• Stars
    star
    469
  • Rank 93,595 (Top 2 %)
  • Language
    Python
  • License
    MIT License
  • Created almost 8 years ago
  • Updated over 7 years ago

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Repository Details

TensorFlow implementation of "Pointer Networks"

Pointer Networks in Tensorflow

TensorFlow implementation of Pointer Networks.

model

Support multithreaded data pipelines to reduce I/O latency.

Requirements

Usage

To train a model:

$ python main.py --task=tsp --max_data_length=20 --hidden_dim=512 # download dataset used in the paper
$ python main.py --task=tsp --max_data_length=10 --hidden_dim=128 # generate dataset itself

To train a model:

$ python main.py
$ tensorboard --logdir=logs --host=0.0.0.0

To test a model:

$ python main.py --is_train=False

Results

Train/Test loss of max_data_length=10 after 24,000 steps:

$ python main.py --task=tsp --max_data_length=10 --hidden_dim=128
$ ...
$ 2017-01-18 17:17:48,054:INFO::
$ 2017-01-18 17:17:48,054:INFO::test loss: 0.00149279157631
$ 2017-01-18 17:17:48,055:INFO::test pred: [1 6 2 5 4 3 0 0 0 0 0]
$ 2017-01-18 17:17:48,057:INFO::test true: [1 6 2 5 4 3 0 0 0 0 0] (True)
$ 2017-01-18 17:17:48,059:INFO::test pred: [1 3 8 4 7 5 2 6 0 0 0]
$ 2017-01-18 17:17:48,059:INFO::test true: [1 3 8 4 7 5 2 6 0 0 0] (True)
$ 2017-01-18 17:17:48,058:INFO::test pred: [ 1  8  3  7  9  5  6  4  2 10  0]
$ 2017-01-18 17:17:48,058:INFO::test true: [ 1  8  3  7  9  5  6  4  2 10  0] (True)

model

Train/Test loss of max_data_length=20 after 16,000 steps:

$ python main.py --task=tsp --max_data_length=20 --hidden_dim=512
$ ...
$ 2017-01-18 17:30:44,738:INFO::
$ 2017-01-18 17:30:44,739:INFO::test loss: 0.0501566007733
$ 2017-01-18 17:30:44,739:INFO::test pred: [ 1  3 16 18  6  2  7  4  5 15 10  8 13 11 17 20 19 14  9 12  0]
$ 2017-01-18 17:30:44,740:INFO::test true: [ 1  3 16 18  6  2  7  4  5 15 10  8 13 11 17 20 19 14  9 12  0] (True)
$ 2017-01-18 17:30:44,741:INFO::test pred: [ 1  4 12  8  2 17 20  3 18 14 16 11 13 15  7 10  9  6 19  5  0]
$ 2017-01-18 17:30:44,741:INFO::test true: [ 1  4 12  8  2 17 20  3 18 14 16 11 13 15  7 10  9  6 19  5  0] (True)
$ 2017-01-18 17:30:44,742:INFO::test pred: [ 1  8 16 20 19 14 18  2  9 12 15 11  3 13  5  6  7  4 17 10  0]
$ 2017-01-18 17:30:44,742:INFO::test true: [ 1  8 16 20 19 14 18  2  9 12 15 11  3 13  5  6  7  4 17 10  0] (True)

model

Author

Taehoon Kim / @carpedm20

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