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License: Apache License 2.0
French to English translator on character level implemented by Keras
License: Apache License 2.0
line 75, In ByteNet-Keras/ByteNet_train.py
encoder2 has to input by encoder2. but you wrote input_tensor.
you implemented byte-net so well, but i think you just made a small mistake.
Hi @liangstein,
Thanx a lot for your implementation, it helped me a lot to understand bytenet.
I have a technical question for your implementation. I see that you use kernel_size=3 in your encoder's Convolutions, which makes absolute sense with padding='same' in order to condition each timestep (t) based on timesteps (t-1, t+1)*. My question is why the kernel_size=3 in decoder's Convolutions, where you use padding='causal' and you only need to condition based on the previous timestep (t-1). Is this the correct size or you should probably use kernel_size=2 in order to avoid including extra timesteps (e.g., timestep t-2)?
Thanx, Ilias
Originally posted by @liangstein in https://github.com/liangstein/ByteNet-Keras/issue_comments#issuecomment-425307037
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