Improvements to learned round #1107
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Giuseppe5
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pablomlago
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pablomlago
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pablomlago
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pablomlago
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| loss, loss_components = block_loss(quant_outs, fp_outs) | ||
| else: | ||
| # Run block forward to obtain quant outputs | ||
| quant_outs = block_forward(block, inputs) | ||
| fp_outs = send_to_device(fp_outs, quant_outs.device) | ||
| loss, loss_components = block_loss(quant_outs.to(torch.float32), fp_outs.to(torch.float32)) |
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The code for each condition is almost exactly the same. Maybe we could have autocast(enabled=use_amp, ...) and just have a conditional for upcasting the outputs to float32 before computing the loss to avoid repeting block_forward/send_to_device/block_loss.
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I understand it's less code, but I think it will be more confusing. I am leaving as it is. Extra verbosity for clarity, I am happy with that.
pablomlago
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Reason for this PR
Fix entrypoint for learned scale
Fix training with float32 + amp
Testing Summary
NA
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devbranch.