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如果不指定device,能正常使用 llamafactory-cli api 启动,但是推理时报错:
[Error]: System Direct Memory Access (DMA) hardware execution error.
估计是310P不支持多卡运行?我如果设置了卡,运行
ASCEND_RT_VISIBLE_DEVICES=0 llamafactory-cli api examples/inference/llama3_local.yaml
会报错:
RuntimeError: call aclnnCast failed, detail:EZ1001: [PID: 3121044] 2025-03-26-15:21:21.052.218 self not implemented for DT_BFLOAT16, should be in dtype support list [DT_FLOAT16,DT_FLOAT,DT_DOUBLE,DT_INT8,DT_UINT8,DT_INT16,DT_INT32,DT_INT64,DT_UINT16,DT_UINT32,DT_UINT64,DT_BOOL,DT_COMPLEX64,DT_COMPLEX128,].
如果不指定device,能正常使用 llamafactory-cli api 启动,但是推理时报错:
[Error]: System Direct Memory Access (DMA) hardware execution error.
估计是310P不支持多卡运行?我如果设置了卡,运行
ASCEND_RT_VISIBLE_DEVICES=0 llamafactory-cli api examples/inference/llama3_local.yaml
会报错:
RuntimeError: call aclnnCast failed, detail:EZ1001: [PID: 3121044] 2025-03-26-15:21:21.052.218 self not implemented for DT_BFLOAT16, should be in dtype support list [DT_FLOAT16,DT_FLOAT,DT_DOUBLE,DT_INT8,DT_UINT8,DT_INT16,DT_INT32,DT_INT64,DT_UINT16,DT_UINT32,DT_UINT64,DT_BOOL,DT_COMPLEX64,DT_COMPLEX128,].
Reminder
System Info
llamafactory
version: 0.9.3.dev0Reproduction
如果不指定device,能正常使用
llamafactory-cli api
启动,但是推理时报错:估计是310P不支持多卡运行?我如果设置了卡,运行
会报错:
类似issue 3796。看错误信息是数据类型不能是bfloat16,而我已经在模型的config.json中修改成float16了。
其中issue 3796是重新安装了910的kernel算子,我的是310P卡,安装的算子是:
Ascend-cann-kernels-310p_8.0.0.alpha001_linux-aarch64.run
。感觉NPU的环境特别混乱,对小版本要求也很严格,而很多教程都是针对910b的。请问大家在310p卡上正确实践是什么?
Others
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