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Enabling distributed training for SSL online evaluator #612
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ozan-oktay
previously approved these changes
Dec 9, 2021
ozan-oktay
approved these changes
Dec 9, 2021
Shruthi42
reviewed
Dec 10, 2021
| trainer2.fit(model, datamodule=data) | ||
| # Read the parameters and check if they are the same as what was stored in the first callback. | ||
| parameters2_after_training = list(callback2.evaluator.parameters()) | ||
| assert torch.allclose(parameters2_after_training[0], parameters1[0]) |
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Could we also check if the optimizer state is restored correctly?
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SSL online evaluator presently is not synchronizing across GPUs. Enable DDP.
Please follow the guidelines for PRs contained here. Checklist:
Added/Changed/Removed/... in the "Upcoming" section.
and if needed a motivation why that change was required.