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Commits on Apr 19, 2019

  1. Add files via upload

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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  2. Add files via upload

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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  3. Removed unnecessary files and added the training data.

    @matthewkennedy5
    matthewkennedy5 committed Apr 19, 2019
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  4. Merge branch 'planB' of https://github.com/matthewkennedy5/RRNN into … 

    …planB
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  5. Removed unnecessary files for real

    @matthewkennedy5
    matthewkennedy5 committed Apr 19, 2019
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  6. Update tree_methods.py

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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  7. The hyperparameters are now loaded from an external JSON parameter fi… 

    …le instead of coded into the .py file. This makes it easier to keep track of many runs.
    @matthewkennedy5
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  8. Merge branch 'planB' of https://github.com/matthewkennedy5/RRNN into … 

    …planB
    @matthewkennedy5
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  9. Added code to perform validation on external saved model checkpoints.

    @matthewkennedy5
    matthewkennedy5 committed Apr 19, 2019
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  10. Fixed inputs to RRNNforGRU constructor

    @matthewkennedy5
    matthewkennedy5 committed Apr 19, 2019
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  11. Added a Dataset subclass to represent the enwik8 data. This way we ca… 

    …n use Pytorch DataLoaders.
    @matthewkennedy5
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  12. Modified to include the new dataloaders from standard_data.py.

    @matthewkennedy5
    matthewkennedy5 committed Apr 19, 2019
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  13. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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  14. Update tree_methods.py

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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  15. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 19, 2019
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Commits on Apr 20, 2019

  1. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  2. Update trainer_temp.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  3. Update tree_methods.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  4. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  5. Removed all codes about Nodes etc.

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  6. Update tree_methods.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  7. Update trainer_temp.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  8. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 20, 2019
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  9. Allowing the EnWik8Clean dataset to have a variable number of samples… 

    … instead of the default 10,000.
    @matthewkennedy5
    matthewkennedy5 committed Apr 20, 2019
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  10. Updated the training code to work with Xin's new vectorized implement… 

    …ation.
    @matthewkennedy5
    matthewkennedy5 committed Apr 20, 2019
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Commits on Apr 21, 2019

  1. Turned off pretrained_weights by default since they cause exploding g… 

    …radients.
    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  2. Removed unused params.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  3. Updated margin function

    @xinqianpku
    xinqianpku committed Apr 21, 2019
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  4. Update trainer_temp.py

    @xinqianpku
    xinqianpku committed Apr 21, 2019
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  5. Support margin loss

    @xinqianpku
    xinqianpku committed Apr 21, 2019
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  6. Put in Xin's fix for the accuracy calculation.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  7. Merged changes.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  8. Made the display of the losses more orderly.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  9. Allowed for variable batch sizes, such as for the last batch in an ep… 

    …och.
    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  10. Made validation work with the new vectorized code.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  11. Now prints the validation loss and accuracy during training.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  12. Added GPU support. One epoch of 10k samples now takes 30 seconds (ins… 

    …tead of 30 minutes).
    @matthewkennedy5
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  13. Divide the loss2...loss4 by the batch_size instead of sum over the ba… 

    …tch.
    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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  14. Accidentally overwrote loss history with the accuracy history.

    @matthewkennedy5
    matthewkennedy5 committed Apr 21, 2019
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Commits on Apr 22, 2019

  1. Removed unnecessary variabls

    @xinqianpku
    xinqianpku committed Apr 22, 2019
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  2. Removed unnecessary packages 

    Also added code for testing on Xin's Windows desktop
    @xinqianpku
    xinqianpku committed Apr 22, 2019
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  3. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 22, 2019
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  4. Now saves the intermittent train, accuracy, and structure history so … 

    …all is not lost if something bad happens before the run ends.
    @matthewkennedy5
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  5. Added a new parameter for how often to pickle the loss history.

    @matthewkennedy5
    matthewkennedy5 committed Apr 22, 2019
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  6. Adapted the results visualizer for the planB output format.

    @matthewkennedy5
    matthewkennedy5 committed Apr 22, 2019
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  7. Checkpoints now include the epoch number in their filename.

    @matthewkennedy5
    matthewkennedy5 committed Apr 22, 2019
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  8. Added hidden_size to the random search hyperparameters.

    @matthewkennedy5
    matthewkennedy5 committed Apr 22, 2019
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Commits on Apr 23, 2019

  1. Added the epoch as an input to checkpoint_model.

    @matthewkennedy5
    matthewkennedy5 committed Apr 23, 2019
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  2. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 23, 2019
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Commits on Apr 24, 2019

  1. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 24, 2019
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  2. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 24, 2019
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  3. Made two separate optimizers for the two training modes. Hopefully th… 

    …is fixes the weird periodic spike issue.
    @matthewkennedy5
    matthewkennedy5 committed Apr 24, 2019
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  4. Added code to extract the weight matrices and bias vectors from the k… 

    …eras .h5 save file.
    @matthewkennedy5
    matthewkennedy5 committed Apr 24, 2019
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  5. Optimized forward pas

    @xinqianpku
    xinqianpku committed Apr 24, 2019
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  6. Optimized tree distance function

    @xinqianpku
    xinqianpku committed Apr 24, 2019
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Commits on Apr 26, 2019

  1. Update trainer_temp.py

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  2. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  3. Fixed a bug in loss2

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  4. Fixed a bug in loss2

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  5. Fixed a bug in Loss2

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  6. Fixed a bug in loss2

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  7. Update GRU.py

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  8. Update tree_methods.py

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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  9. load and save structures and losses

    @xinqianpku
    xinqianpku committed Apr 26, 2019
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Commits on Apr 27, 2019

  1. Support stage searching and fixing

    @xinqianpku
    xinqianpku committed Apr 27, 2019
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  2. Changed the form of y from one-hot to index labels to prevent exhorbi… 

    …tantly large word-level one-hot vectors.
    @matthewkennedy5
    matthewkennedy5 committed Apr 27, 2019
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  3. Finalized the implementation of the Penn Treebank dataset.

    @matthewkennedy5
    matthewkennedy5 committed Apr 27, 2019
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Commits on Apr 28, 2019

  1. Revise validate function 

    Make validation for each data sample, but not a batch of samples. Record the searched structure under ./batch_history/val.txt.
    @xinqianpku
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  2. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 28, 2019
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  3. Update trainer.py

    @xinqianpku
    xinqianpku committed Apr 28, 2019
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  4. Create .gitignore

    @xinqianpku
    xinqianpku committed Apr 28, 2019
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  5. Added a script for generating a JSON file with random hyperparameters.

    @matthewkennedy5
    matthewkennedy5 committed Apr 28, 2019
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  6. Added the SST sentiment analysis dataset.

    @matthewkennedy5
    matthewkennedy5 committed Apr 28, 2019
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Commits on Apr 29, 2019

  1. accidental merge

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    matthewkennedy5 committed Apr 29, 2019
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  2. First steps at a script to convert Keras GRU weights to Pytorch tensors.

    @matthewkennedy5
    matthewkennedy5 committed Apr 29, 2019
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  3. Made the scoring hidden size range more realistic in the random searc… 

    …h (too small previously).
    @matthewkennedy5
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  4. Forgot to actually add the data to the zero-padded tensor so it was j… 

    …ust outputting all zeros for the SST dataset.
    @matthewkennedy5
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  5. Updated display code

    @matthewkennedy5
    matthewkennedy5 committed Apr 29, 2019
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Commits on May 3, 2019

  1. Update GRU.py

    @xinqianpku
    xinqianpku committed May 3, 2019
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  2. Update tree_methods.py

    @xinqianpku
    xinqianpku committed May 3, 2019
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  3. Update trainer.py

    @xinqianpku
    xinqianpku committed May 3, 2019
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Commits on May 5, 2019

  1. Made the model save after training.

    @matthewkennedy5
    matthewkennedy5 committed May 5, 2019
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  2. Wrote code to convert the Keras saved weights to Pytorch format.

    @matthewkennedy5
    matthewkennedy5 committed May 5, 2019
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  3. Increased the number of validation samples to 10000 and the number of… 

    … test to 20,000 for increased precision.
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  4. Divides loss2 and loss4 by the batch size for consistent comparison w… 

    …ith datasets of different sequence lengths.
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  5. Changed the gru_model parameters to the trained baseline parameters f… 

    …rom keras_gru.
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  6. Added code to save Adam's configuration during training for smooth wa… 

    …rm-starting.
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  7. Added functionality for the PTB dataset for the keras baseline GRU.

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Commits on May 6, 2019

  1. Enabled normalization of PTB and SST based on training mean and stand… 

    …ard deviation.
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  2. Serialized normalization statistics so the program starts training mo… 

    …re quickly.
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  3. Found better ground truth GRU parameters for the wiki dataset.

    @matthewkennedy5
    matthewkennedy5 committed May 6, 2019
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  4. Rough PTB random search parameters.

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    matthewkennedy5 committed May 6, 2019
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  5. GRU baseline PTB fine random search range.

    @matthewkennedy5
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  6. Now works for the SST dataset, but somehow I broke it for the other t… 

    …wo datasets. Not sure what the issue is since the code should be the same.
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  7. Ranges for course SST random hyperparameter baseline search.

    @matthewkennedy5
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Commits on May 8, 2019

  1. SST fine random search ranges.

    @matthewkennedy5
    matthewkennedy5 committed May 8, 2019
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  2. Re-add SST dataset 

    Somehow a prior commit where I added the sst dataset got reverted, so I included those changes manually here again. Hopefully no other issues remain with the accidental revert.
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  3. Random hyperparameter search for the RRNN. 

    The ranges listed in lines 428-440 are the hyperparameter ranges used for the initial rough wiki random search.
    @matthewkennedy5
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  4. RRNN PTB rough hyperparameter ranges.

    @matthewkennedy5
    matthewkennedy5 committed May 8, 2019
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  5. Fixed a CUDA/CPU tensor type bug in the normalization.

    @matthewkennedy5
    matthewkennedy5 committed May 8, 2019
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  6. RRNN SST rough param ranges.

    @matthewkennedy5
    matthewkennedy5 committed May 8, 2019
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Commits on May 15, 2019

  1. RRNN Wiki fine param ranges.

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    matthewkennedy5 committed May 15, 2019
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  2. RRNN PTB fine hp ranges.

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    matthewkennedy5 committed May 15, 2019
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Commits on May 21, 2019

  1. Added code to evaluate the test set.

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    matthewkennedy5 committed May 21, 2019
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