Fix batch size in evaluation loop #16763
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LysandreJik
approved these changes
Apr 13, 2022
src/transformers/trainer.py
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| @@ -2548,6 +2548,7 @@ def evaluation_loop( | |||
| # Number of losses has been rounded to a multiple of batch_size and in a distributed training, the number of | |||
| # samplers has been rounded to a multiple of batch_size, so we truncate. | |||
| if all_losses is not None: | |||
| print(all_losses) | |||
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elusenji
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Jun 12, 2022
* Fix batch size in evaluation loop * remove debug statement
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What does this PR do?
The batch size used in the evaluation loop is wrong: it's using the per device batch size, which is different from the actual batch size when using DataParallel with more than one GPU. As a result, the
test_evaluatetest is failing for 2 GPUs (see #16716).This PR fixes that.