[NPU] Add qwen3-4b fully_async script

examples/fully_async/run-qwen3-4B-fully_async-npu.sh

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+#!/bin/bash
+# Tiny end-to-end fully-async GRPO example using Qwen3-4B-Instruct on the
+# dapo-math-17k dataset. Designed to run on a single 4-GPU node in a few minutes
+#
+# Prerequisites:
+#   /root/models/Qwen3-4B/             (HF checkpoint)
+#   /root/datasets/dapo-math-17k/dapo-math-17k.jsonl
+
+# clean any leftover ray/vllm
+pkill -9 -f '[v]llm serve|VLL[M]::'
+pkill -9 -f VLLM
+sleep 3
+ray stop --force
+pkill -9 ray
+pkill -9 python
+sleep 3
+pkill -9 ray
+pkill -9 python
+pkill -9 redis
+
+set -ex
+
+export PYTHONUNBUFFERED=1
+export ASCEND_RT_VISIBLE_DEVICES=0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15
+export RAY_EXPERIMENTAL_NOSET_ASCEND_RT_VISIBLE_DEVICES=1
+export RAY_USE_UVLOOP=0 # upstream: Ray's uvloop integration has caused intermittent async actor issues.
+export CUDA_DEVICE_MAX_CONNECTIONS=1
+export HCCL_HOST_SOCKET_PORT_RANGE=60000-60050
+export HCCL_NPU_SOCKET_PORT_RANGE=61000-61050
+export HYDRA_FULL_ERROR=1
+export DISABLE_L2_CACHE=1
+export VLLM_ASCEND_ENABLE_NZ=0
+export VLLM_USE_AOT_COMPILE=0
+export PYTHONPATH="/root/Megatron-Bridge/src:/root/Megatron-LM/:${PYTHONPATH:-}"
+
+unset http_proxy https_proxy HTTP_PROXY HTTPS_PROXY
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" &>/dev/null && pwd)"
+source "${SCRIPT_DIR}/../../scripts/models/qwen3-4B.sh"
+
+MODEL_DIR=${MODEL_DIR:-/root/models/Qwen3-4B}
+DATA_PATH=${DATA_PATH:-/root/datasets/dapo-math-17k/dapo-math-17k.jsonl}
+
+CKPT_ARGS=(
+   --hf-checkpoint "${MODEL_DIR}"
+   --load "${MODEL_DIR}"
+   --ref-load "${MODEL_DIR}"
+   --megatron-to-hf-mode bridge
+   --save /tmp/vime_fully_async_demo/
+   --save-interval 9999
+)
+
+ROLLOUT_ARGS=(
+   # ↓↓↓ This is the only knob you need to flip to go fully-async ↓↓↓
+   --rollout-function-path vime.rollout.fully_async_rollout.generate_rollout_fully_async
+
+   --prompt-data "${DATA_PATH}"
+   --input-key prompt
+   --label-key label
+   --apply-chat-template
+   --rollout-shuffle
+   --rm-type math
+   --num-rollout 200
+   --rollout-batch-size 32
+   --n-samples-per-prompt 8
+   --rollout-max-response-len 2048
+   --rollout-temperature 1
+   --global-batch-size 256
+   --balance-data
+)
+
+PERF_ARGS=(
+   --tensor-model-parallel-size 2
+   --sequence-parallel
+   --pipeline-model-parallel-size 1
+   --context-parallel-size 1
+   --expert-model-parallel-size 1
+   --expert-tensor-parallel-size 1
+   --recompute-granularity full
+   --recompute-method uniform
+   --recompute-num-layers 1
+   --use-dynamic-batch-size
+   --max-tokens-per-gpu 8192
+)
+
+GRPO_ARGS=(
+   --advantage-estimator grpo
+   --kl-loss-coef 0.00
+   --kl-loss-type low_var_kl
+   --kl-coef 0.00
+   --entropy-coef 0.00
+   --eps-clip 0.2
+   --eps-clip-high 0.28
+)
+
+OPTIMIZER_ARGS=(
+   --optimizer adam
+   --lr 1e-6
+   --lr-decay-style constant
+   --weight-decay 0.1
+   --adam-beta1 0.9
+   --adam-beta2 0.98
+   --optimizer-cpu-offload
+   --overlap-cpu-optimizer-d2h-h2d
+   --use-precision-aware-optimizer
+)
+
+VLLM_ARGS=(
+   --rollout-num-gpus-per-engine 2
+   --vllm-gpu-memory-utilization 0.6
+)
+
+MISC_ARGS=(
+   --attention-dropout 0.0
+   --hidden-dropout 0.0
+   --accumulate-allreduce-grads-in-fp32
+   --attention-softmax-in-fp32
+   --attention-backend flash
+   --use-flash-attn
+)
+
+ray start --head --node-ip-address 127.0.0.1 --disable-usage-stats
+
+# fully-async splits actor / rollout onto disjoint GPUs (no colocation).
+ACTOR_GPUS=2
+ROLLOUT_GPUS=2
+
+ray job submit --address="http://127.0.0.1:8265" \
+   -- python3 train_async.py \
+   --actor-num-nodes 1 \
+   --actor-num-gpus-per-node "${ACTOR_GPUS}" \
+   --rollout-num-gpus "${ROLLOUT_GPUS}" \
+   ${MODEL_ARGS[@]} \
+   ${CKPT_ARGS[@]} \
+   ${ROLLOUT_ARGS[@]} \
+   ${OPTIMIZER_ARGS[@]} \
+   ${GRPO_ARGS[@]} \
+   ${PERF_ARGS[@]} \
+   ${VLLM_ARGS[@]} \
+   ${MISC_ARGS[@]}