ComplexQNN

The ComplexQNN is a quantum-inspired complex-valued neural network for NLP tasks.

Dependencies

1. pytorch>=1.12
2. allennlp==2.10
3. complexPyTorch=0.4

Allennlp train command example

allennlp train config/complexqnn.jsonnet --include-package work -s ./result/mytrain2 -f --dry-run

Some notes about allennlp

1. --dry-run # load dataset but do not train the model
2. -f # force training, this command will override the save path
3. -s # save path
4. --include-package $path # personal work path including model, classifier and so on
5. config/xxx.jsonnet # config file with jsonnet format

Our train command

CNN

allennlp train config/cnn.jsonnet --include-package work -s ./result/cr_cnn -f --dry-run

GRU

allennlp train config/gru.jsonnet --include-package work -s ./result/mpqa_gru -f --dry-run

ELMo

allennlp train config/elmo.jsonnet --include-package work -s ./result/sst2_emlo -f

BERT or RoBERTa

allennlp train config/bert.jsonnet --include-package work -s ./result/subj_bert -f

ComplexTextCNN

allennlp train config/complexcnn.jsonnet --include-package work -s ./result/cr_complexcnn -f

ComplexQNN

allennlp train config/complexqdnn.jsonnet --include-package work -s ./result/subj_complexqnn -f

Dataset

Please modify the variable "task_name" in model.jsonnet to change different datasets.

Other command

# delete training models
rm ./result/*/*_state_*.th -f