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Aug. 16, 2018
Created
Nov. 22, 2016

NMT-Keras

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Neural Machine Translation with Keras (Theano and Tensorflow).

Library documentation: nmt-keras.readthedocs.io

Attentional recurrent neural network NMT model

alt text

Transformer NMT model

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Features (in addition to the full Keras cosmos):

Installation

Assuming that you have pip installed, run:

git clone https://github.com/lvapeab/nmt-keras
cd nmt-keras
pip install -r requirements.txt

for obtaining the required packages for running this library.

Requirements

NMT-Keras requires the following libraries:

Usage

Training

  1. Set a training configuration in the config.py script. Each parameter is commented. See the documentation file for further info about each specific hyperparameter. You can also specify the parameters when calling the main.py script following the syntax Key=Value

  2. Train!:

python main.py

Decoding

Once we have our model trained, we can translate new text using the sample_ensemble.py script. Please refer to the ensembling_tutorial for more details about this script. In short, if we want to use the models from the first three epochs to translate the examples/EuTrans/test.en file, just run:

 python sample_ensemble.py 
             --models trained_models/tutorial_model/epoch_1 \ 
                      trained_models/tutorial_model/epoch_2 \
             --dataset datasets/Dataset_tutorial_dataset.pkl \
             --text examples/EuTrans/test.en

Scoring

The score.py script can be used to obtain the (-log)probabilities of a parallel corpus. Its syntax is the following:

python score.py --help
usage: Use several translation models for scoring source--target pairs
       [-h] -ds DATASET [-src SOURCE] [-trg TARGET] [-s SPLITS [SPLITS ...]]
       [-d DEST] [-v] [-c CONFIG] --models MODELS [MODELS ...]
optional arguments:
    -h, --help            show this help message and exit
    -ds DATASET, --dataset DATASET
                            Dataset instance with data
    -src SOURCE, --source SOURCE
                            Text file with source sentences
    -trg TARGET, --target TARGET
                            Text file with target sentences
    -s SPLITS [SPLITS ...], --splits SPLITS [SPLITS ...]
                            Splits to sample. Should be already includedinto the
                            dataset object.
    -d DEST, --dest DEST  File to save scores in
    -v, --verbose         Be verbose
    -c CONFIG, --config CONFIG
                            Config pkl for loading the model configuration. If not
                            specified, hyperparameters are read from config.py
    --models MODELS [MODELS ...]
                            path to the models

Advanced features

Other features such as online learning or interactive NMT protocols are implemented in the interactiveNMT branch.

Resources

Citation

If you use this toolkit in your research, please cite:

@unpublished{nmt-keras18,
	title={{NMT-Keras}: a Very Flexible Toolkit with a Focus on Interactive {NMT} and Online Learning},
	author={Peris, Álvaro and Casacuberta, Francisco},
	note={\textit{arXiv:1807.03096}}, 
	year={2018}
}

NMT-Keras was used in a number of papers:

Acknowledgement

Much of this library has been developed together with Marc Bolaños (web page) for other sequence-to-sequence problems.

To see other projects following the same philosophy and style of NMT-Keras, take a look to:

TMA for egocentric captioning based on temporally-linked sequences.

VIBIKNet for visual question answering.

ABiViRNet for video description.

Sentence SelectioNN for sentence classification and selection.

Warning!

There is a known issue with the Theano backend. When running NMT-Keras, it will show the following message:

[...]
raise theano.gof.InconsistencyError("Trying to reintroduce a removed node")
InconsistencyError: Trying to reintroduce a removed node

It is not a critical error, the model keeps working and it is safe to ignore it. However, if you want the message to be gone, use the Theano flag optimizer_excluding=scanOp_pushout_output.

Contact

Álvaro Peris (web page): [email protected]

Latest Releases
0.3
 Feb. 13 2018
NMT-Keras (Keras 2)
 Jul. 18 2017
Store dataset at 'datasets'
 Jun. 27 2017
Stable version at 1st June
 Jun. 1 2017
First release
 Apr. 27 2017