ranjaykrishna/iq

Information Maximizing Visual Question Generation

iq's Issues

vae_val_dataset_weights.json missing

Hi! When running train_iq.py, I couldn't find vae_val_dataset_weights.json. Do you know where I can download or generate this file?

Getting an Error "AttributeError: 'dict' object has no attribute 'encode'"

Hi @ranjaykrishna ,

i am trying to execute python utils/vocab.py getting an error
"Traceback (most recent call last):
File "utils/vocab.py", line 144, in
vocab = build_vocab(args.questions, args.cat2ans, args.threshold)
File "utils/vocab.py", line 93, in build_vocab
answer = tokenize(answer.encode('utf8'))
AttributeError: 'dict' object has no attribute 'encode'"

can you help me to resolve this issue...

Thanks & Regards,
Manikantha Sekhar...

The loss got NAN

Hello Ranjay, thanks for your work.
I have run the train_iq.py using the default lr 0.001, but after 4 epochs, the loss and other metrics got Nan. Is there something wrong with the training script?
Looking forward to your reply. Thanks again.

Where can I found ans2cat.json?

Hi, Ranjay

Thanks for releasing the code.

The input parameters of "iq/utils/store_dataset.py" includes a path to the processed "ans2cat.json file". There isn't a processed code for generating this file. Can it be done by exchanging the position of key-value pair in here?

Thanks
Becky

Is it possible to release the pretrained file?

Is it possible to release the pretrained file?

Problem with inference script and replication of paper results

The inference script provided in the repo doesn't seem to work in its current form. I had to make some changes to it to make it run. In doing so, I am not able to replicate the results provided in the paper. The quantitative metrics give a much lower score in comparison to what is reported in the paper.
Please help us point out the mistake we are doing or update the inference/training file with the correct one.
Thank you.

maybe some error in train_iq.py?

In line 186 of train_iq.py, perhaps "scheduler" should be changed to "info_scheduler"? Otherwise, it seems that "info_scheduler" has not been updated continuously? This may be the reason why the loss gradually becomes NaN during the training process.

missing the body of function get_vae_loader() in evaluate_iq.py

Hi Ranjay,
Would you please kindly fix this issue? Thanks a lot

How to specify the model type in train.py ?

I tried to train the model as written in readme.
However, when I tried to specify model_type, I got an error:

$ python train_iq.py --model-type ia2q

usage: train_iq.py [-h] [--model-path MODEL_PATH] [--crop-size CROP_SIZE] [--log-step LOG_STEP] [--save-step SAVE_STEP] [--eval-steps EVAL_STEPS]
                   [--eval-every-n-steps EVAL_EVERY_N_STEPS] [--num-epochs NUM_EPOCHS] [--batch-size BATCH_SIZE] [--num-workers NUM_WORKERS]
                   [--learning-rate LEARNING_RATE] [--info-learning-rate INFO_LEARNING_RATE] [--patience PATIENCE] [--max-examples MAX_EXAMPLES] [--lambda-gen LAMBDA_GEN]
                   [--lambda-z LAMBDA_Z] [--lambda-t LAMBDA_T] [--lambda-a LAMBDA_A] [--lambda-i LAMBDA_I] [--lambda-z-t LAMBDA_Z_T] [--vocab-path VOCAB_PATH]
                   [--dataset DATASET] [--val-dataset VAL_DATASET] [--train-dataset-weights TRAIN_DATASET_WEIGHTS] [--val-dataset-weights VAL_DATASET_WEIGHTS]
                   [--cat2name CAT2NAME] [--load-model LOAD_MODEL] [--rnn-cell RNN_CELL] [--hidden-size HIDDEN_SIZE] [--num-layers NUM_LAYERS] [--max-length MAX_LENGTH]
                   [--encoder-max-len ENCODER_MAX_LEN] [--bidirectional] [--use-glove] [--embedding-name EMBEDDING_NAME] [--num-categories NUM_CATEGORIES]
                   [--dropout-p DROPOUT_P] [--input-dropout-p INPUT_DROPOUT_P] [--num-att-layers NUM_ATT_LAYERS] [--z-size Z_SIZE] [--no-image-recon] [--no-answer-recon]
                   [--no-category-space]
train_iq.py: error: unrecognized arguments: --model-type ia2q

How can I successfully specify model_type?