• Stars
    star
    238
  • Rank 165,317 (Top 4 %)
  • Language
    Python
  • License
    MIT License
  • Created over 7 years ago
  • Updated about 1 year ago

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Repository Details

QRNN implementation for TensorFlow

Tensorflow QRNN

QRNN implementation for TensorFlow. Implementation refer to below blog.

New neural network building block allows faster and more accurate text understanding

qrnn.PNG

Dependencies

  • TensorFlow: 0.12.0
  • scikit-learn: 0.18.1 (for working check)

How to run

Forward Test

To confirm forward propagation, run below script.

python test_tf_qrnn_forward.py

Working Check

To confirm the performance of QRNN compare with baseline(LSTM), run below script. Dataset is scikit-learn's digit dataset.

python test_tf_qrnn_work.py

You can check the calculation result by TensorBoard.

tensorboard.PNG

For example.

tensorboard --logdir=./summary/qrnn

Experiments

Baseline(LSTM) Working check
Iter 0: loss=2.473149299621582, accuracy=0.1171875
Iter 100: loss=0.31235527992248535, accuracy=0.921875
Iter 200: loss=0.1704500913619995, accuracy=0.9453125
Iter 300: loss=0.0782063901424408, accuracy=0.9765625
Iter 400: loss=0.04097321629524231, accuracy=1.0
Iter 500: loss=0.023687714710831642, accuracy=0.9921875
Iter 600: loss=0.07718617469072342, accuracy=0.9765625
Iter 700: loss=0.02005828730762005, accuracy=0.9921875
Iter 800: loss=0.006271282210946083, accuracy=1.0
Iter 900: loss=0.007853344082832336, accuracy=1.0
Testset Accuracy=0.9375
takes 15.83749008178711 seconds.
QRNN Working check
Iter 0: loss=6.942812919616699, accuracy=0.0703125
Iter 100: loss=1.6366937160491943, accuracy=0.59375
Iter 200: loss=0.7058627605438232, accuracy=0.796875
Iter 300: loss=0.3940553069114685, accuracy=0.8984375
Iter 400: loss=0.2623080909252167, accuracy=0.9375
Iter 500: loss=0.3940059542655945, accuracy=0.921875
Iter 600: loss=0.1395827978849411, accuracy=0.96875
Iter 700: loss=0.11944477260112762, accuracy=0.984375
Iter 800: loss=0.1389300674200058, accuracy=0.9765625
Iter 900: loss=0.09582504630088806, accuracy=0.96875
Testset Accuracy=0.9140625
takes 13.540465116500854 seconds.

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