| #!/bin/bash |
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| export DEBUG_MODE=true |
| export LOG_PATH="./debug_log_2b.txt" |
| export CUDA_VISIBLE_DEVICES=0 |
| export MAIN_PROCESS_PORT=29507 |
| export NCCL_DEBUG=INFO |
| export NCCL_IB_DISABLE=1 |
| export NCCL_P2P_DISABLE=1 |
| export NCCL_ASYNC_DISABLE=1 |
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| REASONER_MODEL="Qwen/Qwen2.5-1.5B-Instruct" |
| WEAVER_MODEL="Qwen/Qwen2.5-1.5B-Instruct" |
| TRIGGER_MODEL="Qwen/Qwen2.5-1.5B-Instruct" |
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| DATASET_NAME="kodcode" |
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| TRAIN_METHOD="grpo" |
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| MAX_PROMPT_AUG_NUM=1 |
| MAX_INFERENCE_AUG_NUM=5 |
| PROMPT_LATENTS_LEN=8 |
| INFERENCE_LATENTS_LEN=8 |
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| LOAD_WEAVER_PATH="" |
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| python -m accelerate.commands.launch \ |
| --config_file=configs/zero2.yaml \ |
| main.py \ |
| --cfg-path configs/latent_memory/${DATASET_NAME}.yaml \ |
| --options \ |
| model.model_name ${REASONER_MODEL} \ |
| model.load_model_path ${LOAD_WEAVER_PATH} \ |
| model.max_prompt_aug_num ${MAX_PROMPT_AUG_NUM} \ |
| model.max_inference_aug_num ${MAX_INFERENCE_AUG_NUM} \ |
| model.weaver.model_name ${WEAVER_MODEL} \ |
| model.weaver.prompt_latents_len ${PROMPT_LATENTS_LEN} \ |
| model.weaver.inference_latents_len ${INFERENCE_LATENTS_LEN} \ |
| model.trigger.model_name ${TRIGGER_MODEL} \ |
| model.trigger.active True \ |
| datasets.mode ${TRAIN_METHOD} \ |
| run.mode train \ |
| run.train_weaver False \ |
| run.train_trigger True \ |
| run.train_trigger_method ${TRAIN_METHOD} \ |
| run.trigger.grpo.per_device_train_batch_size 8 \ |
| run.trigger.grpo.per_device_eval_batch_size 8 \ |
| run.trigger.grpo.num_train_epochs 1 \ |
| run.trigger.grpo.num_generations 8 \ |
| run.trigger.grpo.gradient_accumulation_steps 4 \ |
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