perf: run ablations for the paper #1408
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![github-actions[bot]](https://avatars.githubusercontent.com/in/15368?s=60&v=4){kind=small}
DeepONet
Fourier Neural Operator
Need to investigate if the pass pipelines are being correctly set the results seem quite strange honestly |
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FNO case is heavily dominated by FFTs so nothing much we can do there, but the gradients with passes enabled being consistently slower seems off |
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I assume this is all straight line (no control flow like while), and we have no fft specific optimizations yet in which case this also becomes a question of how well xla’s allocation and other passes may recognize certain patterns |
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But also concurrently we built the passes for the primal and post jax differentiation , so we may be missing optimizations relevant to enzyme generated programs |
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