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better check for mxfp8 cuda kernel presence #2933

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Merged
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Sep 3, 2025
Merged

better check for mxfp8 cuda kernel presence #2933

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23 changes: 19 additions & 4 deletions torchao/prototype/mx_formats/kernels.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.

import logging
from typing import Optional, Tuple

import numpy as np
Expand Down Expand Up @@ -35,6 +36,8 @@
F32_EXP_BIAS,
)

logger = logging.getLogger(__name__)


def get_bits(x: torch.Tensor) -> str:
bits_per_byte = 8
Expand Down Expand Up @@ -1476,10 +1479,20 @@ def triton_quantize_nvfp4(
raise AssertionError("needs torch version 2.8+ and triton")


# MXFP8 CUDA kernel is only built on SM100+
mxfp8_cuda_extension_available = False
if is_sm_at_least_100():
from torchao.prototype import mxfp8_cuda

try:
# MXFP8 CUDA kernel is only built on SM100+. Furthermore,
# currently our CI runners are not SM100+, so the user needs to build
# from source.
# TODO(#2932): improve this
from torchao.prototype import mxfp8_cuda

mxfp8_cuda_extension_available = True
except ImportError:
logging.debug("Skipping import of torchao.prototype.mxfp8_cuda")

if mxfp8_cuda_extension_available:
# TODO: Make `scaling_mode` a choice (enum-like) rather than arbitrary string.
# Currently we have to use an arbitrary string because custom ops don't support enum
# params.
Expand Down Expand Up @@ -1599,4 +1612,6 @@ def mxfp8_quantize_cuda(
colwise: bool = True,
scaling_mode: str = "floor",
) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
raise NotImplementedError("needs torch version 2.8+ and sm100")
raise NotImplementedError(
"`mxfp8_quantize_cuda` needs (1) torch 2.8+ and (2) torchao built from source on a machine with CUDA capability 10.0+. Please see https://github.com/pytorch/ao/issues/2932 for more details."
)
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