Comments (2)
Thank you for your feedback. The current codes assume that the mode_fn
returns a single scalar value. So it will not have the problems you pointed out. Our primary intention is to write an implementation that is easy to read and modify. It depends on the users to customize their codes.
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Yep, I know it works fine when model_fn
returns a single scalar. I won't say anything if you don't handle multiple return values at all. But you do handle multiple return values here:
XMUNMT/xmunmt/utils/parallel.py
Line 90 in 84d2d70
by transposing a list of tuples to a tuple of lists, which introduces inconsistency.
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Related Issues (15)
- Where can I download the dataset and how to prepare training corpus exactly? HOT 1
- which version of tensorflow used in this system HOT 2
- Any benchmark result? HOT 4
- Questions about source code HOT 2
- What's the minimum memory requirement for the default configuration? HOT 3
- What's the exact command/dataset to reproduce a BLEU of 30.42 on test set? HOT 4
- "casual" or "causal"? HOT 3
- Loss with multiple GPUs HOT 4
- Why initialize weights from Uniform[-0.08, 0.08]? HOT 6
- pre-trained models? HOT 1
- [Question] Does dropout layer after word embedding improve neural machine translation? HOT 1
- 我配置好环境了,
- What is the belu value of Chinese English translation?
- Does this model support experiments related to GAN neural machine translation?
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