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.

kda/_fla/utils/_compat.py

@@ -0,0 +1,65 @@
+# 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