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base repository: IBM/pytorch-seq2seq
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head repository: IBM/pytorch-seq2seq
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Commits on Sep 28, 2017
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* Use torchtext from pipe. * Fixed torch text sorting order.
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attention is not required when only using teacher forcing in decoder (#…
…90) * attention is not required when only using teacher forcing in decoder
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Commits on Nov 1, 2017
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Fixed field arguments validation.
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Merge branch 'master' into copy
# Conflicts: # seq2seq/models/DecoderRNN.py # seq2seq/models/TopKDecoder.py # tests/test_topkdecoder.py
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Commits on Nov 14, 2017
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shuffle the training data (#97)
* 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
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Commits on Nov 20, 2017
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fix example of inflate function in TopKDecoer.py (#98)
* fix example of inflate function in TopKDecoer.py
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Fix hidden_layer size for one-directional decoder (#99)
* 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`.
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Adapt load to allow CPU loading of GPU models (#100)
* 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.
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Commits on Dec 4, 2017
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Fix wrong parameter use on DecoderRNN (#103)
* Fix wrong parameter use on DecoderRNN
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Merge branch 'master' into develop
# Conflicts: # seq2seq/models/TopKDecoder.py # seq2seq/trainer/supervised_trainer.py
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Commits on Jan 4, 2018
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Upgrade to pytorch-0.3.0 (#111)
* Upgrade to pytorch-0.3.0 * Use pytorch 3.0 in travis env.
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Commits on Jan 18, 2018
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Implementing the predict_n method. Using the beam search outputs it r…
…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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Commits on Jan 21, 2018
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