AI-Hypercomputer / AI-Hypercomputer/maxtext

Issue with gradient accumulation and expansion_factor_real_data>1

Aperta
#3,381 0 commenti 0 reazioni 1 assegnatario Rivendicata da @khatwanimohit Vedi su GitHub
bug
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Python
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Descrizione

### Bug report

`expansion_factor_real_data` > 1 generates placeholder data and then truncates the inputs in `loss_fn` to the correct size, which is supposed to eliminate the placeholder data. In gradient accumulation, from `train_step` we reshape the inputs to introduce a `gradient_accumulation_steps` dimension.

If we first truncated then reshaped, this would work correctly. However, we reshape then truncate, which means later gradient accumulation steps use the placeholder data.

I believe `max_checkify` does not catch this issue because it happens too early in the process.

(Internally we're on an older fork of this codebase, so I apologize if this has been fixed already. I looked through the relevant code and it looked like it would have the same issue)

### Logs/Output

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### Environment Information

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### Additional Context

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