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Release 0.1.6 #137
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Release 0.1.6 #137
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* Fixed topk decoder.
* Use torchtext from pipe. * Fixed torch text sorting order.
…90) * attention is not required when only using teacher forcing in decoder
* 0.1.5 (#91) * Modified parameter order of DecoderRNN.forward (#85) * Updated TopKDecoder (#86) * Fixed topk decoder. * Use torchtext from pipy (#87) * Use torchtext from pipe. * Fixed torch text sorting order. * attention is not required when only using teacher forcing in decoder (#90) * attention is not required when only using teacher forcing in decoder * Updated docs and version. * Fixed code style. * shuffle the training data
* fix example of inflate function in TopKDecoer.py
* Fix hidden_layer size for one-directional decoder Hidden layer size of the decoder was given `hidden_size * 2 if bidirectional else 1`, resulting in a dimensionality error for non-bidirectional decoders. Changed `1` to `hidden_size`.
* Adapt load to allow CPU loading of GPU models Add storage parameter to torch.load to allow loading models on a CPU that are trained on the GPU, depending on availability of cuda.
* Fix wrong parameter use on DecoderRNN
# Conflicts: # seq2seq/models/TopKDecoder.py # seq2seq/trainer/supervised_trainer.py
* Upgrade to pytorch-0.3.0 * Use pytorch 3.0 in travis env.
…eturns several seqs for a given seq (#116) * Adding a predictor method to return n predicted seqs for a src_seq input (intended to be used along to Beam Search using TopKDecoder)
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