mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-06-08 15:30:05 +00:00
07fd9328fa
- Create python/sft/ with 11 modules: base, amx, arch, autograd, layer, lora, weights, wrapper, dist_utils, config, __init__ - Move BaseSFTMoEWrapper + buffer management into sft/base.py (template method pattern: subclass provides _make_forward/backward_task) - Move AMXSFTMoEWrapper into sft/amx.py (thinner, no buffer logic) - Move from accelerate kt_moe.py: KTMoEFunction, KTMoELayerWrapper, MOEArchConfig, PEFT LoRA adaptation, weight extraction, wrapping - Add KTConfig dataclass (DeepSpeed pattern: opaque config passthrough) - Add _get_kt_config() with old→new field name compat conversion - Rename forward_sft→forward, submit_forward_sft→submit_forward, sync_forward_sft→sync_forward (Python only, C++ binding names unchanged) - Delete dump utilities from sft_moe.hpp (-526) and moe-sft-tp.hpp (-78) - Delete experts_sft.py and utils/amx_sft.py (moved to sft/) - Remove SFT stubs from BaseMoEWrapper (experts_base.py) - Lazy SFT import in __init__.py and experts.py (inference isolation) - Delete all lifecycle/debug logging (~500 lines) Verified: Qwen3-235B 4GPU AMXBF16 training, 3 steps loss converges.
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
# KT-Kernel: High-performance kernel operations for KTransformers
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# SPDX-License-Identifier: Apache-2.0
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"""
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KT-Kernel provides high-performance kernel operations for KTransformers,
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including CPU-optimized MoE inference with AMX, AVX, and KML support.
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The package automatically detects your CPU capabilities and loads the optimal
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kernel variant (AMX, AVX512, or AVX2) at runtime.
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Example usage:
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>>> from kt_kernel import KTMoEWrapper
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>>> wrapper = KTMoEWrapper(
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... layer_idx=0,
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... num_experts=8,
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... num_experts_per_tok=2,
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... hidden_size=4096,
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... moe_intermediate_size=14336,
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... num_gpu_experts=2,
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... cpuinfer_threads=32,
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... threadpool_count=2,
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... weight_path="/path/to/weights",
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... chunked_prefill_size=512,
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... method="AMXINT4"
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... )
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Check which CPU variant is loaded:
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>>> import kt_kernel
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>>> print(kt_kernel.__cpu_variant__) # 'amx', 'avx512', or 'avx2'
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Environment Variables:
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KT_KERNEL_CPU_VARIANT: Override automatic detection ('amx', 'avx512', 'avx2')
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KT_KERNEL_DEBUG: Enable debug output ('1' to enable)
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"""
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from __future__ import annotations
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# Detect CPU and load optimal extension variant
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from ._cpu_detect import initialize as _initialize_cpu
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_kt_kernel_ext, __cpu_variant__ = _initialize_cpu()
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# Make the extension module available to other modules in this package
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import sys
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sys.modules["kt_kernel_ext"] = _kt_kernel_ext
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# Also expose kt_kernel_ext as an attribute for backward compatibility
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kt_kernel_ext = _kt_kernel_ext
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# Import main API
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from .experts import KTMoEWrapper
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def __getattr__(name):
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if name == "AMXSFTMoEWrapper":
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try:
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from .sft.amx import AMXSFTMoEWrapper
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return AMXSFTMoEWrapper
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except (ImportError, AttributeError):
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return None
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raise AttributeError(f"module 'kt_kernel' has no attribute {name!r}")
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# Read version from package metadata (preferred) or fallback to project root
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try:
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# Try to get version from installed package metadata (works in installed environment)
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from importlib.metadata import version, PackageNotFoundError
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try:
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__version__ = version("kt-kernel")
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except PackageNotFoundError:
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# Package not installed, try to read from source tree version.py
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import os
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_root_version_file = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "version.py")
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if os.path.exists(_root_version_file):
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_version_ns = {}
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with open(_root_version_file, "r", encoding="utf-8") as f:
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exec(f.read(), _version_ns)
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__version__ = _version_ns.get("__version__", "0.4.3")
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else:
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__version__ = "0.4.3"
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except ImportError:
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# Python < 3.8, fallback to pkg_resources or hardcoded version
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try:
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from pkg_resources import get_distribution, DistributionNotFound
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try:
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__version__ = get_distribution("kt-kernel").version
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except DistributionNotFound:
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__version__ = "0.4.3"
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except ImportError:
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__version__ = "0.4.3"
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__all__ = ["KTMoEWrapper", "AMXSFTMoEWrapper", "kt_kernel_ext", "__cpu_variant__", "__version__"]
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