Update metrics.py - fix for ogbg pytorch #871
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It seems that the problem affecting the pytorch ogbg workloads (but only if they run for some length of time) has to do with jax/xla cpu compilation of the metrics computation. By converting the jax arrays to numpy, hopefully this can be avoided. The next step is to test on schedule free and shampoo, which I hope to do very soon.
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You can see here that schedule free now completes the run with the changes. |
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Tested again but this time only replacing the call to jax for sigmoid with numpy sigmoid. This also avoids the crash. So the problem seems to be calling jax sigmoid in pytorch. |
The problem with torchrun and jax seems to be caused by jax.nn.sigmoid.
Changed from lambda expression which pylint doesn't like.
Defined np sigmoid inside use_pytorch_ddp
Added white space before and after sigmoid_np
Fix white space
priyakasimbeg
changed the title
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It seems that the problem affecting the pytorch ogbg workloads (but only if they run for some length of time) has to do with jax/xla cpu compilation of the metrics computation. By converting the jax arrays to numpy, hopefully this can be avoided. The next step is to test on schedule free and shampoo, which I hope to do very soon.