wehub-resource-sync
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0,1'
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os.environ['ASCEND_RT_VISIBLE_DEVICES'] = '0,1'
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os.environ['MAX_PIXELS'] = '602112'
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if __name__ == '__main__':
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from swift.megatron import MegatronRLHFArguments, megatron_rlhf_main
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megatron_rlhf_main(
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MegatronRLHFArguments(
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rlhf_type='grpo',
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model='Qwen/Qwen3.5-4B',
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save_safetensors=True,
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context_parallel_size=1,
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tuner_type='lora',
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tensor_model_parallel_size=2,
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dataset=['AI-ModelScope/clevr_cogen_a_train#10000'],
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num_train_epochs=1,
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global_batch_size=128,
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vllm_mm_processor_cache_gb=0,
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micro_batch_size=4,
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steps_per_generation=4,
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num_generations=8,
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external_plugins=['examples/train/grpo/plugin/plugin.py'],
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reward_funcs=['external_r1v_acc', 'format'],
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use_vllm=True,
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vllm_mode='colocate',
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vllm_gpu_memory_utilization=0.5,
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vllm_max_model_len=8192,
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max_length=8192,
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max_completion_length=2048,
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lr=1e-4,
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bf16=True,
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beta=0.001,
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importance_sampling_level='token',
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epsilon=0.2,
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epsilon_high=0.2,
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dynamic_sample=True,
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overlong_filter=True,
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loss_type='grpo',
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sleep_level=2,
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offload_model=True,
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offload_bridge=False,
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offload_optimizer=True,
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logging_steps=1,
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recompute_granularity='full',
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recompute_method='uniform',
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recompute_num_layers=1,
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finetune=True,
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dataloader_num_workers=4,
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dataset_num_proc=4,
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no_save_optim=True,
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no_save_rng=True,
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attention_backend='flash',
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temperature=1,
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system='examples/train/grpo/prompt.txt',
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padding_free=True,
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log_completions=True,
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train_iters=100,
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eval_steps=1000,
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save_steps=1000,
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))
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