[DeepSpeed]RuntimeError: output tensor must have the same type as input tensor
最近在跑chatglm2的sft的时候出现了下面的错误，我的运行方式是bf16, deepspeed zero3，因为担心fp16会有很多的nan.
File "/home/suser/.conda/envs/llm/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl
return func(*args, **kwargs)
File "/home/suser/.conda/envs/llm/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 2532, in all_gather_into_tensor
result = forward_call(*args, **kwargs)
File "/home/suser/.cache/huggingface/modules/transformers_modules/chatglm2-6b/modeling_chatglm.py", line 805, in forward
inputs_embeds = self.embedding(input_ids)
File "/home/suser/.conda/envs/llm/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1538, in _call_impl
work = group._allgather_base(output_tensor, input_tensor)
RuntimeError: output tensor must have the same type as input tensor
解决方法
在stage3 config里面加入bf16就行了。
{ "bf16": { "enabled": true },
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"gradient_accumulation_steps": "auto",
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupLR",
"params": {
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto"
}
},
"fp16": {
"enabled": "auto"
},
"zero_optimization": {
"stage": 3,
"overlap_comm": true,
"contiguous_gradients": true,
"sub_group_size": 1e9,
"reduce_bucket_size": "auto",
"stage3_prefetch_bucket_size": "auto",
"stage3_param_persistence_threshold": "auto",
"stage3_max_live_parameters": 1e9,
"stage3_max_reuse_distance": 1e9,
"stage3_gather_16bit_weights_on_model_save": true
}
}
参考文献
[BUG]RuntimeError: output tensor must have the same type as input tensor