Dropout error using external embeddings about pytorch-seq2seq HOT 3 CLOSED

@CoderINusE try increasing the number of layers in your model. PyTorch doesn't allow adding droupout in a single layer RNN. I'm not sure what it has to do with fasttext embeddings.

from pytorch-seq2seq.

I'm not changing number of layers in the model. I just have my pre-trained vectors of English words with hidden size of 300. Then I load them into input_vocab and output_vocab using torchtext.vocab.FastText with max_vectors=5000 and trying to overload embedding and update_embedding. The only file that I'm changing is the examples/sample.py. If it gives me the error and I should change something in the architecture than it is the bug or it should be stated in README.

from pytorch-seq2seq.

@CoderINusE it is not a bug. This is a framework written in PyTorch and PyTorch does'nt allow applying dropout if there is only one layer (last layer) in the RNN as stated in the docs under dropout option. You could also have a look at the source code where the warning is explicitly mentioned:

https://github.com/pytorch/pytorch/blob/master/torch/nn/modules/rnn.py#L43

and also on our develop branch:

https://github.com/IBM/pytorch-seq2seq/blob/develop/seq2seq/models/base_rnn.py#L45

from pytorch-seq2seq.