yyj
e80614fc2d
* feat(sft): support distributed activation reuse policies * feat(sft): add frozen-base INT8 LoRA training * fix(sft): make INT8 expert LoRA rank-zero authoritative * fix(sft): preserve DeepSeek router LoRA routing * feat(sft): enable persistent INT8 LoRA training * perf(sft): accelerate INT8 VNNI with oneDNN BRGEMM * perf(int8): fuse oneDNN compensation into backward repack * [feat]: support BF16 expert LoRA training * [fix]: honor forwarded activation policy in SFT workers * feat(sft): add native block-FP8 routed expert LoRA * feat(sft): expose explicit expert placeholder ownership * fix(sft): publish fused adapter artifacts atomically * feat(sft): own artifact and adapter lifecycle contracts * fix(sft): harden artifact and rank-local contracts * fix(sft): auto-adapt owner before adapter restore * style(sft): keep lifecycle comments concise * fix(sft): require fused adapter manifests * test(sft): use spawn for distributed workers * fix(sft): preserve runtime checkpoint metadata * fix(sft): validate wrapped runtime configuration * fix(sft): preserve expert format provenance * fix(sft): own routed experts during device dispatch * test(sft): lock explicit quantization conflict * fix(cpu): make shared memory buffers lifetime-safe * release: prepare v0.7.0
30 lines
683 B
Python
30 lines
683 B
Python
"""Lightweight top-level package: pip install ktransformers -> installs kt-kernel.
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Extras:
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- ktransformers[sft] installs transformers-kt + accelerate-kt
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- ktransformers[sglang] installs sglang-kt
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"""
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from pathlib import Path
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from setuptools import setup
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_version_file = Path(__file__).resolve().parent / "version.py"
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_ns = {}
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exec(_version_file.read_text(), _ns)
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_v = _ns["__version__"]
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setup(
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version=_v,
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install_requires=[
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f"kt-kernel=={_v}",
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],
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extras_require={
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"sft": [
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"transformers-kt==5.6.0.post2",
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"accelerate-kt==1.14.0.post2",
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],
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"sglang": [
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f"sglang-kt=={_v}",
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],
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},
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)
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