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Fix nondeterministic RNG in test_fused_mxfp4_quant #2562

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Merged
brunomazzottiamd merged 2 commits into from
Apr 1, 2026
Merged

Fix nondeterministic RNG in test_fused_mxfp4_quant #2562

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4d2b520
Fix nondeterministic RNG in test_fused_mxfp4_quant
nidal567 Mar 31, 2026
46bbfd3
Set RNG seed before all test cases to make everything deterministic. …
nidal567 Apr 1, 2026
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14 changes: 11 additions & 3 deletions op_tests/triton_tests/quant/test_fused_mxfp4_quant.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,8 +22,6 @@
from aiter.ops.quant import per_1x32_f4_quant_hip
from aiter.utility.fp4_utils import moe_mxfp4_sort, dynamic_mxfp4_quant

torch.manual_seed(0)


def rmsnorm(input, weight, eps=1e-6):
row_norm = input * input
Expand Down Expand Up @@ -130,6 +128,8 @@ def test_flatten_quant(B: int, M: int, N: int, dtype):
if not (arch_info.is_fp4_avail()):
pytest.skip("MXFP4 not supported on this architecture")

torch.manual_seed(0)

torch.cuda.empty_cache() # Helps avoid hangs in large tests

x = torch.randn((B, M, N), dtype=dtype, device="cuda").transpose(0, 1)
Expand Down Expand Up @@ -169,10 +169,11 @@ def test_fused_rms_quant(
shuffle: bool,
scale_shuffle_padding: bool,
):

if not (arch_info.is_fp4_avail()):
pytest.skip("MXFP4 not supported on this architecture")

torch.manual_seed(0)

torch.cuda.empty_cache() # Helps avoid hangs in large tests
x1, x2, rms1_w, rms2_w, resid1 = generate_fused_rms_quant_data(
x1_shape=(M, N1),
Expand Down Expand Up @@ -317,6 +318,8 @@ def test_fused_reduce_act_mul_mxfp4_group_quant(
if not (arch_info.is_fp4_avail()):
pytest.skip("MXFP4 not supported on this architecture")

torch.manual_seed(0)

if shuffle and (N1 * 2) % 512 != 0:
pytest.skip()

Expand Down Expand Up @@ -402,6 +405,8 @@ def test_fuse_reduce_rms_quant(
if not (arch_info.is_fp4_avail()):
pytest.skip("MXFP4 not supported on this architecture")

torch.manual_seed(0)

torch.cuda.empty_cache() # Helps avoid hangs in large tests
x1, w1, x2, w2, res1, x3 = generate_fused_reduce_rms_quant_data(
M, N1, N2, N3, SPK, dtype
Expand Down Expand Up @@ -548,6 +553,9 @@ def test_fused_dynamic_mxfp4_quant_moe_sort(
):
if not (arch_info.is_fp4_avail()):
pytest.skip("MXFP4 not supported on this architecture")

torch.manual_seed(0)

q_dtype_a = torch.float4_e2m1fn_x2
num_local_tokens = None
num_valid_ids = torch.zeros(2, dtype=torch.int64, device="cuda")
Expand Down
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