* Add ReutersTrainer, ReutersEvaluator options in Factory classes
* Add Reuters to Kim-CNN command line arguments
* Fix SST dataset path according to changes in Kim-CNN args
The dataset path in args.py was made to point at the dataset folder rather than dataset/SST folder. Hence SST folder was added to paths in the SST dataset class
* Add Reuters dataset class, and support in __main__
* Add Reuters dataset trainers and evaluators
* Remove debug print statement in reuters_evaluator
* Fix rounding bug in reuters_trainer and reuters_evaluator
* Add LSTM for baseline text classification measurements
* Add eval metrics for lstm_baseline
* Set batch_first param in lstm_baseline
* Remove onnx args from lstm_baseline
* Pack padded sequences in LSTM_baseline
* Add TensorBoardX support for Reuters trainer
* Add Arxiv Academic Paper Dataset (AAPD)
* Add Hidden Bottleneck Layer to BiLSTM
* Fix packing of padded tensors in Reuters
* Add cmdline args for Hidden Bottleneck Layer for BiLSTM
* Include pre-padding lengths in AAPD dataset
* Remove duplication of preprocessing code in AAPD
* Remove batch_size condition in ReutersTrainer
* Add ignore_lengths option to ReutersTrainer and ReutersEvaluator
* Add AAPDCharQuantized and ReutersCharQuantized
* Rename Reuters_hierarchical to ReutersHierarchical
* Add CharacterCNN for document classification
* Update README.md for CharacterCNN
* Fix table in README.md for CharacterCNN
* Add AAPDHierarchical for HAN
* Update HAN for changes in Reuters dataset endpoints
* Fix bug in CharCNN when running on CPU
* Add AAPD dataset support for KimCNN
* Fix dataset paths for SST-1
* Fix dimensions of FC1 in CharCNN
* Add model checkpointing for Reuters based on F1
* Refactor LSTM baseline __main__
* Add precision, recall and F1 to Reuters evaluator
* Checkpoint only at the end of an epoch for ReutersTrainer
Add detailed log printing for dev evaluations
* Fix log_template and dev_log_template in ReutersTrainer
* Add IMDB dataset
* Fix duplicate printing of header in ReutersTrainer
* Add support for single_label datasets in ReutersTrainer
* Add support for IMDB dataset in lstm_baseline and lstm_reg
* Fix evaluator call in main method of HAN
* Add IMDB for HAN
* Fix for single_label
* Fix evaluate_dataset method for single_label datasets
* Reduce default patience to 5 epochs before early stopping
* Revert change to save_state rather than the entire model
* Add Yelp 2018 dataset
* Integrate Yelp2018 with LSTM baseline
* Replace Yelp2018 with Yelp2014 dataset
* Add Yelp2014 to LSTM Baseline
* Integrate Yelp14 into LSTM Regularization
* Remove dropout in HBL for LSTM Baseline and Reg
* Add Yelp for HAN
* Fix the saving issue for HAN
* Fix loading for HAN
* Fix typo in ReutersEvaluator
* Print to STDOUT rather than logger
* Print XML-CNN eval to STDOUT rather than logger
* Update max_length for IMDB dataset
* Add single_label support for char_cnn
* Fix evaluation method for char_cnn
* Remove unwanted parameters from ReutersTrainer and ReutersEval
* Fix code formatting in lstm_reg/args
* Add support for IMDB and Yelp in KimCNN
* Fix single_label incorporation
* Remove unnecessary conditions
* Fix num_classes in Yelp2014
* Add single_label support for XML-CNN
* Fix call to evaluator in XML-CNN
* Address PEP8 issues
* Address PEP8 issues
* Address PEP8 issues
* Address PEP8 issues
* Add ReutersTrainer, ReutersEvaluator options in Factory classes
* Add Reuters to Kim-CNN command line arguments
* Fix SST dataset path according to changes in Kim-CNN args
The dataset path in args.py was made to point at the dataset folder rather than dataset/SST folder. Hence SST folder was added to paths in the SST dataset class
* Add Reuters dataset class, and support in __main__
* Add Reuters dataset trainers and evaluators
* Remove debug print statement in reuters_evaluator
* Fix rounding bug in reuters_trainer and reuters_evaluator
* Add LSTM for baseline text classification measurements
* Add eval metrics for lstm_baseline
* Set batch_first param in lstm_baseline
* Remove onnx args from lstm_baseline
* Pack padded sequences in LSTM_baseline
* Add TensorBoardX support for Reuters trainer
* Add Arxiv Academic Paper Dataset (AAPD)
* Add Hidden Bottleneck Layer to BiLSTM
* Fix packing of padded tensors in Reuters
* Add cmdline args for Hidden Bottleneck Layer for BiLSTM
* Include pre-padding lengths in AAPD dataset
* Remove duplication of preprocessing code in AAPD
* Remove batch_size condition in ReutersTrainer
* Add ignore_lengths option to ReutersTrainer and ReutersEvaluator
* Add AAPDCharQuantized and ReutersCharQuantized
* Rename Reuters_hierarchical to ReutersHierarchical
* Add CharacterCNN for document classification
* Update README.md for CharacterCNN
* Fix table in README.md for CharacterCNN
* Add AAPDHierarchical for HAN
* Update HAN for changes in Reuters dataset endpoints
* Fix bug in CharCNN when running on CPU
* Add AAPD dataset support for KimCNN
* Fix dataset paths for SST-1
* Fix dimensions of FC1 in CharCNN
* Add model checkpointing for Reuters based on F1
* Refactor LSTM baseline __main__
* Add precision, recall and F1 to Reuters evaluator
* Add ReutersTrainer, ReutersEvaluator options in Factory classes
* Add Reuters to Kim-CNN command line arguments
* Fix SST dataset path according to changes in Kim-CNN args
The dataset path in args.py was made to point at the dataset folder rather than dataset/SST folder. Hence SST folder was added to paths in the SST dataset class
* Add Reuters dataset class, and support in __main__
* Add Reuters dataset trainers and evaluators
* Remove debug print statement in reuters_evaluator
* Fix rounding bug in reuters_trainer and reuters_evaluator
* Add LSTM for baseline text classification measurements
* Add eval metrics for lstm_baseline
* Set batch_first param in lstm_baseline
* Remove onnx args from lstm_baseline
* Pack padded sequences in LSTM_baseline
* Add TensorBoardX support for Reuters trainer
* Add Arxiv Academic Paper Dataset (AAPD)
* Add Hidden Bottleneck Layer to BiLSTM
* Fix packing of padded tensors in Reuters
* Add cmdline args for Hidden Bottleneck Layer for BiLSTM
* Include pre-padding lengths in AAPD dataset
* Remove duplication of preprocessing code in AAPD
* Remove batch_size condition in ReutersTrainer
* Add ignore_lengths option to ReutersTrainer and ReutersEvaluator
* Add AAPDCharQuantized and ReutersCharQuantized
* Rename Reuters_hierarchical to ReutersHierarchical
* Add CharacterCNN for document classification
* Update README.md for CharacterCNN
* Fix table in README.md for CharacterCNN
* Add AAPDHierarchical for HAN
* Update HAN for changes in Reuters dataset endpoints
* Fix bug in CharCNN when running on CPU
Ralph Tang