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[xpu][test] Enable MoE MX format kernels and tensor tests for Intel XPU #4342

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[xpu][test] Enable MoE MX format kernels and tensor tests for Intel XPU #4342

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24 changes: 17 additions & 7 deletions test/prototype/moe_training/ep/test_kernels.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,17 +7,29 @@
import pytest
import torch

from torchao.utils import is_cuda_version_at_least, is_sm_at_least_100
from torchao.utils import is_cuda_version_at_least, is_sm_at_least_100, is_XPU

if not (
_is_xpu = is_XPU()
_is_compatible_cuda = (
torch.cuda.is_available()
and is_sm_at_least_100()
and is_cuda_version_at_least(12, 8)
):
pytest.skip("Test requires CUDA 12.8+ with SM >= 100", allow_module_level=True)
)
if not (_is_xpu or _is_compatible_cuda):
pytest.skip(
"Test requires XPU or CUDA 12.8+ with SM >= 100", allow_module_level=True
)

from torchao.prototype.moe_training.ep.kernels import generate_permute_indices
from torchao.prototype.moe_training.ep.permute import _triton_permute_bwd
from torchao.utils import get_available_devices

_DEVICES = get_available_devices()[1:]


@pytest.fixture(scope="module", params=_DEVICES)
def device(request):
return request.param


@pytest.mark.parametrize(
Expand All @@ -41,10 +53,8 @@
],
)
def test_triton_permute_bwd(
num_tokens, hidden_dim, num_local_experts, ep_degree, alignment
num_tokens, hidden_dim, num_local_experts, ep_degree, alignment, device
):
device = "cuda"

# Generate realistic permutation indices using generate_permute_indices
# Simulate token distribution across experts
tokens_per_expert_group = torch.randint(
Expand Down
24 changes: 18 additions & 6 deletions test/prototype/moe_training/ep/test_permute.py
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Original file line number Diff line number Diff line change
@@ -1,23 +1,35 @@
import pytest
import torch

from torchao.utils import is_cuda_version_at_least, is_sm_at_least_100
from torchao.utils import is_cuda_version_at_least, is_sm_at_least_100, is_XPU

if not (
_is_xpu = is_XPU()
_is_compatible_cuda = (
torch.cuda.is_available()
and is_sm_at_least_100()
and is_cuda_version_at_least(12, 8)
):
pytest.skip("Test requires CUDA 12.8+ with SM >= 100", allow_module_level=True)
)

if not (_is_xpu or _is_compatible_cuda):
pytest.skip(
"Test requires XPU or CUDA 12.8+ with SM >= 100", allow_module_level=True
)

from torchao.prototype.moe_training.ep import permute_mxfp8_fwd_hp_bwd
from torchao.prototype.moe_training.ep.permute import permute_and_pad
from torchao.prototype.mx_formats.mx_tensor import MXTensor
from torchao.quantization.utils import compute_error
from torchao.utils import get_available_devices

_DEVICES = get_available_devices()[1:]


@pytest.fixture(scope="module", params=_DEVICES)
def device(request):
return request.param


def test_mxfp8_permute_forward():
device = "cuda"
def test_mxfp8_permute_forward(device: str):
tokens = 64
dim = 128
num_experts = 8
Expand Down
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