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update test case
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.github/workflows/e2e_ppo_trainer_veomni_vllm.yml

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@@ -123,10 +123,18 @@ jobs:
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run: |
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ray stop --force
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python3 examples/data_preprocess/gsm8k.py --local_dataset_path ${HOME}/models/hf_data/gsm8k
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- name: Prepare GEO3K dataset
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run: |
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ray stop --force
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python3 examples/data_preprocess/geo3k.py --local_dataset_path ${HOME}/models/hf_data/geo3k
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- name: Running GSM8K E2E training tests on 8 L20 GPUs with veomni engine (FSDP_SIZE=4, USP=2)
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run: |
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ray stop --force
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VAL_BEFORE_TRAIN=True TEST_FREQ=1 SAVE_FREQ=1 SAVE_HF_MODEL=True VERL_EXP_NAME="qwen2.5-0.5b-function-reward-minimal-fsdp-size8" bash tests/special_e2e/run_ppo_trainer_veomni.sh
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VAL_BEFORE_TRAIN=True NUM_GPUS=8 FSDP_SIZE=4 SP_SIZE=2 EP_SIZE=1 VERL_EXP_NAME="qwen2.5-0.5b-function-reward-minimal-fsdp-size4" bash tests/special_e2e/run_ppo_trainer_veomni.sh
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- name: Running GEO3K E2E training tests on 8 L20 GPUs with veomni engine (FSDP_SIZE=4, USP=2)
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run: |
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ray stop --force
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MODEL_ID=Qwen/Qwen3-VL-2B-Instruct TRAIN_FILES=${HOME}/data/geo3k/train.parquet VAL_FILES=${HOME}/data/gsm8k/test.parquet VAL_BEFORE_TRAIN=True NUM_GPUS=8 FSDP_SIZE=4 SP_SIZE=2 EP_SIZE=1 VERL_EXP_NAME="qwen2.5-0.5b-function-reward-minimal-fsdp-size4" bash tests/special_e2e/run_ppo_trainer_veomni.sh
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cleanup:
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runs-on: ubuntu-latest

tests/special_e2e/run_ppo_trainer_veomni.sh

Lines changed: 12 additions & 4 deletions
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@@ -8,6 +8,12 @@ MODEL_PATH=${MODEL_PATH:-${HOME}/models/${MODEL_ID}}
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TRAIN_FILES=${TRAIN_FILES:-${HOME}/data/gsm8k/train.parquet}
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VAL_FILES=${VAL_FILES:-${HOME}/data/gsm8k/test.parquet}
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VAL_BEFORE_TRAIN=${VAL_BEFORE_TRAIN:-False}
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NUM_GPUS=${NUM_GPUS:-8}
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FSDP_SIZE=${FSDP_SIZE:-4}
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SP_SIZE=${SP_SIZE:-2}
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EP_SIZE=${EP_SIZE:-2}
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VERL_EXP_NAME=${VERL_EXP_NAME:-qwen2.5-0.5b-function-reward-minimal-fsdp-size8}
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python3 -m verl.trainer.main_ppo --config-path=config\
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--config-name="ppo_veomni_trainer.yaml" \
@@ -33,8 +39,9 @@ python3 -m verl.trainer.main_ppo --config-path=config\
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actor_rollout_ref.actor.kl_loss_type=low_var_kl \
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actor_rollout_ref.actor.entropy_coeff=0 \
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actor_rollout_ref.actor.use_torch_compile=False \
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actor_rollout_ref.actor.veomni.data_parallel_size=4 \
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actor_rollout_ref.actor.veomni.ulysses_parallel_size=2 \
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actor_rollout_ref.actor.veomni.data_parallel_size="${FSDP_SIZE}" \
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actor_rollout_ref.actor.veomni.ulysses_parallel_size="${SP_SIZE}" \
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actor_rollout_ref.actor.veomni.expert_parallel_size="${EP_SIZE}" \
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actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=1 \
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actor_rollout_ref.ref.veomni.param_offload=True \
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actor_rollout_ref.ref.use_torch_compile=False \
@@ -54,8 +61,9 @@ python3 -m verl.trainer.main_ppo --config-path=config\
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trainer.critic_warmup=0 \
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trainer.logger=console \
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trainer.project_name='verl_grpo_example_gsm8k' \
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trainer.experiment_name='qwen25_05b_function_rm' \
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trainer.n_gpus_per_node=8 \
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trainer.experiment_name="${VERL_EXP_NAME}" \
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trainer.n_gpus_per_node="${NUM_GPUS}" \
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trainer.val_before_train="${VAL_BEFORE_TRAIN}" \
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trainer.nnodes=1 \
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trainer.save_freq=-1 \
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trainer.test_freq=-1 \

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