biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

[CI][AMD][BugFix] Use torch.testing.assert_close instead of assert torch.allclose in test_rocm_skinny_gemms.py (#34181)

Browse Source 
Signed-off-by: Randall Smith <Randall.Smith@amd.com>
This commit is contained in:
rasmith
2026-02-18 17:10:19 -06:00
committed by GitHub
parent 11d3976b88
commit 2b84ac669c
1 changed files with 7 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
tests/kernels/quantization/test_rocm_skinny_gemms.py
View File

@@ -155,9 +155,9 @@ def test_rocm_wvsplitkrc_kernel(xnorm, n, k, m, dtype, seed, bias_mode):
out = ops.wvSplitKrc(B, A.view(-1, A.size(-1)), cu_count, BIAS)
if xnorm:
assert torch.allclose(out, ref_out, atol=1e-3, rtol=1e-8)
torch.testing.assert_close(out, ref_out, atol=1e-3, rtol=1e-8)
else:
assert torch.allclose(out, ref_out, atol=1e-3, rtol=1e-2)
torch.testing.assert_close(out, ref_out, atol=1e-3, rtol=1e-2)
@pytest.mark.parametrize("n,k,m", NKM_FACTORS_LLMM1)
@@ -177,7 +177,7 @@ def test_rocm_llmm1_kernel(n, k, m, dtype, rows_per_block, seed):
ref_out = torch.matmul(A, B.t())
out = ops.LLMM1(B, A, rows_per_block)
assert torch.allclose(out, ref_out, rtol=0.01)
torch.testing.assert_close(out, ref_out, atol=1e-8, rtol=1e-2)
@pytest.mark.parametrize("n,k,m", NKM_FACTORS_WVSPLITK)
@@ -194,7 +194,7 @@ def test_rocm_wvsplitk_kernel(n, k, m, dtype, seed):
ref_out = torch.nn.functional.linear(A, B)
out = ops.wvSplitK(B, A.view(-1, A.size(-1)), cu_count)
assert torch.allclose(out, ref_out, rtol=0.01)
torch.testing.assert_close(out, ref_out, atol=1e-8, rtol=1e-2)
@pytest.mark.parametrize("n,k,m", NKM_FACTORS_WVSPLITK)
@@ -213,7 +213,7 @@ def test_rocm_wvsplitk_bias1D_kernel(n, k, m, dtype, seed):
ref_out = torch.nn.functional.linear(A, B, BIAS)
out = ops.wvSplitK(B, A.view(-1, A.size(-1)), cu_count, BIAS)
assert torch.allclose(out, ref_out, rtol=0.01)
torch.testing.assert_close(out, ref_out, atol=1e-8, rtol=1e-2)
@pytest.mark.parametrize("n,k,m", NKM_FACTORS_WVSPLITK)
@@ -232,7 +232,7 @@ def test_rocm_wvsplitk_bias2D_kernel(n, k, m, dtype, seed):
ref_out = torch.nn.functional.linear(A, B, BIAS)
out = ops.wvSplitK(B, A.view(-1, A.size(-1)), cu_count, BIAS)
assert torch.allclose(out, ref_out, rtol=0.01)
torch.testing.assert_close(out, ref_out, atol=1e-8, rtol=1e-2)
@pytest.mark.parametrize("xnorm", [False, True])
@@ -275,4 +275,4 @@ def test_rocm_wvsplitk_fp8_kernel(
# wider pytrch thresh for large-K & no xnorm
torch.testing.assert_close(out, ref_out, atol=0.07, rtol=5e-2)
else:
torch.testing.assert_close(out, ref_out, atol=0.01, rtol=0.01)
torch.testing.assert_close(out, ref_out, atol=1e-2, rtol=1e-2)