Comments (6)
If you want to concatenate fw/bw states after each layer, check this out: https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/stack_bidirectional_rnn
from tensorflow-seq2seq-tutorials.
I had a look at the stack_bidirectional_rnn. But I don't see the argument for the num_layers ?
I am little confused. Without num_layers how it will decide how many layers to stack ?
from tensorflow-seq2seq-tutorials.
You should pass multiple cells as cells_fw
and cells_fw
, one per layer. This is based on the description, I did not use it.
from tensorflow-seq2seq-tutorials.
Got it. But that function is not in TF 1.0. Any idea for TF 1.0 ?
from tensorflow-seq2seq-tutorials.
Same thing, but manually concatenate/stack layers in a for loop.
from tensorflow-seq2seq-tutorials.
Hi, Sorry for badgering but I would really appreciate if you can respond to this related post by me
https://stackoverflow.com/questions/44498771/multilayered-encoder-output-state-to-multilayered-decoder-in-seq2seq-model
from tensorflow-seq2seq-tutorials.
Related Issues (20)
- new changes in tensorflow HOT 4
- My own embedding HOT 1
- Potential bug of the dynamic_decoder HOT 2
- OOM error after running some batches HOT 3
- Beam search toy example
- Using the same weights in two different positions seems wrong
- module 'tensorflow.contrib.seq2seq' has no attribute 'prepare_attention' HOT 2
- there is no input argument when loop_fn method is called. HOT 1
- Increasing max sequence length and vocab size HOT 1
- How does inference work? Always getting same predictions HOT 2
- Duplicated computation of decoder outputs?
- toy task-example1-error
- testing
- Attempted an implementation
- good job
- Logits and labes have different shapes when computing cross-entropy loss HOT 1
- decoder input
- ask for help
- How to connect multilayered encoder to decoder?
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