Add AutoTP=2 smoke test config and script - #1004
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Verified on 2x RTX 5090 with Qwen2.5-0.5B-Instruct: - Student and teacher both use AutoTP=2 - HybridEngineRollout.generate() produces identical output on both ranks - OPSD training loop runs end-to-end with temperature=0 (greedy) - No DistributedSampler in pure-TP mode (all ranks see same data) - Teacher uses ZeRO-0 when AutoTP is enabled (AutoTP+ZeRO-3 not supported) Requires DeepSpeed >= commit 53a2ac4 (AutoTP KV cache consistency fix). Signed-off-by: Guokai Ma <guokai.ma@intel.com> Signed-off-by: Guokai Ma <guokai.ma@gmail.com>
PKUWZP
self-requested a review
July 21, 2026 14:43
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Note DeepSpeed AutoTP for now does not have column parallel in |
- teacher.py: drop the stale guard that forced ZeRO-0 whenever AutoTP was enabled. AutoTP + ZeRO-3 is now supported by recent DeepSpeed, so the two can be combined. Also gate ZeRO-3 on a real data-parallel dimension (world_size > autotp_size) instead of world_size > 1, so pure-TP runs (autotp_size == world_size, no offload) no longer pay needless ZeRO-3 per-forward gather overhead. - configs/smoke_ds_zero3_offload_autotp2.json: student ZeRO-3 + param/optimizer offload + AutoTP=2 DeepSpeed config. - configs/smoke_hybrid_autotp_zero3.json: OPSD smoke with teacher and student both on AutoTP=2 + ZeRO-3 (teacher offload). - test_teacher_autotp_zero3.py / test_student_autotp_zero3.py: isolated AutoTP + ZeRO-3 probes (env-tunable OFFLOAD/AUTOTP). Verified on 4x RTX 4080 SUPER with Qwen2.5-0.5B/1.5B-Instruct: - Teacher AutoTP=2 + ZeRO-3 (offload and 2x2) runs on upstream DeepSpeed master. - Student AutoTP=2 + ZeRO-3 (offload and 2x2) and the full OPSD smoke (teacher + student) require DeepSpeed PR #8168 (AutoTP + ZeRO-3 checkpoint consolidation). Signed-off-by: Guokai Ma <guokai.ma@intel.com> Signed-off-by: Guokai Ma <guokai.ma@gmail.com>
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Now teacher support autotp + zero3, including autotp + zero3 offload. |
tohtana
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Jul 29, 2026
| # and deadlock the TP all-reduce. Only shard when there is real DP. | ||
| tp_size = student_engine.autotp_size() if hasattr(student_engine, 'autotp_size') else 1 | ||
| dp_size = dist_world_size() // tp_size | ||
| sampler = DistributedSampler(dataset, shuffle=cfg.data.shuffle) if dp_size > 1 else None |
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Don't we need to pass dp size and rank to DistributedSampler?
| from deepspeed.accelerator import get_accelerator | ||
| from transformers import AutoModelForCausalLM | ||
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| MODEL = os.environ.get("STUDENT_MODEL", "/root/autodl-tmp/models/Qwen2.5-0.5B-Instruct") |
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We could replace it with HF model ID
| from teacher import TeacherWrapper | ||
| from config import TeacherConfig | ||
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| MODEL = os.environ.get("TEACHER_MODEL", "/root/autodl-tmp/models/Qwen2.5-1.5B-Instruct") |
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We could replace it with HF model ID
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Verified on 2x RTX 5090 with Qwen2.5-0.5B-Instruct:
Requires DeepSpeed >= commit 53a2ac4 (AutoTP KV cache consistency fix).