Comments (2)
Hi @saxenarohit ,
There is just one layer in the example, but multiple layers can be used with ease.
The encoder is word-level, indeed. What's wrong with that? The overall idea is to apply attention to specific words, so it makes sense to work on word level rather than character or sentence level (the last one is possible though for large texts)
from tf-rnn-attention.
I see what you mean, it's not an exact implementation of an algorithm from "Hierarchical Attention Network". It's more simple example of attention use.
from tf-rnn-attention.
Related Issues (15)
- how this attention is different from attention described by Bahdanau? HOT 8
- Getting negative loss for keras "reuters" dataset HOT 1
- Regarding softmax used for attention implementation. HOT 1
- tensorflow version HOT 1
- what is the meaning of attention_size? HOT 4
- where is the previous hidden state of the decoder HOT 1
- which paper to cite? HOT 1
- What the different between this project and the one below? HOT 1
- Question for accuracy metric in toy_example.py HOT 2
- Is there any code for visualizing attention picture HOT 2
- About padding sentences HOT 1
- Finding actual length of sequence HOT 5
- Masking out padded positions for attention HOT 2
- Can't see any graph/scalar in tensorboard HOT 7
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from tf-rnn-attention.