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The first item should definitely be fixed, but for the second one, there are some differences between implementations. What we usually monitor is the bleu score or log-prob of the validation set or a subset of the training set. And for both, we use models without any regularization. So, I think, the first item should be fixed, the second can be optional.
In this example, dropout is effectively ignored because:
https://github.com/mila-udem/blocks-examples/blob/12013e6c737171ce285b27381f0f5aacfdff7cab/machine_translation/__init__.py#L160
https://github.com/mila-udem/blocks-examples/blob/12013e6c737171ce285b27381f0f5aacfdff7cab/machine_translation/__init__.py#L112
is not the dropped out one, so instead one should use here cg.outputs[0].
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