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Starter Code for MemexQA dataset

Dataset website

Explore dataset:

Dataset download

(You don't have to download "shown_photos.tgz" if you use our image features "photos_inception_resnet_v2_l2norm.npz")
	├── album_info.json   # album data:
	├── glove.6B.100d.txt # word vectors for baselines:
	├── shown_photos.tgz (7.5GB)  # all photos:
	├── photos_inception_resnet_v2_l2norm.npz # photo features:
	├── qas.json # QA data:
	└── test_question.ids # testset Id:

Starter Code: word embedding w/ simple LSTM

Dependencies: tensorflow >= 1.0, tqdm, numpy...

Code Structure:
	1. # main code for training and testing
	2. # the LSTM model
	3. # code to preprocess data into pickle files for
	4. # tester class
	5. # trainer class
	6. # some helpful function for the model and evaluation

1 preprocess

	$ python starter_code/ memexqa_dataset_v1.1/qas.json memexqa_dataset_v1.1/album_info.json memexqa_dataset_v1.1/test_question.ids memexqa_dataset_v1.1/photos_inception_resnet_v2_l2norm.npz memexqa_dataset_v1.1/glove.6B.100d.txt started_test/prepro

2 train

	$ python starter_code/ starter_test/prepro/ starter_test/baselines --modelname simple_lstm --keep_prob 0.7 --is_train

3 test

	$ python starter_code/ starter_test/prepro/ starter_test/baselines --modelname simple_lstm --use_char --keep_prob 0.7 --is_test --load_best

	Trained for 100 epoch, testing accuracy: 54.8%