XLA-TPU - Extremely slow

I am trying XLA on the TPUs for the first time. Have been running all my other training on Flax. I need to move a Whisper finetuning script from GPU to TPU (and finally TPU Pods). I am using a simple TPU VM v4 .

I am able to set up the TPU. The sample scripts run at correct speed. I am also able to start my script without any errors. For me it seems that the xla-hook-script is initiated, and I set the variable “xla”=True in the Trainer script. No error messages. But everything is extremely slow. On a standard A6000 I am able to run around 16s/it. On the TPU I am running 800s/it! It is as if I am training on CPU.

Could anyone give me some basic tips in how to debug this? If you are interested, the script is available here: NbAiLab/whisper · Hugging Face

Hi pere,

Such a slow down with PyTorch/XLA usually indicates there are excessive recompilations or CPU fallbacks.

Could you trying out the steps in the pytorch/xla troubleshooting guide, especially the “Perform A Auto-Metrics Analysis” and the “Get A Metrics Report” parts. It’s usually a good start point to show if excessive recompilations or CPU fallbacks are happening.

Also, would you mind opening a github issue under GitHub - pytorch/xla: Enabling PyTorch on Google TPU for better tracking purpose?


Thanks you. I have opened an issue here: XLA-TPU - Extremely slow · Issue #4203 · pytorch/xla · GitHub

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