[CI][Test] Deflake the rms_norm scaling-property assertions (#54271)
Signed-off-by: Oxana Korzh <okorzh@amd.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
Oxana Korzh committed
Aug 28, 2026 at 18:08 UTC
1a16c2ad2cb43b68b99a25965ebdb799c690968d
1 file changed
+10
-4
tests/kernels/ir/test_layernorm.py
+10
-4
@@ -12,7 +12,7 @@ from tests.ir.ir_test_utils import (
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clone_args,
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supported_providers,
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)
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-from tests.kernels.allclose_default import get_default_rtol
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+from tests.utils import set_random_seed
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from vllm import ir
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from vllm.platforms import current_platform
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@@ -52,6 +52,7 @@ def test_rms_norm_registration():
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)
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class TestRMSNorm:
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def test_native_semantics(self, dtype, n_tokens, hidden_size, epsilon):
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+ set_random_seed(0)
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x, weight, epsilon = ir.ops.rms_norm.generate_inputs(
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num_tokens=4,
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hidden_size=8,
@@ -66,9 +67,13 @@ class TestRMSNorm:
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assert out.dtype == x.dtype
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assert out.device == x.device
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- # Check the scaling property of rms norm
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+ # Check the scaling property of rms norm. This holds only
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+ # approximately: epsilon does not scale with x, so
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+ # rms_norm(2x) = x / sqrt(mean(x^2) + epsilon/4), which differs from
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+ # rms_norm(x) by the epsilon term. Use the op's declared tolerance
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+ # rather than a tighter hard-coded one.
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out2 = rms_norm_native(x * 2.0, weight, epsilon=epsilon)
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- torch.testing.assert_close(out2, out, rtol=get_default_rtol(out), atol=1e-3)
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+ assert_close(ir.ops.rms_norm, out2, out)
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# Mean square should be approximately 1 (ignoring epsilon and weight scaling)
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combined_norm = out.float() / weight.float()
@@ -266,6 +271,7 @@ def test_vllm_c_fused_add_rms_norm_accepts_nd_input():
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)
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class TestFusedAddRMSNorm:
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def test_native_semantics(self, dtype, n_tokens, hidden_size, epsilon):
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+ set_random_seed(0)
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x, x_residual, weight, eps = ir.ops.fused_add_rms_norm.generate_inputs(
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num_tokens=4,
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hidden_size=8,
@@ -304,7 +310,7 @@ class TestFusedAddRMSNorm:
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out2, _ = fused_add_rms_norm_native(
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x * 2.0, torch.zeros_like(x), weight, epsilon=epsilon
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)
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- torch.testing.assert_close(out2, out1, rtol=get_default_rtol(out), atol=1e-3)
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+ assert_close(ir.ops.fused_add_rms_norm, out2, out1)
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# Check behavior with and without weight
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weight1 = torch.ones_like(weight)