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Updated test to include CK/AITER V2/V3 test in single backend case #454

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Updated test to include CK/AITER V2/V3 test in single backend case #454

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d6e6591
Updated test to include CK/AITER V2/V3 test in single backend case
Micky774 Feb 20, 2026
83c715d
Streamlined per PR review
Micky774 Feb 20, 2026
b0b9906
Updated skip condition
Micky774 Feb 20, 2026
7ac6eab
Added IS_HIP_EXTENSION guard, and included CK/AITER comp in transformer
Micky774 Feb 23, 2026
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83 changes: 69 additions & 14 deletions tests/pytorch/attention/test_attention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -240,7 +240,12 @@ def test_dot_product_attention(
flash_attn_supported = True

# Skip if only unfused backend is supported
if (len(fused_attn_backends) + flash_attn_supported + unfused_attn_supported) < 2:
# Double-count the CK backend since we want to compare V2/V3 kernels
if (
len(fused_attn_backends) +
int(IS_HIP_EXTENSION and FusedAttnBackend["CK"] in fused_attn_backends) +
flash_attn_supported + unfused_attn_supported
) < 2:
pytest.skip("Less than two backends to compare.")

# UnfusedDotProductAttention backend
Expand Down Expand Up @@ -269,7 +274,21 @@ def test_dot_product_attention(
pad_between_seqs,
is_training,
)
if len(fused_attn_backends) == 2:
# We can consider the CK backend as being two, since we have V2/V3 kernels
if IS_HIP_EXTENSION and FusedAttnBackend["CK"] in fused_attn_backends:
os.environ["NVTE_CK_USES_FWD_V3"] = "0"
os.environ["NVTE_CK_USES_BWD_V3"] = "0"
fused_attn_fwd_1, fused_attn_bwd_1 = _run_dot_product_attention(
dtype,
config,
"FusedAttention",
ckpt_attn,
qkv_layout,
workspace_opt,
pad_between_seqs,
is_training,
)
elif len(fused_attn_backends) == 2:
os.environ["NVTE_FUSED_ATTN_BACKEND"] = "0"
os.environ["NVTE_FUSED_ATTN_CK"] = "0"
os.environ["NVTE_FUSED_ATTN_AOTRITON"] = "1"
Expand All @@ -286,8 +305,6 @@ def test_dot_product_attention(
os.environ["NVTE_FUSED_ATTN_BACKEND"] = "1"
os.environ["NVTE_FUSED_ATTN_CK"] = "1"
os.environ["NVTE_FUSED_ATTN_AOTRITON"] = "0"
os.environ["NVTE_CK_USES_FWD_V3"] = "1"
os.environ["NVTE_CK_USES_BWD_V3"] = "1"
fused_attn_fwd_1, fused_attn_bwd_1 = _run_dot_product_attention(
dtype,
config,
Expand Down Expand Up @@ -352,6 +369,16 @@ def test_dot_product_attention(
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_2, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_2[i], **tols)
if (
fused_attn_supported and
len(fused_attn_backends) == 1 and
IS_HIP_EXTENSION and
FusedAttnBackend["CK"] in fused_attn_backends
):
logging.info("[test_dot_product_attention]: CK fused attn V2 vs V3")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_1, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_1[i], **tols)


@pytest.mark.skipif(get_cudnn_version() < (8, 9, 1), reason="cuDNN 8.9.1+ is required.")
Expand Down Expand Up @@ -1259,7 +1286,12 @@ def test_transformer_layer(
flash_attn_supported, fused_attn_supported, unfused_attn_supported = available_backends

# Skip if only unfused backend is supported
if (len(fused_attn_backends) + flash_attn_supported + unfused_attn_supported) < 2:
# Double-count the CK backend since we want to compare V2/V3 kernels
if (
len(fused_attn_backends) +
int(IS_HIP_EXTENSION and FusedAttnBackend["CK"] in fused_attn_backends) +
flash_attn_supported + unfused_attn_supported
) < 2:
pytest.skip("Less than two backends to compare.")
# Skip if qkv_format = thd and "padding" not in attn_mask_type
if qkv_format == "thd" and "padding" not in config.attn_mask_type:
Expand Down Expand Up @@ -1293,6 +1325,20 @@ def test_transformer_layer(
RoPE,
is_training,
)
if IS_HIP_EXTENSION and FusedAttnBackend["CK"] in fused_attn_backends:
os.environ["NVTE_CK_USES_FWD_V3"] = "0"
os.environ["NVTE_CK_USES_BWD_V3"] = "0"
fused_attn_fwd_1, fused_attn_bwd_1 = _run_transformer_layer(
dtype,
config,
"FusedAttention",
ckpt_attn,
qkv_format,
workspace_opt,
fused_qkv_params,
RoPE,
is_training,
)
elif len(fused_attn_backends) == 2:
os.environ["NVTE_FUSED_ATTN_CK"] = "0"
os.environ["NVTE_FUSED_ATTN_AOTRITON"] = "1"
Expand Down Expand Up @@ -1363,15 +1409,24 @@ def test_transformer_layer(
logging.info("[test_transformer_layer]: fused attn vs flash attn")
torch.testing.assert_close(fused_attn_fwd, flash_attn_fwd, **tols)
torch.testing.assert_close(fused_attn_bwd, flash_attn_bwd, **tols)
if IS_HIP_EXTENSION and fused_attn_supported and len(fused_attn_backends) == 2:
logging.info("[test_transformer_layer]: fused attn backend 0 vs 1")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_1, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_1[i], **tols)
logging.info("[test_transformer_layer]: fused attn backend 0 vs 2")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_2, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_2[i], **tols)
if IS_HIP_EXTENSION and fused_attn_supported:
if len(fused_attn_backends) == 2:
logging.info("[test_transformer_layer]: fused attn backend 0 vs 1")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_1, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_1[i], **tols)
logging.info("[test_transformer_layer]: fused attn backend 0 vs 2")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_2, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_2[i], **tols)
elif (
len(fused_attn_backends) == 1 and
FusedAttnBackend["CK"] in fused_attn_backends
):
logging.info("[test_dot_product_attention]: CK fused attn V2 vs V3")
torch.testing.assert_close(fused_attn_fwd, fused_attn_fwd_1, **tols)
for i, _ in enumerate(fused_attn_bwd):
torch.testing.assert_close(fused_attn_bwd[i], fused_attn_bwd_1[i], **tols)


@pytest.mark.skipif(get_cudnn_version() < (8, 9, 1), reason="cuDNN 8.9.1+ is required.")
Expand Down