Files
K3/kda/_fla/utils/_compat.py
T
dela 584f7e9e73 Initial K3 snapshot: 0.5B KDA/MLA/MoE train path
Standalone tree split from LLMRL/projects/kda. Includes Triton dt_bias
backward fix, train_k3 --preset 0.5b, SFT, Docker runtime, and tests.
2026-08-25 14:43:17 +08:00

66 lines
2.3 KiB
Python

# Copyright (c) 2023-2026, Songlin Yang, Yu Zhang, Zhiyuan Li
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# For a list of all contributors, visit:
# https://github.com/fla-org/flash-linear-attention/graphs/contributors
import functools
import importlib.metadata
import inspect
import logging
import os
import shutil
from importlib.util import find_spec
from pathlib import Path
import triton
from packaging import version as package_version
from ._config import FLA_CACHE_RESULTS
logger = logging.getLogger(__name__)
TRITON_ABOVE_3_4_0 = package_version.parse(triton.__version__) >= package_version.parse("3.4.0")
TRITON_ABOVE_3_5_1 = package_version.parse(triton.__version__) >= package_version.parse("3.5.1")
TRITON_ABOVE_3_7_1 = package_version.parse(triton.__version__) >= package_version.parse("3.7.1")
SUPPORTS_AUTOTUNE_CACHE = "cache_results" in inspect.signature(triton.autotune).parameters
autotune_cache_kwargs = {"cache_results": FLA_CACHE_RESULTS} if SUPPORTS_AUTOTUNE_CACHE else {}
@functools.cache
def find_spec_cached(name):
return find_spec(name)
@functools.cache
def has_usable_nvcc() -> bool:
"""Whether a usable nvcc compiler is available for TileLang's JIT.
Mirrors the guesses in ``tilelang.env._find_cuda_home`` (env
CUDA_HOME/CUDA_PATH, nvcc on PATH, the ``nvidia-cuda-nvcc`` wheel,
/usr/local/cuda), but verifies the nvcc binary actually exists —
only ``nvidia-cuda-nvcc`` >= 13.0 ships it, the ``-cu12`` variant
installs just ptxas.
"""
cuda_home = os.environ.get("CUDA_HOME") or os.environ.get("CUDA_PATH")
if cuda_home is not None and (Path(cuda_home) / "bin" / "nvcc").exists():
return True
if shutil.which("nvcc") is not None:
return True
try:
files = importlib.metadata.files("nvidia-cuda-nvcc") or []
except importlib.metadata.PackageNotFoundError:
files = []
if any(f.name in ("nvcc", "nvcc.exe") for f in files):
return True
if (Path("/usr/local/cuda") / "bin" / "nvcc").exists():
return True
logger.info(
"[FLA Backend] TileLang is installed but no usable nvcc compiler was found; falling back to Triton. "
"Install a CUDA toolkit or nvidia-cuda-nvcc, or set FLA_TILELANG=0 to disable TileLang explicitly."
)
return False