min must always be provided (not None) and bounded, leave room for max
spec.inspec[index].constraints.extend(
[
cp.Optional.Eq(lambda deps: False), # Never None
cp.Value.Ge(lambda deps, dtype: -(2**4)),
cp.Value.Le(
lambda deps, dtype: 2**4 - 2
), # Leave room for max (at least 2 units)
]
)
elif in_spec.name == "max":
# max must always be provided (not None), be >= min + 2 (sufficient gap), and bounded
spec.inspec[index].deps = [0, 1] # deps on input tensor and min
spec.inspec[index].constraints.extend(
[
cp.Optional.Eq(lambda deps: False), # Never None
cp.Value.Ge(
lambda deps, dtype: deps[1] + 2
), # max >= min + 2 (sufficient gap)
cp.Value.Le(lambda deps, dtype: 2**4),
]
)
elif in_spec.name == "max_val": # hardtanh
spec.inspec[index].deps = [0, 1]
spec.inspec[index].constraints.extend(
[cp.Value.Ge(lambda deps, _: deps[1])]
Expand Down
Loading